Read the news today and there is likely to be an article on how generative artificial intelligence (GenAI) is going to change the world. One story will praise the transformative potential of GenAI, the next will shout doom and gloom. Neither is 100% right and neither is 100% wrong.
The mixed perceived potential of GenAI can be seen in responses to the “2023 Gartner Supply Chain Technology User Wants and Needs Survey.” We asked respondents to rate how important they currently saw certain emerging technologies like GenAI and how transformative they felt these technologies were going to be over the next decade. GenAI was an interesting case study. Respondents saw it as one of the most potentially transformative emerging technologies over the long term. But, at this time, it was rated as one of the least currently important technologies.
At this point, many organizations are struggling to prove and realize value from their GenAI investments and pilot projects. Accordingly, Gartner research predicts that at least 30% of GenAI projects will be abandoned after proof of concept by the end of 2025.
The survey findings highlight that before they invest heavily in a technology, companies must honestly assess who they are and what their risk tolerance is. Different supply chain organizations view the value and importance of technology differently, and they should align their investment strategies with their unique identity. Every supply chain and logistics organization has its own culture, and this culture has a significant influence on how leaders must approach and manage their technology investment decisions.
What’s your tech adoption profile?
Gartner has identified five types of technology adopters. These five types are fairly evenly distributed among respondents to the analyst company's "Supply Chain Technology User Wants and Needs Survey."
"Gartner Supply Chain Technology User Wants and Needs Survey," 2023
As part of gaining an understanding of what types of technology they should invest in, supply chain leaders must honestly and candidly assess their organization's risk tolerance. This is because risk tolerance has a notable impact on which technology investments are right for an organization, at what time, and for what reasons.
Gartner research has identified five adoption profiles:
Cautious: These organizations wait until technologies are fully mature and several iterations of the technology have been released.
Conservative: These organizations adopt mainstream technologies once they are proven and lower risk solutions are available.
Adventurer: These organizations prefer to adopt adolescent but maturing technologies with manageable risk.
Pioneer: These organizations may adopt emerging technologies in the early stages of commercialization when there are successful deployments by industry leaders.
Maverick: These organizations favor adopting embryonic, emerging, and often unproven technologies that are relatively new and riskier.
The figure above shows the distribution of adoption profiles among respondents to the “Wants and Needs” survey. As can be seen in the chart, there is a notable disparity among companies in how they approach purchasing and adopting technology.
If buying decisions are not aligned with the organization’s adoption behavior, then investments may be made at the wrong time or for the wrong reasons—or both—and organizations will fail to meet their intended goals and objectives. For example, risk-intolerant companies, like cautious or conservative adopters, should be very cautious of investing in technologies like GenAI today, while risk-exploiting companies (those that are willing to put capital at risk for big payoffs) should take the plunge.
Taking a closer look
In addition to their application profile, there are three other dimensions that supply chain leaders should take into account when deciding what technology they should invest in and when and how these technologies should be implemented: planning, control, and pace of change.
Planning identifies the organization’s approach to creating and adhering to a strategic technology plan. There are three general profile attributes:
Strict—The majority of technology decisions will be driven by and to fit to the plan.
Accommodating—The strategic plan is typically adjusted only under certain situations, such as changes in the business climate or the urgency of responding to new, unanticipated events.
Flexible—The plan is less of a definitive driver for technology decisions, and users have more autonomy to pursue other opportunities where they make business sense.
Control identifies the locus of power for driving the technology agenda, with the following profile attributes:
IT-led—The IT organization and a strong chief information officer drive the technology agenda.
Collaborative—Business and IT work together to determine the technology path.
Business-led—Leaders from the business largely guide the agenda.
Pace of change explores the organization’s receptivity to new ideas and technology approaches, building upon the technology adoption approaches outlined previously with the following profile attributes:
Measured—The enterprise prefers to observe the impact of events and new technology before acting.
Responsive—The enterprise looks for technology to help it react and respond to external events.
Dynamic—The enterprise aggressively pursues new technologies and reacts quickly to external events in pursuit of competitive advantage.
