The past decade has seen an explosive adoption of artificial intelligence (AI) and automation in supply chains. This rise in new technologies has been a valuable opportunity for businesses to boost efficiency, increase customer satisfaction, and minimize costs. Read on to discover how your team can bring about a new era of efficiency and resilience by adopting these tools.

The growth of cutting-edge technology in the supply chain

Companies with supply chains at their core are quickly employing state-of-the-art technologies to support long-term business growth. The need for enhanced operational efficiency and cost reduction, the rising complexities and interconnected nature of supply chains, the exponential growth of data and analytics, and increasing customer expectations for faster deliveries, personalization, and transparency have triggered this accelerated adoption. Because the integration of technologies has emerged as a powerful catalyst for achieving success amid a rapidly changing landscape, we are taking a closer look at the principal systems utilized by supply chain organizations today.

5 Key AI and automation technologies driving supply chain transformations

Considering the ever-evolving supply chain environment, it is no surprise that teams are turning to robust AI and automation technologies to enhance efficiency and establish a competitive advantage. Here are six solutions organizations are implementing to transform their operations:

The metaverse

The metaverse — a virtual reality space — has opened the doors to unique opportunities for supply chain teams to reconcile supply and demand. Within this environment, businesses can create virtual simulations and utilize real-time monitoring that provides greater visibility into processes, facilities, inventory, and capacity.

According to the Accenture Technology Vision 2022 report, 71% of supply chain management executives believe the metaverse will positively impact organizations. These benefits include:

• Improving visibility at all stages of production and distribution.
• Boosting demand planning and problem-solving.
• Increasing connectivity and chances for collaboration.
• Empowering sustainability efforts.

Predictive analytics

Solutions that equip your company with robust analytics provide the capability to analyze historical data and up-to-date information. These tools will be a cornerstone in accurately forecasting demand, anticipating market trends, and optimizing inventory levels.

Warehouse operations teams have embraced analytics to anticipate demand fluctuations and ensure timely order fulfillment. While professionals in logistics, on the other hand, take advantage of real-time data to optimize route planning, predict transportation capacity needs, and proactively manage disruptions.

Internet of Things (IoT) and sensors

IoT devices and sensors are revolutionizing the supply chain as we know it by connecting physical assets and products to the Internet. As a result, supply chain organizations have access to real-time insights and greater oversight. In addition, using AI in conjunction with IoT applications is a powerful approach to keep your business consistently up-to-date and safeguarded against risk.

In the modern supply chain, teams are leveraging IoT systems and sensors to:

• Track the location and condition of goods during transportation.
• Monitor warehouse environmental factors (e.g., temperature and humidity).
• Optimize equipment maintenance schedules.

Robotic process automation (RPA)

Now considered a game changer in the supply chain, robotic process automation (RPA) has become an increasingly popular strategy for automating repetitive, manual tasks. These tasks include order processing, data entry, inventory management, and shipment tracking, to name a few. RPA tech is here to stay, with Grand View Research projecting the global RPA market — valued at $2,322.9 million in 2022 — to expand at a compound annual growth rate of 39.9% until 2030.

Machine learning

Today, AI applications are adopted to analyze massive amounts of data and uncover valuable insights. The patterns and trends discovered can help organizations streamline routing, identify anomalies, and improve decision-making.

It is important to remember that AI and automation technologies are not one-size-fits-all. It will be necessary to assess different potential systems and how they might fit into your unique strategy and technology stack for the best results.

What are the benefits of integrating new technologies? 

Transformative technologies that enable unique business objectives provide supply chain organizations with a myriad of advantages, such as:

• Boosting supply chain management: Cutting-edge technology equips teams with the real-time visibility and tracking capabilities needed to achieve comprehensive operational oversight. This technology enables proactive monitoring and bottleneck management.
• Improving customer experience: Solutions that support accurate demand forecasting, more efficient order processing, and timely delivery help minimize the impact of disruptions and increase long-term customer satisfaction.
• Removing barriers between different business functions: Introducing AI and automation breaks down silos and promotes cross-functional collaboration, leading to better coordination and faster decision-making in a more efficient value chain.
• Optimizing and streamlining operations: Automation is an efficient tool for eliminating repetitive tasks and promoting efficiency while minimizing human error. With AI, teams can enhance demand forecasting and inventory management to improve operational performance.
• Driving cost-efficiency: Supportive technologies pinpoint where there is room to save costs and improve resource use — maximizing long-term profitability.

Adopting AI and automation solutions successfully 

While the supply chain continues to grow more complex, market analysis from Research and Markets reveals that AI-enabled supply chains are 67% more effective than non-AI-enabled supply chains. This descrepancy is due to mitigated risks and lower overall expenses. To introduce new tech successfully, be sure to:

1. Establish a focused AI and automation strategy where you have outlined specific goals, priorities, and desired outcomes.
2. Create an environment that embraces innovation by encouraging collaboration, communication, and upskilling among team members.
3. Start with smaller pilot projects, learn from the process, and gradually scale your use of technologies.

Oracle Cloud solutions can help your organization prepare for the future by creating metaverse-ready enterprise resource planning (ERP) systems. By bringing together the right teams and technology, Oracle and Inspirage can empower your business to optimize its use of AI and automation technologies.

Contact us today to learn more about our customized solutions and world-class Oracle Cloud expertise.

As supply chain disruptions and uncertainty continue, organizations have embraced artificial intelligence (AI) to safeguard their operations and stay ahead of the competition. Discover which AI technologies teams have integrated into their procedures and how these groundbreaking solutions have impacted forecasting, planning, and budgeting.   

The accelerated adoption of AI technology  

After the COVID-19 pandemic revealed how susceptible the global supply chain is to disruptions, organizations quickly recognized the need to improve agility and resilience. Teams are increasingly turning to AI tools to deliver the powerful optimization capabilities required for more accurate planning and financing — all while reducing costs and promoting sustainability. What has contributed to the widespread adoption of AI across the entire value chain? Here are some of the key drivers:

1. The increasing complexity of supply chain networks, global markets, and consumer demands has necessitated solutions that can handle massive amounts of data and streamline operations.  
2. Organizations need greater operational efficiency and flexibility to respond quickly to market changes and demand fluctuations.  
3. With large datasets available, teams need AI-powered analytics and machine learning models to extract actionable insights and enable informed decision-making.  
4. Businesses want to identify and mitigate potential disruptions and boost resilience to ensure operational continuity in the face of future uncertainties. 

Utilizing AI tools for forecasting, planning, and finance functions    

Enhancing organizational planning and management is crucial to optimizing operations and controlling costs — which is more important than ever while supply chain uncertainty continues. Consider the following AI-driven solutions that businesses are introducing to reach their goals:  

1. Machine learning models and predictive analytics
   AI-powered demand forecasting tools use advanced algorithms to analyze historical data, market trends, and other external factors. These tools enable companies to make more accurate predictions about future demand levels. Actionable insights into what is needed to maintain inventory levels and reduce stockouts support the organizational planning process.  

2. Supply chain optimization
   AI-optimization tools empower supply chain managers to maximize the potential of every facet of the business — from inventory levels and transportation costs to production schedules and demand fluctuations. As a result, these algorithms help align resource utilization with forecasting and budgeting processes.   

3. Robotic process automation (RPA)
   By deploying RPA, organizations can automate repetitive tasks within supply chain processes. These processes include everyday undertakings such as order processing, inventory management, and invoice reconciliation. According to Adobe, executives are also looking for AI to alleviate menial tasks like paperwork (82%), scheduling (79%), and timesheets (78%). Interweaving this technology into existing systems frees up human resource teams, reduces errors, and improves efficiency — inevitably enhancing planning and financing. 

4. Blockchain technology
   With Gartner reporting that 60% of CIOs plan to adopt some level of blockchain technologies in the coming years, it is clear why this has become a big topic of discussion in the supply chain landscape. Visibility has become increasingly essential, and blockchain technology enables transparent, secure, and traceable transactions across production and distribution networks. By using smart contracts and distributed ledgers to boost oversight, organizations can streamline financial planning and budgeting processes, like invoice verification, payment settlements, and trade finance.  

The potential challenges and benefits of AI-driven solutions   

Although the AI tools discussed above demonstrate the immense potential this technology holds for supply chain forecasting, planning, and financing, there are challenges that organizations must navigate in the process:  

1. Data quality and availability pose an issue as teams face limited access to high-quality information.   
2. Integrating AI tools with existing systems and infrastructure can cause hurdles if systems are non-compatible. 
3. Research consistently shows that AI systems can exhibit human and systemic biases stemming from their program and data sources. Businesses need proactive measures to ensure equitable AI adoption. 
4. High implementation costs are a common financial barrier for supply chain organizations, requiring upfront investments in more advanced technology infrastructure.   

On the other hand, when supply chain organizations overcome barriers to AI adoption and integrate this technology successfully, they can see several resulting benefits. With AI-augmented processes for forecasting, planning, and budgeting, teams can:    

• Leverage real-time decision-making: AI-driven analytics provide real-time insights and actionable data that enable supply chain executives to make informed decisions faster.   
• Enhance forecast accuracy: By quickly analyzing vast amounts of data, organizations can ensure more accurate forecasting and planning.    
• Boost risk mitigation and resilience: AI technology can identify potential risks, like supplier disruptions or transportation delays, before disaster strikes — minimizing impact and ensuring business continuity.   
• Harmonize inventory levels: With more information about demand patterns, seasonality, lead times, and market trends, businesses enjoy more efficient inventory management.  
• Optimize resource allocation: Resources are precious, and AI algorithms help ensure asset allocation, such as labor or equipment, is aligned with demand patterns and operational capacity.   

Unleashing the power of AI tools with Oracle Cloud solutions  

With the ability to provide more accurate predictions, uncover hidden insights, and ensure real-time adjustments, AI technologies promise to disrupt budgeting and forecasting in the coming years. Oracle Cloud EPM can help organizations navigate planning and financing with Intelligent Performance Management (IPM) capabilities.  

That daunting process that once took weeks to complete? Now users can finish in days, or maybe even hours, with the help of Oracle Cloud EPM. Take advantage of predictive insights and automated data analysis — not to mention features like forecast variance and bias, prediction, and anomaly insight.   

Inspirage helps customers select Oracle solutions to support their digital transformation journeys. With deep domain experience and a global workforce, Inspirage helps organizations implement Oracle Cloud enterprise performance management (EPM) and enterprise resource planning (ERP) solutions to optimize long-term operations. Ready to strengthen your forecasting and financing? Contact us to learn more. 

The Metaverse — the increasingly popular immersive virtual realm where people can connect, interact, and explore — is now an emerging reality driven by the accelerated growth of digital technologies and market demand for them. By one estimate, over 400 million unique users worldwide visit this data-driven “landscape” every month. However, with the powerful technological breakthroughs that support valuable digital experiences comes the added responsibility to ensure that people can engage in the Metaverse safely, securely, and sustainably.

What is a “Sustainable” Metaverse?

Because the Metaverse centers around the digital landscape, it holds the potential to create a more equitable and sustainable world. But, to do this, the Metaverse must integrate sustainability into every facet of design and development. With a comprehensive framework, organizations can help foster a virtual realm that balances social, environmental, and economic factors. A completely sustainable Metaverse ensures teams prioritize long-term viability, inclusivity, and responsible practices to minimize possible negative impacts.

According to a survey by Wunderman Thompson Data, 71% of people who are conscious of the Metaverse said brands need to consider its environmental consequences. How are companies creating more sustainable digital landscapes? Some of the top strategies include highlighting:

• Energy efficiency: To cultivate energy efficiency within the Metaverse, organizations are optimizing server farms, data centers, and virtual environments — helping minimize both power consumption and carbon emissions.
• A scalable and adaptive infrastructure: Sustainable virtual realms require a foundation that can scale and adapt to changing needs as they come. Creating this foundation involves implementing flexible, cloud-based systems that more efficiently allocate resources and adequately accommodate growing user bases.
• Blockchain technology: Blockchain technology, which plays a progressively significant role in establishing a sustainable digital environment, provides decentralized and transparent systems that enhance security, trust, and accountability. Leveraging blockchain to create fair and inclusive virtual economies ensures data privacy.
• Renewable energy integration: Teams may consider embracing renewable energy sources, such as wind or solar power, to meet the energy demands of the Metaverse more sustainably. Clean energy remains the best alternative to help businesses reduce their reliance on fossil fuels and mitigate long-term environmental ramifications.
• User education and awareness: Developing a truly sustainable Metaverse will rely on more than just executives and supply chain leaders, but every individual across the organizational ladder. To ensure proper user education, companies can introduce initiatives that offer information on sustainable behaviors, promote responsible virtual practices, and encourage individuals to make the right choices within the digital realm.

Standards and Industry Codes of Conduct 

As organizations take steps to construct a more sustainable Metaverse, it will be essential to consider the roles of regulation, governance, and administrative responsibility to mitigate potential threats in these virtual environments. Some of the top control-related issues for regulators to assess in the Metaverse include:

1. Supporting personal data protection and preventing unauthorized access with data privacy and security measures,
2. Addressing misinformation and hate speech that can spread quickly within digital landscapes with content moderation policies,
3. Balancing the potential impacts on mental health through relevant laws,
4. Preventing fraud, money laundering, and illicit activities with systems for virtual currencies and transactions, and
5. Ensuring equal access and accommodation for individuals with disabilities and promoting inclusivity and non-discrimination by implementing accessibility standards.

Continuously monitoring prospective regulations will be critical, considering experts are already calling on players in the industry to create a “metacode of conduct.” This code would theoretically protect users from abuse, fraud, and loss until official legislation catches up.

Looking at the Metaverse through a Sustainable Lens

Not only are people increasingly aware of — and actively engaging in — the growing Metaverse, but statistics show that 38% of U.S. adults think this virtual world will improve life. These potential benefits include:

• Reduced environmental impact: Bringing sustainability to the forefront of organizational decisions minimizes the footprint caused by the Metaverse. Valuable opportunities to foster an energy-efficient infrastructure, use renewable energy sources, and optimize resource consumption will prove to be linchpins in mitigating climate change as virtual worlds expand.
• Enhanced diversity, equity, and inclusion (DEI): Digital landscapes provide a pathway to advanced DEI efforts. By ensuring accessibility, equal opportunities, and fair economic participation, equality and representation will be at the core of this online environment.
• Increased resilience: Fostering a Metaverse with sustainability in mind can boost financial and operational flexibility. This preparedness, along with data protection and scalability, helps teams reduce disruptions and promote long-term stability.
• Improved collaboration and knowledge sharing: A sustainable Metaverse facilitates enhanced global collaboration, cross-disciplinary cooperation, and an exchange of ideas that empowers innovation and collective problem-solving.
• Greater transparency and trust: Despite the growing recognition of the Metaverse, many individuals remain wary of this digital space. Fortunately, emphasizing sustainability promotes visibility and accountability. In addition, implementing ethical practices, data privacy, and decentralized systems helps companies build trust.

Drive Sustainability in the Metaverse with a Digitally Integrated Enterprise

Prioritizing sustainability across social, environmental, and economic factors can shape a virtual world that captivates and engages users and contributes positively to our collective future. With this in mind, business leaders are turning to cutting-edge solutions that help optimize operations, reduce waste, and minimize their environmental footprint within the Metaverse.

Inspirage can make life easier for IT and business personnel by empowering these professionals to embrace artificial intelligence, data analytics, and supply chain management. Our digital transformation expertise allows enterprises to operate effectively in immersive, interconnected digital environments that transcend physical limitations and promote sustainable practices.

Inspirage works with organizations to become agents of sustainable change, driving faster decision-making through strategic planning, process enablement, and actionable intelligence. Our team manages Oracle Cloud deployments and successfully aligns technological tools with sustainability responsibilities. If you are ready to digitally enable an integrated enterprise that supports the long-term viability and beneficial impact of the Metaverse, contact us today to learn more.

While potentially disruptive digital technologies such as cloud computing, virtual reality, machine learning, and artificial intelligence (AI) have been around for a number of years, today they are finally capable of addressing real-world concerns for both consumers and business owners alike. It is little wonder why organizations worldwide are expected to spend more than $4.6 trillion on new digital technology in 2023, according to a report from Nash Squared. That is up from $4.2 trillion in 2021. Whether utilizing machine learning to improve operational efficiency in supply chains or data analytics to better understand what buyers value during the customer experience, leveraging the latest technology now makes previously unimaginable innovation and digital transformation possible. These technologies are particularly important in the high-tech industry where embracing digital technologies is paramount. Which high-tech trends will stand out and how will businesses be investing in the future throughout 2023? Here are a few possibilities:

High-Tech Trend No. 1: Workplace Automation

In the high-tech industry, organizations can gain speed and efficiency in 2023 and beyond by automating many of their routine and semi-routine processes. Workplace automation frees up time and energy for creativity and innovation by eliminating mundane business processes. While workplace automation can involve computers doing the work of a user, that is not the extent of their use. These automation tools can also be harnessed to create business value from contextual information. They help businesses respond with speed and urgency to changing markets and demands and also delegate tasks more effectively. This technology is crucial to the creation of more efficient and effective organizations.

Another example of the way high-tech organizations are automating the workplace is through ambient computing. Otherwise known as ubiquitous computing, ambient computing is a somewhat complex concept to grasp — quite literally. That is because the technology itself is invisible. Instead, it is embedded in the users’ surroundings. Imagine, for example, a thermostat that raises and lowers the temperature within a room by “remembering” or “learning” the habits of the homeowner. Or ponder the possibility of a smartphone that tells a driver how long it takes to get to a frequently visited destination just as he or she enters the vehicle. Ambient computing is what makes these capabilities possible; it is baked into daily life.

Jason Low, principal analyst for the research firm Canalys, told ZDNET that ambient computing is very similar conceptually to internet of things (IoT) technology, which relies on machine learning to perform predictive capabilities. But there is a key difference between the two. “IoT forms a base for ambient computing, with ambient computing more focused on how devices and intelligent services interact with users,” Low explained.

In essence, ambient computing is a more nuanced form of the Internet of Things that is centered on how IoT devices go about gathering data on users. Amazon, Google, Apple, and Microsoft are just a few of the major high-tech corporations that are either utilizing this latest technology trend in one of their consumer products (e.g., Alexa, Amazon’s Echo Device voice assistant) or seeking to expand its use through more IoT devices.

One way high-tech businesses are increasingly relying on ambient technology is by making it easier for staff to collaborate across different geographies. The pandemic was a game changer for the workplace. Due to state-mandated lockdowns, many organizations were forced to close their offices and conduct day-to-day business affairs entirely remotely. Given that work productivity often did not suffer — and in some cases actually improved — several workplaces now permit their employees to work 100% remotely. In fact, according to a recent Gallup poll, just 20% of “remote-capable” employees (those whose jobs can be done from home) work entirely on-site. Among those who have the ability to do their job from home and the workplace, 50% divide their time between the two.

But having staff in different environments can present communication challenges when work requires collaboration via video conferencing tools, such as having trouble hearing who is speaking. As ZDNET reported, more organizations are relying on ambient computing in their conference rooms to address these issues. When deployed, the technology can seamlessly amplify voices so those speaking can be more easily heard by colleagues who are working from home. Essentially, the technology allows individuals to sit anywhere they want and speak normally rather than need to sit near the computer or raise their voices. Ambient computing allows companies to work more efficiently and increases flexibility.

High-Tech Trend No. 2: Continuous Penetration Testing

Cybercrime has become so commonplace that it is only a matter of time before a business is impacted by an attack — if it has not already encountered one. Nearly all businesses, regardless of their size, are in hackers’ crosshairs. In fact, according to Check Point Research, there was a 28% increase in cyberattacks globally in the third quarter of 2022 compared with one year earlier. Ransomware, which involves hijacking or locking down an organization’s system or network until a ransom is paid, is one of the most common types of cyberattacks. The pervasiveness of these attacks — and their difficulty to deter — is why Cybersecurity Ventures anticipates victims will experience $265 billion in losses by 2031, with attacks occurring once every two seconds.

High-tech companies are often targeted by cybercriminals because of the vast array of information and data an attack can provide. Beyond traditional cybersecurity measures, such as investing in software and reminding workers to follow strict safety protocols, high-tech businesses are investing in continuous penetration testing to fight back. Unlike traditional penetration testing, which assesses the resilience of a network at a specific point in time, continuous penetration is ongoing. This is done by simulating regularly occurring attacks. According to Forbes, an increasing number of organizations are turning to continuous penetration testing as a way to blunt cyberattacks, in general, and ransomware attacks, in particular. Penetration testing can be a reliable strategy because it helps to identify vulnerabilities, improve cyber risk management, and automates security monitoring in real time rather than during one specific instance.

Leveraging automated security monitoring can also help lower high-tech businesses’ costs by eliminating the need to rely on internal staff or outside help. However, cybersecurity expertise is hard to come by. According to (ISC)², the cybersecurity industry is in the midst of a severe shortfall in experienced professionals who can meet the demand for services. It is a global problem, too, with job openings worldwide increasing by 350% between 2013 and 2021, according to Secureworks.

High-Tech Trend No. 3: Augmented Reality

Augmented reality involves superimposing the digital world onto the real world by leveraging high-tech devices. Sony, Microsoft, Nintendo, and other video game developers all offer augmented reality products to boost the customer experience for avid gamers. But augmented reality is not found exclusively among the gaming community; it is also used by schools to enhance learning, by retailers to personalize online shopping, and by businesses to train employees. The emerging technology is expected to become even more omnipresent in 2023. In fact, Research and Markets estimates that the augmented reality market’s valuation will top $61 billion worldwide in 2023 and continue to rise from there. The high-tech industry will be one of the main beneficiaries of this emerging technology.

In high-tech manufacturing, for example, augmented reality allows companies to overcome the challenges posed by their contract manufacturers’ high turnover rates. Turnover often results in less efficient processes, more human errors, and lower productivity. One way it accomplishes this is by enabling real-time training that allows workers to visualize – rather than simply hear about – vital work instructions and processes as they perform their jobs.

Augmented reality also has the potential to significantly improve quality assurance initiatives during every stage of high-tech product development. Guided AR solutions, such as the use of 3D imagery and machine learning to simulate the workings of mechanical components, now allow manufacturers to identify and rectify potentially costly design errors before products roll off the factory floor. In addition, augmented reality can improve the data management and analytics outcomes unique to manual processes. Through process simulation and workflow tracking, high-tech manufacturers can gather and document important information about inefficient cycle times, designs, and operational metrics that might otherwise go unrecorded and unnoticed until a problem arises.

High-Tech Trend No. 4: Artificial Intelligence

As far back as 2018, 85% of Americans were using at least one product that had AI capabilities, according to a Gallup survey. Artificial intelligence, while still a relatively new technology, is in full bloom. Industry experts believe AI will continue to saturate the marketplace in 2023. One type of AI that is poised to become more prominent is no-code AI. As its name implies, no-code AI is a code-free technology that makes it easier for users to implement and test their ideas through drag-and-drop interfaces. The turn-key nature of drag and drop enables any business owner — regardless of their familiarity with AI — to take advantage of it without expert assistance.

An increasing number of high-tech companies are also using artificial intelligence as well as machine learning to strengthen their supply chains before disruptions occur. These technologies speed up time to remediation by automating product analysis. Edge computing, for example, puts the processing power of AI and ML closer to the devices they monitor. That embeds crucial insights deeper into every aspect of operations, making supply chains function more efficiently and cost-effective over the long term. AI also provides benefits after a successful product launch, such as the ability to leverage user data to enhance product-related software, customer service, and security. Many of the online campaigns and tools high-tech companies now use — think search engine strategies and chatbots — rely on AI to engage potential consumers searching for specific content online and then guide them to desired outcomes.