These categories are more indicative of an organization’s buying propensity in terms of when, who, and how they make technology decisions than traditional factors such as company size, geography, or even industry.
These considerations also go a step beyond traditional technology maturity models. Maturity models are a good first step for gaining an understanding of “who are you,” “what you do,” and “how you perform” compared to other companies. However, the three dimensions above help you unlock another level of insight—the “why you do what you do” and the way you do it. This provides leaders with a deeper level of understanding of organizational behavioral traits, much like psychographic targeting in consumer marketing.
These insights can help leaders gain perspective on how cultural differences influence an organization’s supply chain technology adoption behaviors. Thus, they can use the information to determine which technology strategies and investment plans will be most effective with their organization’s unique temperament.
Do you have five minutes to help shape the future of retail by sharing your insights and experience? The MIT Omnichannel Supply Chain Lab has officially opened its 2024 Omnichannel Survey, and researchers want to hear from you.
This year’s survey is investigating the impact of e-commerce on the different tiers of the supply chains, the most common challenges faced when defining and implementing an omnichannel strategy, and the role of artificial intelligence and tech-related innovations supporting it.
What did we learn in 2023?
Last year’s survey unveiled some game-changing trends in omnichannel retailing, particularly around the explosive growth of artificial intelligence (AI). Here are some highlights:
AI is taking over: 70% of retailers are now leveraging AI in their operations, with a 90% adopting it within just the last three years. It’s clear: AI is no longer a luxury; it’s a necessity.
Where's AI making waves? Retailers are using AI for everything from demand forecasting (65% adoption) to pricing optimization (48%) and inventory management (43%). These tools are revolutionizing how businesses operate.
Investing in the future: Looking ahead, 83% of retailers plan to ramp up their AI investments. This commitment signals a new era for retail, driven by technology and innovation.
Be part of the change
As the 2024 survey kicks off, your voice matters more than ever. By participating, you’ll contribute to vital research that will help define the future of omnichannel retailing and technology integration. Don’t miss out on this opportunity to make your mark. Click here to take the survey.
“ExxonMobil is uniquely placed to understand the biggest opportunities in improving energy supply chains, from more accurate sales and operations planning, increased agility in field operations, effective management of enormous transportation networks and adapting quickly to complex regulatory environments,” John Sicard, Kinaxis CEO, said in a release.
Specifically, Kinaxis and ExxonMobil said they will focus on a supply and demand planning solution for the complicated fuel commodities market which has no industry-wide standard and which relies heavily on spreadsheets and other manual methods. The solution will enable integrated refinery-to-customer planning with timely data for the most accurate supply/demand planning, balancing and signaling.
The benefits of that approach could include automated data visibility, improved inventory management and terminal replenishment, and enhanced supply scenario planning that are expected to enable arbitrage opportunities and decrease supply costs.
And in the chemicals and lubricants space, the companies are developing an advanced planning solution that provides manufacturing and logistics constraints management coupled with scenario modeling and evaluation.
“Last year, we brought together all ExxonMobil supply chain activities and expertise into one centralized organization, creating one of the largest supply chain operations in the world, and through this identified critical solution gaps to enable our businesses to capture additional value,” said Staale Gjervik, supply chain president, ExxonMobil Global Services Company. “Collaborating with Kinaxis, a leading supply chain technology provider, is instrumental in providing solutions for a large and complex business like ours.”
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Future warehouse success depends on robot interoperability.
Interest in warehouse robotics remains high, driven by labor pressures and a general desire to further automate distribution processes. Likewise, the number of robot makers also continues to grow. By one count, more than 50 providers exhibited at the big MODEX show in Atlanta in March 2024.
In distribution environments, there is especially strong interest in autonomous mobile robots (AMRs) for collaborative order picking. In this application, the AMR meets pickers at the right inventory location, and the workers then place picks in totes on the robot, which then moves on to another location/picker or off to packing, greatly reducing human travel time.
While the use of robots in distribution is still early in its maturity, for many, if not most, companies, the future is one of heterogeneous robots—different types of bots from different vendors operating in a given facility. With the growth in robotics, these different robots will often need to communicate with each other—either directly or indirectly through use of an integration platform—to automate the flow of information and work. This is broadly termed “interoperability,” and it is an important concept for companies planning warehouse robotics initiatives, with the ultimate goal of achieving a “plug and play” environments where new robots can easily be added to the automation mix and processes adapted over time.
Interoperability example
Why is interoperability important?
Consider the following example. A company buys perhaps 20 AMRs to support collaborative picking. A few years later, additional AMRs are needed to support growth. But now there is another AMR from a different vendor that the company prefers for cost, design, change in stock keeping unit (SKU) attributes, or other factors.
Interoperability will allow a company to keep the AMRs they have and seamlessly add the new AMRs to the mix. Beyond basic integration, a company will want to manage the robots across both vendors in terms of visibility, task assignment, performance measurement, and more, operating as if it’s a single fleet.
That’s a good example of what interoperability is all about.
Are there interoperability standards?
There are some initiatives across the robotics sector to develop cross-vendor integration protocols that will make interoperability much easier. However, these standards, such as VDA5050 (a standardized interface for automated guided vehicles) and the Mass Robotics 2.0 AMR Interoperability Standard, are either not widely used or are still under development.
Many vendors have also started offering support for what is called a “robot operating system” (ROS/ROS2). However, this is a loose, open source framework (not a full standard) that doesn’t fully address the interoperability challenge.
The robotics platform alternative
In the absence of useful standards, companies still have a few options for achieving interoperability. One is the traditional approach of manually programming interfaces between different robots and interfaces between robots and software systems such as warehouse management (WMS) or warehouse execution systems (WES).
The downsides of this approach are well understood. They include extended developing times and the high cost to get the integrations done, as well as a significant lack of flexibility down the road, with some added risk thrown into the mix as well.
A better alternative is the use of a platform strategy. Which begs the question: What is a robotics platform?
A robotics software platform is a middleware ecosystem—cloud-based or on-premise—that provides various capabilities and services from integration to fulfillment planning and execution. It also acts as a bridge between automation systems and various enterprise software applications.
The starting point for any robotic platform success is, in fact, integration. That integration capability includes advanced tools that enable flexible “no code/low code” approaches to connecting robot fleets.
The right platform can also more rapidly integrate with WMS/WES or other software applications, using AI to greatly accelerate the often time-consuming data-mapping process. Once the WMS/WES is connected to the platform, then the robots are also connected to enable real-time, bidirectional access to the WMS/WES data.
Such a platform delivers interoperability across robot types and connects different automated processes. A simple example would be a communication from the platform to a robot needed to move goods from receiving to reserve storage, where another robot is made aware via the platform that there is a new putaway task ready for completion.
Other interoperability considerations
To maximize interoperability opportunities, companies should consider the following interoperability-related capabilities that may be available from a given robotics platform:
Flexibility in integration based on robot software functionality: Different robot vendors come with software at different levels of maturity. An interoperability platform should be able to work with robotic vendors at any level of software functional capability, ensuring flexibility in robot selection.
User experience consistency: For interoperability to be functionally effective, the user interface across robotic-enabled processes should be consistent, so that users can easily interact and switch between different tasks.
Flexible communication protocols: A platform should provide support for a wide range of different protocols, such as application programming interfaces (APIs), socket communication (a two-way communication link between a server and a client program), web services, ROS/ROS2.0, and VDA5050, to name just a few.
Observability: AMRs especially will generate huge of amount of data on their movements and activities that can be used for analytics. The robotics platform should normalize data packets from different vendors to create a unified dashboard.
Safety and risk mitigation: A robotics platform can help achieve safety across different types of robots by understanding the safety protocols of different machines and coming up with a common set of rules. These rules will exist in an extended fleet manager that runs in the platform and sits on top of the fleet managers of each individual brand of AMR.
While some of these capabilities may not be relevant in a company’s early years in warehouse robotics, they could prove valuable down the road, so give them some consideration today.
Interoperability use cases
We’ve already covered a couple of common robotic interoperability use cases:
Adding new robots of the same type but from a different vendor and having all of them operate together as a single fleet.