New technologies have long been the key agents of growth in a wide variety of industries — and will continue playing that role in the decades ahead. Yet it is safe to say that the speed and intensity of innovation, disruption, and competition in the high-tech industry are unrivaled by those in any other realm. By their very nature, research and development initiatives drive the success and profitability of high-tech enterprises, so the reliance on cutting-edge technology by manufacturers and R&D firms will only grow in the future.

Almost any high-tech organization will have opportunities to benefit from these technology trends in 2023 and beyond. At Inspirage, we offer transformational services that can help keep your business on track by bringing the right teams and technologies together to optimize agility and drive operational excellence. Contact us today to learn more or download our new high-tech eBook.

The freight industry is a vital part of the financial engine of the United States. With consumer spending representing more than two-thirds of the U.S. gross domestic product, the ability of trucks, trains, ships, and airplanes to transport goods to their intended destinations is ultimately what enables the economy functioning. The commercial trucking industry alone hauled nearly 11 billion tons of freight in 2021, according to the American Trucking Association (ATA). In doing so, it generated more than $875 billion in total revenue, making it the biggest mover of domestic freight.

Yet the freight industry — trucking, in particular — is dealing with several challenges. How it maneuvers its way through those challenges may have a sizable impact on whether the economic road ahead will be smooth or riddled with potholes. Here are some of the issues the freight industry is experiencing and what business owners are doing to address them.

Challenge No. 1: Ongoing labor shortage

In the wake of the pandemic and the shutdowns that ensued, many industries have struggled to find workers. For trucking companies, however, finding help has been a problem for a long time now. This is due primarily to deterring factors such as low pay, long hours, and the solitary lifestyle that it often entails for drivers. By late 2022, trucking companies needed an additional 78,000 drivers to keep up with the pace of demand, according to the most recent statistics available from the ATA. If the trend continues, the shortfall could top 160,000 by 2031.

With varying degrees of success, motor carriers have made a number of business decisions to attract and retain drivers, including boosting pay, making it easier to obtain commercial driver’s licenses, and improving work-life balance. Whether those efforts are enough to make up for the driver shortage remains to be seen.

Solution: Artificial intelligence

Some organizations are also leveraging artificial intelligence as a way to boost productivity. While fully autonomous trucks are still not commonplace on the nation’s roads, AI has allowed for the creation of advanced driver assistance technologies. They rely on a combination of sensors, cameras, software, radar, and other technologies that help drivers navigate more safely.

As the American Transportation Research Institute (ATRI) pointed out in a 2020 report, “the rapid pace of autonomous vehicle development has the potential to affect many aspects of trucking industry operations,” including by enhancing productivity and improving safety. There are also a number of automakers that are either building or planning to build both fully and semi-autonomous trucks. Semi-autonomous trucks are those that require human interaction to perform certain tasks related to the truck’s operation.

Aside from on-road automation, motor carriers are also using technology to manage their fleets and optimize their routes. For example, through GPS, employers can track the location and status of their drivers in real time. This enables them to determine how long it takes to get from Point A to Point B and apply that knowledge to craft more time-efficient routes and schedules. Additionally, AI is proving to be helpful in identifying available parking spaces, the shortage of which is slowing the speedy movement of freight. While lawmakers are introducing legislation designed to boost truck parking infrastructure, there are downloadable mobile apps that enable truckers to find open spots. According to the ATA, the average driver spends 56 minutes each work shift looking for open parking. This downtime translates to an average of $5,500 in lost wages per year.

Challenge No. 2: Truckload capacity constraints

Another issue that is intertwined with the driver shortage is truckload capacity. With demand for trucking services persistently high, and availability of truckers low, the current state of trucking forces motor carriers to make decisions that can affect their profitability and their relationships with customers and businesses. This dilemma is exacerbated when they lack enough trucks to move products, which is common for smaller carriers that need to be constantly aware of expenses.

ATA Chief Economist Bob Costello has frequently discussed this challenge in the trade association’s monthly tonnage reports, which detail the amount of freight the trucking industry hauls over time. Truckload capacity constraints have also contributed to the supply chain problems much of the world has faced since the pandemic.

“Demand for trucking freight services remains strong, but for-hire contract carriers are capacity constrained due to the driver and equipment markets,” Costello said, as reported by Truckinginfo.

In a 2022 Benchmarking Survey Report from the National Private Truck Council, limited capacity was cited as a leading pain point for the freight industry, along with driver-related issues, the cost of fuel, regulations, and a few other struggles.  Parts and equipment shortages are also contributing to the capacity crunch among truck manufacturers.

Solution: Truck-sharing

One of the ways organizations are working around this issue is through truck sharing. As the term suggests, truck sharing involves multiple businesses sharing one or more trucks for the transportation of goods, even though those items may be different in nature and have different destinations. A truck may be owned by a truck-sharing company, for example, or by another motor carrier that rents out unused space to other companies. This approach can be arranged through a truck-sharing platform or application that enables carriers to coordinate with one another. In addition to making more efficient use of resources, truck sharing can also help reduce costs and greenhouse gas emissions.

Oren Zaslansky, founder and CEO of the logistics company FlockFreight, told Supply Chain Brain that shared truck loading makes good business sense because it allows for more efficient use of existing resources. “Many goods can be put together in a very agnostic way that creates value for everyone,” Zaslansky explained.

Truck sharing also helps to reduce the freight industry’s carbon footprint by reducing the number of fuel-burning trucks on the roads. In the average year, one commercial truck emits 223 tons of carbon dioxide, according to FreightWaves. That is roughly the amount of carbon that 14 people produce in a year.

Challenge No. 3: SEC’s climate disclosure rules

Originally issued by the Securities and Exchange Commission in 2010, climate disclosure rules are a set of regulations that require publicly traded companies to reveal any information pertaining to their production processes that can potentially harm the environment by contributing to climate change. Some of these rules were updated in 2020, and they require organizations to increase their reporting on how they may be exacerbating the effects of global warming. For trucking outfits, much of that information pertains to their fuel emissions. The SEC created these rules for transparency purposes so investors can make more informed decisions and put their money toward organizations that share their values and priorities.

Even though the rules are not legally binding, the SEC can still impose penalties for companies that fail to comply.

Solution: Zero-emission trucks

Cognizant of their impact and eager to be part of the solution, some fleets are investing in zero-emission trucks or ZETs. Zero-emission trucks look like any other commercial vehicle but without exhaust. ZETs, which are powered by electricity from batteries or fuel cells, produce minimal pollutants.

Since the federal government has ramped up its spending on electric charging station infrastructure, supporters of ZETs within the trucking industry contend that it makes sense for companies to put their money toward this type of equipment. In addition to helping decrease their carbon footprint, it also incentivizes investors to put their money behind organizations that are climate-focused. Many consumers like to buy from companies that uphold sustainable business practices. As a 2020 poll from the National Retail Federation revealed, over 70% of consumers say they are willing to spend more on items or services from companies that are transparent about their production methods.

Other ways that trucking companies can be more climate-focused without reducing productivity include reducing their empty miles by adopting a full truckload strategy (FTL) and prioritizing tire maintenance, writes Emily Newton, an industrial journalist for Global Trade. Ensuring that tires are properly inflated increases fuel efficiency by reducing a tire’s resistance. “Even simple changes to business processes that help maximize the number of FTLs can have a major impact on emissions,” Newton wrote. “Employing these tactics paves the way for a more sustainable trucking industry.”

The challenges the freight industry faces are solvable through a combination of technology and improved processes. Inspirage has expertise in both areas. We bring the right teams and technologies together to optimize agility and drive operational excellence for all product-based industries. Contact us today to learn more.

Relative to other countries, the United States has a remarkably diverse manufacturing sector, perhaps the most eclectic of the nation’s largest industries. You name it, some manufacturing company in the U.S. makes it — from hydraulics and hardware to plastics and silverware. Because of this, companies within the manufacturing industry — and their supply chain — cannot be painted with a broad brush. Despite the apparently rampant disruption of supply chains, a recent poll led by Oracle and IndustryWeek found nearly half of manufacturers were not negatively impacted by the pandemic. In fact, many are now in a better position today than they were before COVID. That said, supply chain disruptions remain the rule rather than the exception, with nearly 80% of leaders saying it was a top business challenge for them in 2022, according to polling conducted by the National Association of Manufacturers.

A decade from now, each manufacturer will look back upon 2023 differently given their diverse makeup, but here are a few manufacturing trends that are expected to emerge or persist in manufacturing in the months ahead. As you will see, many of them involve some aspect of the supply chain.

Heavy recruitment push to continue

Although the national unemployment rate at the end of 2022 was below 4%, companies in many industries have been struggling to find individuals who can fill open roles. Manufacturing is one of those industries. As of September 2022, there were at least 835,000 job openings among manufacturing organizations large and small, based on jobs data from the Bureau of Labor Statistics. If the high turnover rate in manufacturing employment continues at its present pace, the shortage could hit 2.1 million by 2030, according to the National Association of Manufacturers.

As with numerous other sectors, thousands of manufacturing jobs were lost in 2020 during the pandemic. Those jobs were quickly replaced, however, thanks in part to the economy bouncing back and by robust consumer spending when lockdowns were lifted. Chad Moutray, the chief economist for the National Association for Manufacturers, told Manufacturing Dive that employers are raising manufacturing employee wages to encourage more applicants, but this effort has not been enough to close the gap.

To increase productivity and make up for lost workers, manufacturers are increasingly investing in automation, AI, and other smart manufacturing capabilities. But the future of the industry remains with the traditional flesh-and-blood laborer. Because of this, manufacturing companies need to invest in their people and ensure workers receive the proper training so they have the skill sets needed to succeed in this line of employment.

“Manufacturers must continue to lead the way in skills development if we are going to close the skills gap and make the industry more competitive,” said Moutray, who also serves as the director for the Center for Manufacturing Research.

Some of the employee skills that manufacturing companies will need to be competitive include being adept with data gathering and analysis. While these are hard skills, employers are also seeking soft skills as well, such as critical thinking, problem-solving, collaboration, and communication.

Growth in additive manufacturing

Manufacturing may be one of the oldest industries in the world, but the rapid pace of technological innovation is creating new subsectors within the field, one of which is additive manufacturing. Additive manufacturing uses 3D printing technology to create a variety of applications, products, and even food for personal, commercial, or industrial use. Just about every industry has benefited from the revolutionary capabilities the 3D printer has to offer, including healthcare, transportation, restaurants, and fashion.

The processes that make three-dimensional creations possible depend on the item that is produced and may include binder jetting, material extrusion, sheet lamination, and vat photopolymerization. With 3D printing technologies becoming increasingly sophisticated, the federal government is seeking to leverage additive manufacturing for national security and military needs. Kevin DeVries, deputy director of the DoD’s Manufacturing Technology Program, noted in a statement that if the U.S. is to achieve its goal of test-firing a hypersonic missile in 2023, 3D printing will play a key role. “We need to be pushing the envelope with materials produced using the additive manufacturing processes,” DeVries said. “The science has proven it is possible, but the practice is not widespread enough.”

Relative to other subsectors of manufacturing, additive manufacturing is still in its infancy. But it is poised to grow substantially in the years ahead, potentially reaching a valuation of approximately $34.8 billion by 2028, according to Facts & Factors. That is up from $11.3 billion in 2021. The fascinating nature of the novel technology may inspire more individuals to pursue a career path in the industry in the years ahead.

Further expansion of smart factories

From phones to TVs to headphones, consumer technologies have clearly received the “smart” treatment, which in the tech world refers to innovations that allow devices to “think,” such as by employing artificial intelligence and machine learning. Workplaces, like factories, that utilize these same capabilities have gained traction as “Industry 4.0” becomes more entrenched in global economies and work processes.

Like some of the other manufacturing trends mentioned here, smart factories are not new. In 2017, for example, well-known manufacturers like General Electric, BMW, and BASF had at least one smart factory system or initiative in place or were planning one. They made these early investments because smart factories have the potential to reduce operational expenses, improve manufacturing quality, and increase overall output.

Fast forward to today, and newly launched manufacturers are using smart factory capabilities right out of the gate. Smart factory operations and techniques are expected to become more of the norm moving forward. The industrial internet of things market globally in 2021 was worth $263 billion in 2021, according to Grand View Research. Its valuation is expected to rise at a compound annual growth rate of 23% through 2030.

AI for decision-making purposes

Artificial intelligence has become widespread among manufacturers, especially in Europe. Last year, according to Google, an estimated 79% of manufacturers in Germany and 80% of those in Italy reported using AI in their regular and ongoing operations. Perhaps surprisingly, the U.S. (63%) trails both of these countries, as well as France (71%) and the United Kingdom (66%). Including all the nations that Google polled, more than three-quarters of manufacturers have incorporated AI into their day-to-day operations.

Today, manufacturers are utilizing AI for a variety of supply chain activities, including quality control inspection, production checks, inventory management, and more. The more efficient use of resources, time savings, and potential for lower costs are making them believers. If more leading industries, in addition to manufacturing, incorporate AI into their business processes, it has the potential to boost global GDP by $13 trillion by the year 2030, according to Harvard Business Review.

Flexible manufacturing

A case can be made for high-speed internet being the most groundbreaking invention in world history. Thanks to its availability, millions of organizations were able to pivot to all-remote work arrangements, a capability that likely staved off a more long-lasting recession, if not depression. While manufacturing is predominantly a profession in which work occurs in a central location — given the machinery that’s involved — flexible manufacturing has unmoored the industry from physical spaces.

Flexible manufacturing involves leveraging work machines, material handling, or central processing computers — or a combination of all three — so organizations can maintain production, but in a broader variety of work environments. These systems can also respond to certain discrepancies that may compromise output, which provides employers greater reliability.

Given the success some manufacturers experienced during the pandemic, many organizations have maintained their remote work arrangements. According to polling conducted by Fictiv, more than 80% of manufacturing executives who allow their employees to work remotely have had a beneficial experience. It positively affected their points of view regarding flexible manufacturing and justified their investments in systems that allow for added versatility.

The trends of today and tomorrow are meant to help manufacturers build a more resilient and sustainable supply chain. Since our founding, Inspirage specializes in implementing the right systems and solutions so businesses achieve a higher standard of excellence. Contact us today and please browse some of our Customer Testimonials and Spotlights, which are real-life examples of how we deliver solutions to our clients’ operational challenges.

Digital transformation is not the wave of the future or the next big thing; it’s the here and now. From manufacturing entities leveraging the “Internet of Things” (IoT) or “Artificial Intelligence” (AI) in their production lines to banking institutions setting up digital platforms to send and receive money electronically, digital adoption in many industries is already in place or well underway.

Digital transformation has become an existential necessity for the contemporary economic ecosystem. Large, midsize, and small businesses aren’t transforming digitally only to keep up with their competitors, either. They’re doing it because it enables them to work smarter and more effectively and take advantage of opportunities that would have been impossible a few decades ago. Digital transformation:

• Improves efficiencies in assembly lines through process automation
• Empowers small businesses and cottage industries to access the global market through modern e-commerce platforms performing customer sentiment analysis using social media data mining
• Hones in on investment strategies via machine learning
• Optimizes supply chain management via scientific analysis of available data
• Helps businesses achieve their goals and obtain results in highly challenging, highly dynamic environments

Few periods in recent years were so universally challenging as 2020 when the effects of COVID-19 threw a wrench into just about every conceivable norm. As a recent poll commissioned in part by the Institute for Supply Management found, approximately three-quarters of business owner respondents said that their supply chains were adversely impacted by the pandemic, due primarily to labor shortages and state-mandated lockdowns. Additionally, 45% said they experienced higher costs that year and more than half (51%) had a hard time shifting to partial and fully remote work environments.

Yet the survey showed that organizations that had digital solutions in place before the pandemic endured the coronavirus crisis better than those that did not. This was particularly true of digital technologies designed to support processes and outcomes like team collaboration, procurement, and remote work. In other words, companies that invested in digital solutions for inventory management, procurement, and other functions were more resilient.

“Companies that invested in a digital transformation program have found it easier to cope, to flex, and to change what they’re doing to meet new demands,” said Paul Blake, a product marketing specialist who led the research.

Here are a few of today’s top digital transformation trends, which could transform your business and its processes.

Business process automation

Of all the digital technologies and capabilities, business process automation may be the most ubiquitous. Business process automation is largely defined as the leveraging of software, hardware, and/or other equipment so routine tasks are performed more quickly and accurately. From data entry to employee onboarding to customer invoicing, business process automation reduces the hassles associated with tedious work so key employees can focus on core work. When deployed smartly, business process automation can help to improve the customer experience since more people are devoted to that goal. In short, business process automation enables organizations to use their resources more wisely.

Examples of this kind of digital technology are innumerable. From claims processing to batch processing, event log monitoring to automated order entry, business process automation reduces the legwork that’s associated with these kinds of repeatable tasks since they’re all handled by computer-based systems. Organizations leverage business process automation regularly. As a recent survey from Gartner showed, more than 75% of businesses today routinely use a combination of artificial intelligence, integration, and automation application in their day-to-day work processes. In addition to minimizing errors through predefined processes, business process automation also saves staff members’ time — a fact that is not lost on employees. Indeed, as Forbes reported, more than 50% of workers say they suspect they’d be able to cut their workload down by an average of two hours per day if some of their tasks were done by automation.

Critics of automation claim that the increased use of this type of digital technology will lead to job losses. But as a report from the Organization for Economic Cooperation and Development has found, automation has not produced the kind of job losses that some projected. In fact, in virtually all professions between 2012 and 2019, employment has increased globally, even in industries considered to be highly vulnerable to job loss stemming from automation. The OECD report noted that even when other contributing factors were taken into account across countries and economies (e.g. wealth, taxes, product market regulations, etc.), the implementation of automation did not lead to reduced employment growth.

Cloud-based solutions

In many ways, the cloud has revolutionized not just the internet, but how and where businesses operate. Traditionally, when companies have needed to compile or create data, they’ve stored it all in large servers and similar on-premises infrastructure. But aside from the room that these stations take up, they’re highly complex to create, maintain, and update to keep them operating efficiently.

The cloud has changed all that. All the information that used to be stored or accessed on site is available through centrally located servers that are accessible via an internet connection. By 2025, an estimated 85% of enterprises in the United States will have a cloud-first strategy in place, Business Insider reported. But other studies suggest cloud adoption among enterprises has already surpassed this figure.

Enterprises and small businesses are increasingly using the cloud as a result of the benefits it offers, including greater security, heightened visibility, scalability, unlimited storage capacity for data, cost efficiency, and workplace flexibility. Not only are more organizations using the cloud, but they’re also often using more than one. Indeed, on average, businesses use at least two public cloud (2.6) and two private cloud environments, according to a report by InfoWorld. Finally, as noted in the 2022 Gartner® Magic Quadrant for Oracle Cloud Application Services, Worldwide, “by year-end 2024, 75% of Oracle application services revenue will be cloud-related as enterprises accelerate their move to the cloud in response to the massive disruption of the COVID-19 pandemic.”

Data democratization

Another digital transformation trend that is taking the business world by storm — largely thanks to the cloud — is data democratization. Data democratization refers to the various processes that allow information to be accessible to pretty much anyone, regardless of their status within a company. Gone are the days when data was only relevant to IT professionals or business analysts assisting executives with major decisions. Data democratization enables non-specialists to not just dissect data, but to gather it as well, without requiring the assistance of someone whose background is in data analysis or data analytics.

Before these advancements, data democratization was difficult to achieve because of how data was often stored. Housed in its silos, data was typically unable to reach the appropriate people across the breadth of an organization.  Data inaccuracy was another dilemma adversely influencing the decisions made by companies. Data literacy has also held back data democratization. Data can only productively influence the decisions a company makes if it is interpreted accurately and if others examining the same data can draw the same conclusions.

Today, thanks to data federation software, virtualization, and cloud storage, data democratization is easier and more seamless than ever. For example, with data federation software, businesses can comprehensively go out and gather data so that it can be obtained from several different sources and environments, which was difficult and tedious to do previously. It can then be stored in a virtual database for later use or analysis. Data virtualization, meanwhile, uses software so anyone can retrieve and interpret data quickly regardless of how it was sourced or formatted. Cloud storage also offers protection from cyberattacks, thanks to encryption technology.

Whether you’re leveraging all of these digital technologies or seeking to begin your digital transformation journey, Inspirage can help you with the process. We deliver end-to-end digital transformation projects for product-based companies. For more information about our expertise and solutions, contact us today.

In the days of analog operations, processing information and using it to further your company objectives were typically limited to targeted — and often costly — initiatives that involved field experts, statisticians, and data analysts. Processing large swaths of data were beyond the capabilities of most contemporary technologies and were often cost-prohibitive for smaller organizations. Digital transformation was the technology that only the upper echelons of the industry could afford. Prioritizing data analytics and digital transformation was, for the most part, a recommendation, something that was highly encouraged but not always seen as necessary for the sustained growth of the organization.

With the advent of technological innovations over the last two decades, there has been a paradigm shift in how data is processed, analyzed, and leveraged at a reasonable cost for all organizations in the economic spectrum. Today, all businesses wanting to achieve their long-term goals around growth, social responsibility, and competitive advantage are investing in digital technology — including “Internet Of Things” (IoT), “Process Filtering,” “Artificial Intelligence” (AI), “Machine Learning” (ML), and “Data Mining” — that can achieve their objectives with a few simple and smart initiatives. Now, digital transformation is not just recommended, it’s expected — especially given the pace of technological innovation and its rate of adoption, which only accelerated when the COVID-19 crisis exposed large gaps in demand speculation and the supply chain. While the setback to the overall global economy wasn’t as harsh as some of the earlier studies suggested, the pandemic nevertheless revealed myriad vulnerabilities within current business intelligence operations.

Generally speaking, those organizations that digitized their work processes and leveraged digital technology before the pandemic were able to overcome the disruptions that resulted in their supply chains and other areas of production. In fact, “digitally mature organizations” are more likely to have increased their profit margins and annual revenue growth during the pandemic compared to businesses whose processes weren’t as digitally mature. These same companies said digital transformation was central to their financial success by helping to improve the customer experience.

It’s little surprise, then, that digital transformation continues to be an important investment for businesses. As Gartner reported, in the United States alone, information technology spending is on pace to reach $4.4 trillion by the conclusion of 2022. Much of that spending is in software, such as infrastructure as a service (IaaS). And last year, nearly three-quarters of organizations in a separate Gartner poll said they were actively engaged in digital transformation initiatives (24% leading, 48% heavily involved).

To what degree are businesses investing in digital transformation?

Digital transformation means different things to different organizations, depending on their needs, goals, specialties, and the products or services they provide. For example, among banks and credit unions, digital transformation may involve rolling out mobile apps that customers can use for remote banking capabilities. For other types of businesses, digital transformation may involve leveraging digital assistants, work-from-home solutions for staff, or chatbots on their websites to help with customer concerns or questions. During COVID-19, call centers experienced substantial growth in call volume because of the lockdown measures. As Forbes reported, organizations with technology in place that allowed employees to field calls from their homes had an easier time navigating the pandemic.

But regardless of how digital transformation manifests itself, organizations have stepped up their efforts to make it happen. According to the International Data Corporation, the combined amount of money that businesses worldwide are expected to spend on digital transformation activities is poised to reach $6.8 trillion by 2023, an increase of 15.5% from 2020. By next year, fully 75% of enterprises are expected to have a “digital transformation roadmap” in place, outlining the steps involved.

But much like a standing structure needs a foundation, every successful digital transformation journey requires a starting point. And for digital transformation to be successful, your business must first begin with data and analytics. This article will help you understand why data analytics is central to digital transformation. As you’ll see, just because organizations take steps toward digital transformation doesn’t mean they’ll always be successful in those efforts.
 