Connecting different types of robots or automation to support multi-step process flows (for example, receiving to putaway).
Here is another: One global consumer goods company wants to heavily automate distribution processes but give individual regions or countries they operate in the flexibility to select the vendor for a specific type of robot (for example, a layer picker) and be able to easily plug that specific equipment into the larger platform infrastructure. This allows a centralized automation strategy with local execution.
The Interoperability Imperative
For a significant and growing number of companies, the future on the distribution center floor will be robotics of multiple types and vendors. To maximize flow and productivity, these heterogeneous environments must adopt interoperability strategies, enabling systems of different types to operate as if a single fleet. While standards to help with all this may arrive in future, for now a robotics integration and execution platform will provide an attractive alternative to traditional programming-heavy approaches.
Pharmaceutical groups are breathing a sigh of relief today after federal regulators granted many of them more time to come into compliance with strict track and trace rules required by the Drug Supply Chain Security Act (DSCSA).
The regulation was initially scheduled to be required by 2023, but that has been delayed due to the steep logistics and IT challenges of managing the reams of data that must be generated, stored, and retrieved. The most recent target update was November 27, but industry experts say many businesses would probably have missed that date, too.
Facing that reality, the FDA yesterday again delayed that deadline until next year, setting new deadlines for various trading partners: Manufacturers and Repackagers have until May 27, 2025; Wholesale Distributors have until August 27, 2025; and Dispensers with 26 or more full-time employees have until November 27, 2025.
Pharmaceutical businesses quickly cheered the move. “HDA and our pharmaceutical distributor members applaud the FDA’s decision to grant an exemption for the DSCSA’s enhanced drug distribution security (EDDS) requirements for eligible trading partners,” said Chester “Chip” Davis, Jr., president and CEO of the Healthcare Distribution Alliance (HDA), which is an industry group representing primary pharmaceutical distributors, who connect the nation’s pharmaceutical manufacturers with pharmacies, hospitals, long-term care facilities, and clinics.
“While many in the supply chain have made significant progress throughout the stabilization period, some are still struggling to establish data connections. Given the interdependency of the pharmaceutical supply chain, FDA’s phased-in approach will allow supply chain partners to better align their data exchange processes to ultimately achieve full implementation and also acknowledges the progress made thus far,” Davis said.
“As we continue to make progress toward full DSCSA implementation, HDA and our distributor members will remain engaged with our public- and private-sector partners to share information and education, as we move toward our shared goal: helping patients and providers safely access the medicines they need.”
The North American robotics market saw a decline in both units ordered (down 7.9% to 15,705 units) and revenue (down 6.8% to $982.83 million) during the first half of 2024 compared to the same period in 2023, as North American manufacturers faced ongoing economic headwinds, according to a report from the Association for Advancing Automation (A3).
“Rising inflation and borrowing costs have dampened spending on robotics, with many companies opting to delay major investments,” said Jeff Burnstein, president, A3. “Despite these challenges, the push for operational efficiency and workforce augmentation continues to drive demand for robotics in industries such as food and consumer goods and life sciences, among others. As companies navigate labor shortages and increased production costs, the role of automation is becoming ever more critical in maintaining global competitiveness.”
The downward trend was led by weakness in automotive manufacturing, which traditionally leads the charge in buying robots. In the first half of 2024, automotive OEMs ordered 4,159 units (up 14.4%) but generated revenue of $259.96 million (down 12.0%). The Automotive Components sector was even worse, orders 3,574 units (down 38.8%) for $191.93 million in revenue (down 27.3%). Declines also happened in the Semiconductor & Electronics/Photonics sector and the Plastics & Rubber sector.
On the positive side, Food & Consumer Goods companies ordered 1,173 units (up 85.6%) for $62.84 million in revenue (up 56.2%). This growth reflects the increasing reliance on robotics for efficiency in food processing and packaging as companies seek to address labor shortages and rising costs, A3 said. And the Life Sciences industry ordered 1,007 units (up 47.9%) for revenue of $47.29 million (up 86.7%) as it continued its reliance on robotics for efficiency and precision.