 

Data analytics explained

Data and analytics go hand in hand. In fact, the terms are used so frequently together, that it spawned the hybrid term “data analytics.” Data analytics refers to the ongoing measurement and gathering of statistics, facts, observations, and other pieces of information that can be used to make smart, well-thought-out business decisions. Grouped into four forms  — predictive, prescriptive, diagnostic, and descriptive — data analytics help to identify trends, answer questions, map out solutions, explain why events happened, and draw conclusions.

Bottom line: Data analytics not only helps you make decisions with respect to your business but make the right ones since they’re grounded in actionable intelligence.

1. Predictive
   As its description implies, predictive data analytics leverages quantitative techniques to forecast potential outcomes. From machine learning to data mining to statistical modeling, such methodologies can help to identify trends, cause and effect, and patterns in behavior in terms of end results.
2. Prescriptive
   Prescriptive analytics builds off of predictive analytics; they are often used in combination. While predictive helps to identify trends, prescriptive data analytics outlines the proper course of action in light of those forecasted outcomes. Whether it’s through artificial intelligence or big data, prescriptive analytics provide possible solutions by testing the prescribed actions.
3. Diagnostic
   Whereas prescriptive and predictive analytics are more forward-looking — answering the “what?” about something — diagnostic data analytics is more historical in nature, answering the “why?” about things turning out the way that they did. This part of data analytics is where the actual analysis takes place to explain relationships from a standpoint of cause and effect. Regression analysis, data discovery, and data mining are some examples of diagnostic data analytics techniques.
4. Descriptive
   Descriptive analytics is the data type that helps to draw conclusions. Whether it’s combing through historical data, comparing and contrasting numbers from one year to another (e.g., sales, prices, subscribers, etc.), or assessing other key performance indicators, descriptive analytics answer the most questions, including what, where, when, and how many. Descriptive analytics also assists with reporting, a core function for businesses regardless of their size or industry.

Data analytics is the key to digital transformation success

Forbes has reported that just a few years ago, approximately 85% of companies that took the initial steps toward digital transformation were unsuccessful in their attempts. Michael Gale, an industry expert in integrated technology, told Forbes that part of the reason for the high failure rate has to do with the inability to help employees manage the shift in processes. In short, organizations often struggle with change management and preparing workers for some bumps along the road. “Basic awareness about those challenges is probably the key indicator of how well the process will be successful,” Gale told Forbes.

The main complicating factor, however, is not fully appreciating the indispensability of data in digital adoption. Data is essential to guiding informed business decisions. In 2019, fewer than half of corporate strategies that Gartner reviewed referenced data analytics as being fundamental to delivering enterprise value. Douglas Laney, an analyst at Gartner, said that for businesses to be successful in the increasingly digitized economy, data and analytics are must-haves. “A company’s ability to compete in the emerging digital economy will require faster-paced, forward-looking decisions,” Laney explained. Laney added that corporate heads must ensure that their staff members have at least a basic, high-level understanding of data, analytics, and data science. But this is a challenge for many companies. According to a poll from the Harvard Business Review, just 25% of surveyed workers were confident in their ability to understand and interpret data.

Establish a data-driven culture and improve data literacy

How does an organization improve data literacy? One way is by establishing a data-driven culture. This involves not only bottom-lining data so that the average layperson can understand but also helping workers see how data can help solve business problems at all levels of an organization, from the supply chain to inventory management to worker productivity.

Another way is by simply discussing data and analytics more often so it’s not a foreign, abstract concept. This may even include creating positions within the company that specialize in all things data and data management, such as a chief data officer (CDO). “Increasing data literacy inside the organization enables D&A leaders and CDOs to implement a data-driven culture which encourages the use of data in decision-making,” said Debra Logan, vice president of research at Gartner. Logan added that data analytics is “fundamental to digital business transformation and can deliver value if the CDO addresses both data and business priorities.”

Another way to both build data literacy and establish a more well-entrenched data-driven culture is by asking a series of “How many?” questions. For example, how many workers would be able to interpret traditional statistical operations, such as correlations? On the management side, how many team leads would be able to construct a business case that is numbers-based? How many managers would be able to elaborate on the output they’re getting from their systems? Would those same managers be able to explain the output of their machine learning algorithms, or would that only be something a data scientist could address? The answers to these questions can help determine the strategy needed to build a more data-literate organization.

Craft an effective digital transformation strategy with data analytics as the foundation

With the correct data analytics and actionable intelligence in place, organizations can craft a digital transformation strategy with a strong foundation. Just as digital transformation can mean different things to different people, the same can be said for transformation strategy. McKinsey & Company offers a few suggestions regarding what every transformation strategy ought to include. A prime component to success is crafting a transformation team:

• Clearly define the mission: It isn’t enough to roll out digital tools “just because” or to approach the transformation with an “everyone else is doing it” mentality. There needs to be a reason for it, one that is holistic in scope, measurable, and understood by all.
• Ensure there’s collaboration: Digital transformation can’t be in just one portion of the company. It needs to be implemented with an all-hands-on-deck style approach, involving all channels and departments. When building a digital transformation team, the membership should be similarly diversified.
• Delegate authority: While it’s important for digital transformation teams to work together, there is also something to be said for allowing members to “own” their responsibilities. Corporate leaders need to define the goal and/or mission, then get out of the way and let the team members do their thing.
• Be judicious: While a good balance of team membership is important, the composition of the team requires serious thought. For example, you shouldn’t just appoint individuals to the team because the workers you wanted weren’t available.
• Build a central team: Ideally, digital transformation teams should be complemented by a centralized team that is there to support those who are leading the effort. They can assist with coordination, allocating resources, maintaining best practices, and reviewing progress.

From developing a strategy to proofs of concept to implementation, Inspirage can help you during every stage of your digital transformation journey. Contact us today to learn more.

When it comes to global transport logistics and supply chain management, there is no such thing as “good enough.” Items, products, equipment, and other deliverables can always get to their intended destinations a bit faster than they do currently. Freight can always be processed and handled more efficiently to expedite shipment from the United States to Australia and everywhere in between. The steady advancements of technology have helped make the once impractical easily achievable. 

But the world is a very big place, and the overall supply chain is extraordinarily complex. Indeed, recent global events — namely, the COVID-19 pandemic and the measures governments have taken to neutralize the virus— have led to supply chain slowdowns and severe production disruptions. Global trade volume has diminished significantly over the past couple of years, and as economists for the trade credit insurer Euler Hermes point out and CNBC reported, production shortfalls and logistics bottlenecks are the main reasons why.  

To more effectively navigate these obstacles, global transport logistics and supply chain management teams will have to optimize their operations and leverage the very latest technological solutions. Here are a few of the technologies poised to improve global transport logistics and supply chain management capabilities in 2022 and beyond.   
 

 

Tech Trend No. 1: Artificial Intelligence

What once seemed futuristic is today highly commonplace. From navigation apps to intelligent home personal assistants and smart home devices, artificial intelligence is very much a part of everyday life. In fact, 85% of Americans regularly use solutions that contain artificial intelligence technology, according to a Gallup poll.  

Just as AI has helped make consumers’ lives easier and more convenient, the same goes for global transport logistics and supply chain management. From intelligent courier robots that assist with transport to the internet of things applications that help to mobilize freight, AI is improving process efficiencies. Robotics have proliferated over the last decade and they’re expected to surge even more in the years ahead, particularly among supply chain and logistics management teams. Valued at $1.7 billion in 2018, global artificial intelligence in the logistics and supply chain market is poised to hit $12 billion by 2027, according to All The Research. 

In terms of which AI solutions are gaining the most traction, McKinsey & Company points to the following: 

• Real-time inventory management. 
• Dynamic margin optimization of end-to-end chains with digital twins. 
• Demand planning. 

Not only has AI-assisted in the improvement of workflow processes, but it has also lowered costs. Where successfully implemented, it has improved logistics expenses among early adopters of the technology by 15% versus those who have yet to adopt AI or did so very recently, McKinsey & Company reported.  

Tech Trend No. 2: Automation

The terms “artificial intelligence” and “automation” are frequently used interchangeably. But in reality, they’re actually different types of technology. Whereas artificial intelligence is designed to perform a multitude of tasks and adapt through the power of machine learning, automation is much more specific, designed to carry out specific jobs that are pre-set. Another distinction between the two relates to the kinds of jobs they are meant to facilitate. Artificial intelligence\is for non-repetitive tasks; automation is for those that are more mechanical.  

Because global transport logistics and supply chain management involve both, automation and artificial intelligence are leveraged at roughly the same rate. Whether it’s back-end automation or the kind that is used on the warehouse floor, such as robot installation, automation is increasing in prevalence. For example, in the automotive sector back in 2000, there were roughly 25,000 robotic systems in factory warehouses globally. That number jumped to 103,000 by 2016, according to Oxford Economics.   

As much as automation has already been used for supply chain and logistics management purposes, its rollout is poised to continue. For example, according to data compiled by Statista, approximately 60% of supply chain management firms anticipate robotic process automation will have an impact on supply chains by 2025, whether significantly or moderately. Robotic process automation is a solution that automates menial tasks such as certain rule-based IT processes, system updates, and data collection. As polling done by Forrester Consulting found, nearly half of respondents (48%) indicated their employers were increasing their investments in robotic process automation in the next year. 

Another automation technology logistics solution teams are getting behind is warehouse automation. Like numerous other industries, warehousing experienced massive disruptions during the height of the pandemic, especially in North America. As the Ontario Chamber of Commerce reported in its annual Ontario Economic Report, nearly three-quarters of firms (73%) in the province that specialize in warehousing and transportation are still dealing with labor shortages. Warehousing organizations in the United States are encountering similar challenges.  

Warehousing automation is helping to fill those shortages. The warehouse automation market was worth $15 billion in 2019, according to ResearchAndMarkets.com. But by 2030, its valuation could surpass $37 billion. Some of the technologies warehouse management teams are anticipated to utilize more in the coming years include autonomous mobile robotics, robotic item picking, and robotic case picking, according to Forbes.  

Tech Trend No. 3: Blockchain

A substantial portion of global transport logistics and supply chain management teams’ responsibilities revolve around documentation. Accuracy is essential to efficiency so when customers are expected to receive a specific number of orders, documentation helps ensure that the appropriate quantity is available in inventory.  

The blockchain makes this recording and storing process more seamless and secure. Used in a variety of industries and job functionalities beyond supply chain management, blockchain is basically a shared database that stores information in special blocks that are bonded with one another, hence the name. This binding process is accomplished through a process called cryptography.   

The genius behind blockchain technology, from a supply chain management perspective, is that it makes it easier and more secure to track, record, distribute, and verify data from anywhere across a business network. And, because it’s all decentralized, the blockchain increases visibility over production processes that may be outsourced to another company. 

Again, blockchain as a business solution is not unique to the supply chain and logistics universe. In fact, it’s typically associated with financial services and products like Bitcoin, the digital currency system that has gained renewed attention amid the pandemic. But it’s especially beneficial to global transport logistics because there are so many players involved. Entities that have no history with one another can verify that the information added to a digital ledger is accurate because it’s time-stamped. Thus, if something is updated, the logistics team at the other end of the digital ledger can identify when that data-add occurred. 

While more organizations are expected to use blockchain technology, Walmart, FedEx, and jewelry developer DeBeers were among the early adopters. 
 
Will the reality of driverless trucks make today’s transportation management systems obsolete? If not, will other emerging trends reshape logistics? Forbes recently turned to Bob Hart, Senior Vice President of Logistics Management at Inspirage, for answers. Read the article here.
 
Trend No. 4: Autonomous trucks

When it comes to freight transportation, particularly in North America, trucking is the top dog. According to the American Trucking Association, trucks hauled over 10.2 billion tons of freight in 2020, more than any other form of domestic transportation method. 

But like warehousing, trucking is struggling with labor. According to the American Trucking Associations, if hiring doesn’t improve notably, the shortage could top 160,000 drivers by 2030, up from the current shortfall of 80,000.  

But autonomous trucks — which don’t necessarily require a human at the wheel — could be a game-changer. While there hasn’t been widespread utilization of autonomous trucks, global transport logistics companies, as well as e-commerce giants, are investing heavily in these capabilities. This includes Amazon. As Bloomberg reported in 2021, the e-commerce corporation plans to buy 1,000 autonomous truck driving systems from a company that specializes in software for motor carriers.  

There is some question regarding how, or to what extent, the deployment of this technology could displace truckers, but government research suggests that it will also lead to the creation of jobs that rely on human input. Regardless, the autonomous vehicles market is projected to grow in value to more than $11 billion by 2028, up from $1.6 billion in 2021, according to Fortune Business Insights.  

When it comes to global transport logistics efficiency, there’s always room for improvement. If you’re looking to optimize your operations, Oracle Transportation Management Cloud is a one-stop solution. From transportation order management to shipment management to booking and tendering, as well as transportation intelligence, Oracle Transportation Management Cloud is a platform that supports the ongoing needs of shippers, receivers, logistics service providers, and many more. Inspirage can help you with the implementation that is customized to your service. Contact us today to learn more. 

Today’s finance teams understand the importance of future-proofing their systems. That’s why the best finance teams are leveraging artificial intelligence (AI)—specifically robotic process automation (RPA) and machine learning—to manage and automate their corporate financial processes. These types of AI can apply human-like intelligence to machine-performed tasks, such as decision-making and visual interpretation. RPA, for example, is a scripted, software-driven process for streamlining common repetitive tasks. This technology, considered the simplest form of AI, creates valuable process efficiencies for finance.

Oracle Cloud EPM has made significant investments embedding AI and RPA in its Cloud EPM platform under the Intelligent Performance Management (IPM) umbrella.

Oracle refers to RPA as Intelligent Process Automation (IPA), which reflects the fact that it is embedded into the processes, allowing finance teams to automate many of their processes. That, in turn, allows them to benefit from this emerging technology during their everyday finance activities. Cloud EPM offers IPA capabilities to arm finance professionals with the technology to automate manual corporate financial processes, support budgeting and forecasting, and provide accurate insights and reporting.

Adopting AI is an increasing priority for many companies. Finance teams that choose to utilize IPA and machine learning can leave manual processes behind, allowing them to increase workforce capacity, save time and money, and ensure the integrity of their data. Finance professionals are using these capabilities to:

• Close faster: Processes that previously required weeks to complete can now be completed in days, or in some cases, even hours.
• Reconcile balance sheets: Reconciling items is an integral part of the close process. IPA can perform most zero-balance reconciliations automatically, giving finance staff more time to reconcile key items that have a greater impact on the month-end financials.
• Detect anomalies in your trend analysis: Stopping financial fraud can be difficult due to the sheer volume of events and false alarms. Payment processors have turned to RPA to systematically analyze these activities, identifying and alerting system users of potentially fraudulent behavior.
• Connect enterprise plans: Oracle Cloud EPM provides an integrated planning platform to connect plans from Finance, Operations, Supply Chain, Human Resources, IT, Sales, and Marketing. All lines of business can utilize the shared data to create better insights, and the machine learning-driven forecasts help support better decision-making.
• Leverage AI and IPM for predictive insights: Finance teams harness the power of Oracle Cloud EPM to inform short- and long-term decision-making, such as whether to adopt a conservative or aggressive forecast strategy.
• Automate data analysis: Users can also leverage a machine learning model from any data science platform by importing the model into Cloud EPM and accessing its predictions and signals there. (Oracle calls this BYOML: “Bring your own machine learning”)

Charting a smarter course with intelligent insights

Capitalizing on the potential of finance-oriented AI requires the right enterprise performance management (EPM) solution. Oracle Cloud EPM comes with Intelligent Performance Management (IPM) Insights, a set of built-in capabilities that helps unlock new possibilities for finance teams. IPM Insights help you take performance management to the next level through more informed decision-making. Unlike a traditional machine learning platform, which is designed for developers, or a business intelligence tool that depends on existing data to generate insights, Oracle provides predictive insights with data that are optimized for multidimensional planning and forecasting. Oracle Cloud EPM leverages “what-if” analysis and scenario modeling that can improve forecasting accuracy, reduce risk, and slash the amount of time spent on manual data analysis through the power of automation.

Additionally, Oracle Cloud EPM improves the quality of insights, with features such as:

• Forecast variance and bias insight: Uncovers hidden biases in forecasts submitted by planners by measuring the variance between two historical scenarios.
• Prediction insight: Identifies significant deviation in forecasts by measuring the variance between future scenarios.
• Anomaly insight: Helps financial professionals and planners to detect unusual patterns that may deviate from expected results.

With Oracle Cloud EPM, finance organizations can automate the entirety of their business lifecycle, from budget, profit and costing, and long-range planning to line-of-business planning and management reporting. This results in a higher quality of analysis in less time. With this new freedom, teams can focus on tasks dependent on human input. In short, Oracle Cloud EPM complements your finance team’s abilities to perform their roles more efficiently.

Inspirage is an experienced Oracle partner that has successfully guided many EPM and ERP implementations, supply chain transformations, and numerous other ambitious projects for customers across a diverse range of industries. Contact our team to learn more about how we can help your finance organization harness the power of IPA and machine learning in the cloud.

It is not an exaggeration to say that the entire fate of a business hinges on the quality of its enterprise resource planning (ERP) implementation. An ERP system not only represents a major financial investment for companies, but it also touches every essential aspect of their operations from accounting to supply chain management.

Accordingly, the costs of not properly implementing an ERP solution are substantial, with some of the most notable failures bearing multimillion-dollar price tags, as chronicled by ERP News. Recent trends in ERP development — most notably, the move to cloud ERP and the integration of relatively new technologies such as artificial intelligence (AI) — have been driven by organizations looking to ensure that their ERP solutions are less risk-prone. In other words, they’re looking for ERPs that are more cost-effective, better capable of supporting informed decision-making, and easily scalable as company operations grow.

With those considerations in mind, let’s look at some of the top trends in ERP in 2021 and beyond.

1. The ongoing rise of cloud ERP

Cloud ERP has gained significant momentum in recent years for several reasons:

• Latest and greatest functionality: Modern cloud-based ERPs always deliver the most recent features from their respective vendors, with updates arriving frequently (e.g., on a quarterly basis).
• Manageable costs: With cloud ERP, companies can move from capital expenditures to operating expenditures. This shift provides more budgetary flexibility and lets them pay for what they actually use.
• Straightforward access: As more employees go remote, cloud ERP provides the flexible access that they need. Workers don’t need to be within the four walls of the organization and can instead access applications over the internet.
• Scalability: By hosting EPR in the cloud, companies can eliminate the burden of managing and upgrading hardware and software on-premises. This newfound simplicity supports more scalable operations.

According to MarketsandMarkets, the global cloud ERP market will more than double in size between 2020 and 2025, reaching $101.1 billion in value.
 

 

2. AI comes to ERP

Artificial intelligence (AI) is changing how organizations collect, analyze, and apply their business data, so it’s not surprising that it has found a comfortable place within ERP solutions. Major use cases for AI in ERP include:

• Deeper data insights: As the amount of unstructured data that organizations generate continues to increase, AI provides a way to systematically identify patterns and surface actionable insights.
• Process automation: AI can automate a lot of otherwise tedious and time consuming tasks, such as categorizing financial information from invoices and verifying reports. This frees up time for human teams to focus on other priorities.
• Optimized scheduling: In logistics and planning, AI can play a pivotal role in determining the optimal delivery and labor schedules. A 2019 IPFS survey of 600 executives found that 40% of them intended to use AI for inventory planning.

ERP vendors are also increasingly building such capabilities directly into their solutions, saving customers the trouble of having to implement AI modules on their own.

3. Multi-tier ERP

“One ERP to rule them all” has been the traditional approach to ERP deployments, as organizations have looked to use a single ERP to serve all of their locations. However, this hasn’t always worked out well, since the specialized requirements of different business units often exceed the capabilities of a one-size-fits-all ERP solution. Moreover, the costs of continually retrofitting a single ERP for the entire business can be substantial.

An alternative approach that has become more popular over time is the multi-tier or two-tier ERP. Under this setup, an organization uses one core ERP at the corporate level and another for its various divisions and subsidiaries. This approach may involve a combination of on-premises and cloud-based ERP solutions. Gartner has highlighted the benefits of multi-tier ERP, calling it a path toward easier modernization of small and fast-growing business units.

Making the multi-tier ERP work requires tight integrations between multiple systems. As an experienced Oracle partner, Inspirage has integrated ERP, supply chain and other solutions for organizations of all kinds. Connect with our expert team to learn more about how we can guide your next project.

Product lifecycle management (PLM) is at a pivotal juncture. As numerous relatively new digital technologies are gaining popularity, more companies are looking to harness the power of cloud computing, artificial intelligence (AI) and machine learning (ML) to enhance their PLM strategies.

Over the years, these PLM practices and supporting systems have evolved significantly, to the point that they are now integral parts of the business models of many organizations – not just manufacturers. Worth slightly more than $18 billion in 2018, the global PLM solution market is expected to top $26 billion by 2023, according to Quadrant Knowledge Solutions.

This expansion means that new trends and challenges in PLM have wide-reaching implications. Let’s look at some of the major ones to keep an eye on in the 2020s.

1. Digital twins and digital threads turbocharge the product lifecycle

Digital twins are virtual representations of physical systems and processes, displaying all of the attributes and workflows associated with them. Each digital twin provides an easily graspable model of something tangible, which can help in not only understanding how it works currently but how it might evolve over time as well.

Similar to digital twins, digital thread are virtual representations, but in this case of a communication flow related to a digital twin. Digital threads offer traceability of a digital twin back to its specifications. They link together different product, performance and supply chain data, to provide a straightforward yet comprehensive model of a real-world product’s lifecycle.

2. Investment in PLM cloud solutions continues to ramp up

Many companies have opted to move on from their on-premises PLM solutions in favor of cloud-based services. According to the 2021 CIMdata PLM Foresight Poll, all respondents had increased their cloud investments in the wake of the COVID-19 pandemic.

PLM cloud solutions offer distinct advantages over traditional PLM systems:

• Relatively low total cost of ownership.
• Flexibility, with numerous possible integrations.
• Regularly scheduled software updates.
• Superior resource scalability (scale up or down as needed).
• Simplified software licensing.
• Accelerated deployment and modification.
• Out-of-the-box functionality.

The move to cloud-based PLM has coincided with the shift to cloud software across other core business operations, including in enterprise resource planning and customer experience (ERP and CX, respectively).

3. Aging infrastructure highlights the need for fresh investment

A big part of PLM is recognizing when certain products and services are in decline and thus in need of replacement. The winter weather that caused major problems for the Texas state electricity grid is a case in point.

Although there were attempts to pin the widespread outages in Texas on the perceived unreliability of renewable energy sources like wind and solar, the reality was that aging fossil fuel infrastructure was at fault. Natural gas pipelines that had not been winterized froze in the unseasonably cold temperatures, choking off a vital source of fuel.

The ransomware attack on a major refined oil pipeline, Colonial Pipeline, illustrated another liability in critical infrastructure, namely, its vulnerability to cyberattacks. Modernization via expert PLM will be essential in thinking about the way forward.

In 2021, the mean age of a power transformer in the U.S. was 25 years, while transmission lines averaged 30 years, according to The American Prospect. Hundreds of billions of dollars in upgrades will be needed to ensure sustainable infrastructure in the years to come. PLM platforms will ensure detailed planning and proper execution for new additions to the grid.

Inspirage is an experienced Oracle partner with expertise across PLM, ERP, supply chain and more. As your organization thinks about the next steps on its PLM journey, our expert team is here to help. Contact us to learn more about how we can implement the right Oracle solutions for your business requirements.

From COVID-19 to the Suez Canal crisis of 2021, the supply chain management (SCM) sector has faced some high-profile disruptions in recent years. In reality, though, there are always challenges that SCM professionals need to navigate through. Limited system visibility, new sustainability goals and the integration of the internet of things (IoT) are just a few of the issues that supply chain organizations will continue to confront in the 2020s and beyond. Let’s examine some of the key trends in SCM right now and how companies are responding to them.
 

 

1. Falling costs and expanding use cases for IoT sensors

The rise of the IoT and its implications for SCM aren’t new developments, but falling costs for IoT sensors are. After years of hype, this IoT infrastructure has finally become sufficiently cost-effective to began supporting use cases such as:

• Digital twins: IoT sensors provide the critical data for creating and maintaining these digital representations of physical products and processes. For example, a digital twin can run simulations for a truck with specific configurations, without having to actually have that vehicle nearby.
• Real-time monitoring: Temperature-sensitive items such as vaccines require careful monitoring, which IoT sensors can handle. Because they’re so small, these sensors can easily be placed throughout supply chain checkpoints to provide detailed insights on current item temperatures and locations.
• Process automation: The Oracle Cloud SCM suite has been integral to IoT-driven automation in settings like factories. IoT sensors can automatically detect deviations from normal specifications and also connect to versatile application programming interfaces (APIs) or service oriented integration (SOA) to drive highly automated operations.

IoT infrastructure has also been floated as a complement to blockchain technology in helping root out counterfeit items. Blockchain can provide an immutable record of the actions taken on a product’s journey, as documented by IoT sensors along the way. Deviations from normal behavior may indicate counterfeits.

2. Expanding use of artificial intelligence and machine learning

Both artificial intelligence (AI) and machine learning (ML) can complement IoT infrastructure by enabling more extensive automation as well as smoother adaptation to evolving business requirements. AI refers to machines that can do human-like tasks such as make decisions, while ML is a type of AI involving programs that improve on their own.

Logistics Machine Learning within Oracle SCM Cloud is a prime example of how AI and ML have transformed supply chains. Using historical data, this solution enables accurate predictions of end-to-end transit times for direct shipments, which in turn allow logistics providers to deliver items more reliably and at lower cost.

Overall, AI and ML lead to more proactive supply chain operations. Paired with cloud integration and APIs/SOAs, these technologies give teams the visibility and awareness they need to make informed decisions about supply chain activities.

3. The drive to make supply chains more sustainable

According to McKinsey, 80% of the typical organization’s greenhouse gas emissions originate in its supply chain. On-road vehicles and warehouses, for example, are major sources of carbon pollution.

Some of the basic steps that companies are taking to make their supply chains more sustainable include:

• Pursuing a “circular economy” model, under which materials like pallets get regularly reused.
• Switching to renewable energy sources such as solar and wind power.
• Relying on energy-efficient LED lighting.
• Operating out of LEED-certified buildings.
• Using lift trucks powered by lithium-ion batteries or hydrogen fuel cells.

Beyond these measures, organizations have also looked to some of the aforementioned technological innovations, like IoT sensors and AI/ML, to identify areas for ecological improvement in their supply chains. Embedded sensors and digital twins, for instance, can provide clarity about how a process is currently functioning, including the amount of energy or other resources it’s consuming. With that data, decision makers can decide where to make more eco-friendly adjustments.
 

 
Many of our clients, like this pioneer in the online car retail industry, are reevaluating their supply chain operations. As your organization contemplates the future of its own SCM operations, Inspirage can provide the expert guidance and technical proficiency you need to ensure the right mix of Oracle solutions and integrations. Connect with our expert team to get started.

Predictability, Agility and Flexibility – Attributes You Must Bring into Your Supply Chain Management

Supply Chain disruptions have strongly impacted most industries over the last few years due to the pandemic, environmental or geopolitical issues. These disruptions have interfered with regular business streams as well as new product introductions, resulting in delays, additional costs, lower revenues, brand damage and overall customer dissatisfaction. Those enterprises that have decided to adopt new integrated business planning and execution (IBPX) processes that gave them the insight, agility and flexibility needed to best manage those Supply Chain disruptions; however, were able to adapt to market changes and become much more predictable in their execution.

In this webinar, experts from Oracle and Inspirage will discuss what IBPX is and how those early adopters have taken benefits from a full IBPX deployment. Using Oracle Cloud Solutions and Inspirage expertise, they have aligned Finance and Operations around the Supply Chain. More specifically, we will dive into selected Inspirage-led customer case studies and learn how Oracle IBPX solutions allow you to:

• Unite planning across development and production with a single product record
• Plan efficiently your New Product introduction for a better impact on the market
• Obtain real-time financial simulations to respond to supply chains disruptions
• Accelerate decision-making by analyzing alternative solutions or suppliers
• Visualize changes to business metrics in real-time

Register now

Meet the Speakers

Lionel Albert, EMEA SCM Business Solutions Director, Oracle

Based in Paris, Lionel carries 25+ years of experience in Supply Chain and Manufacturing and often participates in panels of international experts. At Oracle, he drives SCM strategic requirements for the European markets and works closely with Oracle product development. Additionally, he regularly engages in Supply Chain transformation projects as part of customer steering committees.

Denis Senpere, Vice President, Inspirage Europe

Denis joined Inspirage in 2016 to lead the European Business Development team. Prior to joining Inspirage, he had a long and successful career in PLM and SCM with Matra Datavision, Dassault Systèmes and Oracle as a senior executive across EMEA. He has more than 20 years of experience in SCM applied to discrete manufacturing, life sciences and consumer goods industries. As such he is often engaged as executive sponsor for Inspirage industrial projects. Denis also serves as a board member of several European technology companies. Most recently, Denis received Oracle awards for his contribution to Product Innovation and on Industry 4.0.

Sujit Jha, Practice Director, Inspirage 

Sujit is a Practice Director within Inspirage and has over 22 years of experience in Consulting & Delivery Management for Global fortune 100 & 500 customers, working with client executives (CFO, CIO, CTO & IT Heads) to define solution road maps & delivered the solution with modern best practices, superior functionalities & on-time delivery to offer higher ROI. He has implemented over 150 client projects/programs on Enterprise Performance Management (EPM), Business Analytics, ERP-Finance Analytics & ERPM Financial Master Data Management solutions and delivered over 1000+ client proposal responses.

The life sciences industry was in the public eye like never before in 2020. The rapid onset of the COVID-19 pandemic spurred a high-profile, worldwide quest to develop effective vaccines on a similarly quick timeline — and the effort succeeded, with multiple vaccines receiving regulatory approval before the end of 2020.

In 2021, pharmaceutical companies, as well as medical device firms, will continue to face challenges related to the coronavirus pandemic, in particular, and to the optimization of their supply chain operations, in general. Let’s look at some of the key trends across the industry for the coming year.

1. The increasing importance of cold chain visibility and traceability

The two earliest COVID-19 vaccines approved in the U.S. both have stringent requirements for cold storage. The Moderna and Pfizer vaccines must be kept at subzero Celsius temperatures during transport and have limited shelf life thereafter in refrigerators.

Accordingly, there is growing urgency around cold chain traceability, to ensure proper vaccine handling from manufacturing all the way through distribution. Such cold chain visibility was important before COVID-19 — for instance, to keep insulin at acceptable temperatures — so this trend represents an acceleration of something already in motion, rather than something entirely new.

Numerous technologies have emerged over time to enhance cold chain traceability in life sciences, including:

• Specialized barcodes and QR codes.
• RFID tags.
• Internet of Things sensors.
• GPS tracking.
• Near-Field Communication devices.
• Cloud-based software tools for managing the ensuing data.

These tools will become even more integrated into life sciences cold chains in 2021 and beyond. Annual sales of cold chain biopharma products could increase by $100 billion between 2020 and 2024 as demand ramps up and life sciences firms globalize their businesses.
 

 

2. Digital technologies come to the forefront of research and treatment

The life sciences sector has gradually moved toward cloud computing services as a way to streamline its IT costs and ensure proper infrastructure for more flexible and scalable operations. IBM has estimated that life sciences companies may be able to reduce their IT system costs by 25% through a cloud transition, although cost reduction is arguably the least important benefit of such a move.

More critically, cloud enables rapid data management and analysis, from a more streamlined, integrated and standardized technology stack than achievable with on-premise solutions alone. Digital technologies for AI, natural language processing (NLP), robotic process automation (RPA) aggregation and more are easier to implement and scale from the cloud, and these innovations will be important to the research and the monitoring of treatments in 2021.

For example, a pharma expert speaking to Drug Discovery & Development identified the use of AI and NLP as integral components of digital transformation in life sciences. These technologies can help:

• Gain insights during the discovery process.
• Speed up screening for clinical trials.
• Manage regulatory compliance at every stage.
• Integrate and analyze data from the patient end.

With the ongoing growth of telehealth and vaccination campaigns, digital technologies will only become more important to ensuring life sciences supply chains can be reliably scaled and modified amid these rapidly changing circumstances.

3. Accelerating development timelines and closer cross-industry collaboration

The COVID-19 vaccines followed exceptionally fast approval timelines. In 2021, life sciences organizations may look for opportunities to speed up the development of additional vaccines and other products.

The aforementioned digital technologies like AI and NLP may help, along with decentralized clinical trials facilitated by more collaborations between life sciences firms and contract research organizations. Treatments targeted at rare diseases, sometimes called “nichebusters,” may also become more common projects for drug makers.

Digital therapeutics, such as IoT wearables, could supplement medicines in more cases in 2021 and beyond, too. For example, armbands can gather patient vitals and analytics and assist in adherence to a treatment regimen.
 

 

Overcoming supply chain challenges in 2021

As the life sciences industry navigates these challenges and others in 2021, Inspirage can provide expert guidance and customized solutions across the supply chain. One such life science firm recently underwent the process of bringing internal processes and systems in line with GDSN standards. Organizational leaders wanted to implement a product data management solution that not only addressed current regulatory requirements from bodies like the NHS or FDA, but also positioned them to enter other markets and expand their capabilities as new regulations and customer requirements are released. Learn more about how Inspirage helped this organization, or contact a member of our team directly to get started on your next project.

The entire manufacturing sector has been materially affected by the COVID-19 pandemic, although the exact impact has varied significantly from one manufacturer to the next. For example, manufacturers of light vehicles and of raw materials such as steel saw steep drop-offs in production — as much as 99% in some instances — throughout 2020. Meanwhile, makers of paper products, specialty chemicals (like those in hand sanitizers) and consumer electronics all saw surging demand.

But even for manufacturers that weathered the storm and saw stable or increased revenues in 2020, there were formidable supply chain disruptions to navigate through along the way. In 2021 and beyond, industrial manufacturers will be looking to shore up their supply chain operations, with an eye toward employee health and safety, increased automation and the integration of digital technologies. Let’s examine some of the key trends to watch in the coming year.

1. Increased Investment in Digital Twins, AI and IoT

The use of digital twins in manufacturing is accelerating, due to a combination of the COVID-19 pandemic, the maturation of related technologies such as artificial intelligence (AI) and the expansion of the Internet of Things (IoT). Juniper Research has projected a 17% year-over-year increase in spending on digital twins technology in 2021, driven by manufacturers.

A digital twin is a representation of a physical object, with the ability to simulate any changes to that item based on the data stream from its connected sensors. In industrial manufacturing, one of the central digital twin use cases is predictive maintenance, as a digital twin can offer continuous, real-time insights into product wear and tear and make recommendations on any necessary fixes.

This approach, powered by numerous IoT devices and AI, can save manufacturers substantial sums. Instead of costly outages, repair and warranty liabilities, they can keep their operations consistently on track and more reliably respond to changes in customer demand.
 

 

2. Sharper Focus on Employee Health and Safety

Virtually all Fortune 1000 companies experienced supply chain disruptions as a result of COVID-19. Staff shortages among manufacturers, due to coronavirus infections, significantly contributed to these issues, underscoring the importance of prioritizing employee health and safety in 2021 and beyond.

Many of the essential tasks that these workers perform aren’t being automated, despite ongoing predictions that robots or other forms of automation could perform them. While investment in robots is rising — there were nearly 3 million of them in use in September 2020, a record, per the International Federation of Robotics — human workers are vital, and manufacturers will look to promote their well-being through a combination of COVID-specific and more general measures, including:

• Physical distancing.
• Protective gear and equipment.
• Real-time monitoring and communications.
• Regular trainings.
• Consistent inspections and reviews.

3. Localized and Near-Sourced Production

More manufacturers may begin or continue moving their production closer to consumption in 2021. This trend began even before COVID-19, in response to the rising costs of shipping from Asia, as well as concerns about geopolitical tensions and the environmental footprint of far-flung, carbon-intensive global supply chain operations.

But COVID-19 put into sharp relief the risks of complex, widely distributed supply chains, which can break down more easily than ones closer to the manufacturer’s home. In response, some organizations may look to reduce supply chain risk by relocating their operations.

Localized and near-sourced production may lower transportations costs, avoid regulatory complexity (e.g., changes in international trade agreements) and support certain types of branding, e.g. “Made in the U.S.A.” for some American firms.

4. The Ongoing Transition to Cloud

Cloud infrastructures and applications provide much more flexibility and scalability across supply chains than possible with legacy IT. For examples, one industrial manufacturer sought to harness the unique power of cloud-based supply planning, a project for which it enlisted the help of Inspirage.

Key processes such as sales order quoting and promising were moved from on-prem to cloud systems with all functionality intact, while many time-consuming manual processes were automated. The organization can now automatically pull in its sale orders based on selected criteria, greatly streamlining its ability to ensure consistent delivery to its customers.
 

 
Want to learn more? Make sure to download our Customer Spotlight and to connect directly with an Inspirage team member for your next project!

The COVID-19 pandemic has had an uneven impact on the high-tech industry. Compared to firms in other sectors such retail, the manufacturers of semiconductors, PCs, network equipment and related assets saw a much quicker rebound in demand for their products throughout 2020. IDC estimated that PC shipments climbed 13% year-over-year in 2020, the fastest growth in a decade. Likewise, the semiconductor market saw its strongest quarterly growth since 2016. The sudden uptick in work from home as well as the broader shift of consumer spending away from services and experiences toward durable goods helped buoy this growth.

But that momentum could fade in 2021 and beyond, forcing high-tech firms to look for new avenues of growth and confront some big ongoing challenges, too. Let’s look at some of the key current trends.
 

 

The Great Supply Chain Uncoupling

Arguably no industry is as reliant on China — for both supply and demand — as high-tech is. In the past, companies would often have most or all of their manufacturing within Greater China. This region has also accounted for a rapidly growing share of high-tech purchases. But the combined effects of rising costs and trade tensions have spurred many organizations to relocate their supply chains. For example, according to the Financial Times, one major Taiwanese server manufacturer recently moved its operations back home and to the U.S. and Mexico.

We should expect more of the same in the years ahead as firms seek cost efficiencies, redundancy and other assurances. Supply chains will become less concentrated within China, but companies will still seek to balance their reservations about overreliance on China operations with their need to sell to consumers there, per a Bain analysis.

Cloud Transformation Becomes Realistic

In addition to such relocation and diversification, upgrading to cloud-based systems is one of the most reliable steps toward a more robust high-tech supply chain. But supply chain management (SCM) in the cloud has only recently achieved real momentum. Companies that still rely on on-premises IT infrastructure often struggle to keep up with rapid changes in the marketplace and also scale their operations, all while shouldering relatively high maintenance and opportunity costs. As more of them look to modernize and future-proof their operations, they’re flocking to cloud SCM.

Gartner estimates that cloud SCM growth began to outpace traditional licensed alternatives in 2019 and that in 2020 it accounted for 90% of all SCM spending. Inspirage has guided the cloud transition for customers like Cohu, which brought together all of its operations in one convenient, scalable cloud-based platform.
 

 

Machine Learning Throughout the Supply Chain

Machine learning (ML) and artificial intelligence (AI) can both help detect issues within supply chains before they become unmanageable. For example, ML and AI may enable automated analysis of products for common defects, speeding up time to remediation. The growth of edge computing, which puts processing power for ML and AI closer to the devices actually gathering raw data, is embedding these types of insights deeper into supply chain operations. Supply chains could become more efficient and cost-effective over the long term due to ML and AI enhancements.

Inspirage’s team of supply chain experts can help your company find its way toward more sustainable operations. Connect with us directly to learn more.

Benefit from IBPX consolidation and become a predictive, zero-latency global enterprise by combining Financial and Supply Chain information and leveraging AI, IoT and Prescriptive Analytics

 
Recent major disruptions caused by the pandemic, geopolitical unrest and climate events prove how critical it is for companies to detect and adapt quickly to changing business conditions. Global enterprises often lack a single line of sight to their end-to-end business plan and are therefore unable to execute business decisions and changes in real-time. That’s where Oracle’s Integrated Business Planning and Execution (IBPX) solution comes into play. With IBPX all planning information is consolidated into a single hub allowing for the alignment of Finance and Operations.

Join Inspirage and Oracle to discover how IBPX gives you the capability to predict performance gaps, detect unforeseen improvement opportunities and perform risk management and modeling for product introduction, strategic initiatives and M&A projects. We will delve into supply chain visibility, products/supplier risk management, and financial reconciliation as we share customer case studies and insights from the CFO, COO and IT Departments from selected customers.

Don’t miss this webinar if you want to get started aligning and optimizing your business operations. Furthermore, learn how you can supercharge your IBPX Oracle Cloud solution with Inspirage’s Control Tower to accelerate implementation speed, increase user acceptance and help your business establish an IBPX foundation in 60 days or less.
 

Meet the Speakers

Mo Khurana, Senior Vice President, Global Management Consulting, Inspirage

Mo Khurana leads Inspirage’s global Management Consulting practice. Mo has over 20 years supply chain and commercial experience and is an active industry thought leader. Over the years, Mo has undertaken large complex business transformations in industry on a global scale, such as centralizing business operations, supply chain optimization, delivering Integrated Business Planning maturity level 4+ capabilities and various ERP implementations. At Inspirage, Mo continues to help our clients realize their full potential for their business transformations with our Management Consulting practice that specializes in: Digital Strategy Enablement, Performance Benchmarking, Business Process Services (BPM/BPaaS), Business Intelligence & Analytics and Organizational Change Management.

Jaime Marijuan Castro, Strategy Director for SCM Cloud Applications, Oracle EMEA

Jaime is a Digital Transformation and Industry 4.0 evangelist with more than 20 years of experience across various industries including high tech, automotive, industrial manufacturing and consumer products. While holding several supply chain leadership positions, Jaime has driven teams to success and gained a strong understanding of business processes as well as new digital technologies applied to supply chain management. These technologies include blockchain, IoT, analytics, VR/AR, artificial intelligence and machine learning.

John Conlee, Senior Vice President, Global EPM, Inspirage

With over 20 years of experience working with Oracle and Hyperion technology, John is widely recognized for his expertise in both the technical as well as the functional side of Enterprise Performance Management solutions. He is passionate about ensuring a practical and successful approach while ensuring Finance organizations get the most out of their EPM investments. John has close relationships with Oracle Sales and Product Development along with our customers which enable him to provide valuable insight into the EPM market. As an Oracle Hyperion Certified Consultant, John has served as a panel expert and as a speaker for several Oracle Hyperion User conferences.

Denis Senpere, Vice President Business Development and Sales, Inspirage Europe

Denis joined Inspirage in 2016 to lead the European development of the company. He has more than 20 years of experience in SCM applied to discrete manufacturing, life sciences and consumer goods industries. As such he is often engaged as executive sponsor for Inspirage industrial projects. Denis also serves as a board member to several European technology companies.

Robotic process automation (RPA) sounds futuristic, and although it doesn’t involve a talking, sentient robot a la “The Iron Giant” or even a self-aware AI like Skynet from “The Terminator” series, it is indeed a huge advance in the use of technology for solving complex problems. RPA is much more subtle than any big-screen robot, but still transformative in its effects on enterprise productivity.

It harnesses the power of automated business processes to eliminate significant portions of so-called swivel-chair work, i.e. the manual entry of the same or similar information across multiple systems. The image conjured up by this traditional workflow is a powerful one – imagine downloading an email attachment, copying and pasting some of its data into an Excel sheet, then doing that workflow all over again, except within the different context of your HR software. Even with no literal chair involved, you’re repeatedly jumping (swiveling) between systems, while wasting time and increasing the likelihood of error.

Thanks to RPA, such workflows became much more streamlined. Its robots are all software-based, so there’s no danger of them rusting like the Tin Man from “The Wizard of Oz,” and in fact, they’re highly resilient and self-directing, with designs based on how actual humans already complete common tasks within GUI-based applications. They’re built to scale and to handle numerous activities; the RPA possibilities run the gamut from basic screen-scraping and macros at one end of the spectrum, to sophisticated natural language processing and the sorting of unstructured data at the other.

Looking over the RPA horizon

That said, RPA is still in its infancy, and its evolution could take a lot of twists and turns before it becomes more widely accepted. Here’s what to expect in the near term, over the next year or so:

1. Increasing uptake in the insurance, communications and utilities sectors

RPA really shines in the handling of any work that includes a lot of searching, collating and updating of big datasets. Accordingly, it would seem ideal for the three industries listed above, all of which manage immense amounts of information about customer addresses, billing details and service histories.

Moreover, they need to build bridges between systems like HR and accounting, many of which are still legacy implementations, so that they can ensure their vast data repositories are properly aligned and synchronized. RPA robots can take on much of the manual activity that was previously required to maintain all of this infrastructure, from managing claims forms to processing invoices.

2. Growing popularity among large enterprises

IT research firm Gartner has forecasted robust growth in RPA over the next few years, driven in large part by companies with more than $1 billion in annual revenue. It expects adoption to reach 60 percent of these firms by the end of 2018 and 85 percent through 2022.

At the same time, Gartner foresees the vendor landscape evolving to meet rising demand for RPA. In addition to software vendors, companies specializing in software testing and business process will also get in on the action and thereby expand the number of RPA offerings organizations will be able to choose from.

3. More cognitive abilities within RPA

As we noted earlier, most RPA relies on mimicking how a person will navigate an app’s GUI while completing common tasks. That’s both a strength and a weakness – on the plus side, RPA can work even with older applications that lack modern APIs, but, on the downside, without APIs to draw upon RPA can easily break if there are any changes to the user interface.

To solve this problem, some vendors are looking at implementing more AI capabilities into RPA robots. Don’t expect something like the crafty HAL from “2001: A Space Odyssey” anytime soon, but do expect the roll-out of natural language processing, speech recognition and machine learning to build upon and extend the fundamental GUI-oriented designs of today’s RPA processes.

4. Combining RPA with conversational UI

The rise of RPA isn’t an isolated phenomenon; it’s of a piece with the growth of chatbots and conversational UI, which leverage similar automation in the handling of routine tasks such as first-line handling of customer service inquiries. Going forward, we can expect more pairings of RPA with conversational UI and automation.

For example, a company might use RPA to automate the reordering process for its wholesale buyers, while using chatbots to engage visitors to its website seeking answers to basic questions. If nothing else, the conversational UI there can efficiently direct these customers to live agents for further assistance. Overall, both RPA and chatbots greatly increase the capacity of requests and workflows an organization can handle, since additional manpower is no longer a prerequisite for proper scaling.

5. Further RPA-related enhancements to common workflow tools

The makers of solutions such as Abbyy, the popular tool for document scanning and OCR, are looking to RPA to future-proof these tools. For these platforms, RPA helps streamline both the data processing itself and the flow of information between multiple systems.

In other words, it further reduces the number of situations requiring manual intervention. That leads to increased efficiency in data management, fewer mistakes from human actions and a better user experience for workers, who no longer have to sink so much of their time into repetitive tasks and can instead focus on higher-level activities.

Where should organizations begin with RPA?

Since it’s still in its early stages, RPA can seem like a daunting hill to climb for SMBs and enterprises alike. Fortunately, it doesn’t have to feel this way. With the help of an integrated supply chain expert like Inspirage, you can create a roadmap for modernizing your key processes and systems through RPA.

Our team of experts is here to assist you from start to finish in the selection and implementation of solutions that meet your business requirements. Visit our resource center or contact us directly for additional information.