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Predictive Analytics Target the Still-Broken Supply Chain

Vizen Analytics mixes cutting-edge predictive technology with an old-fashioned growth strategy

Predictive Analytics Target the Still-Broken Supply Chain

Pandemic-era supply chain disruptions taught many organizations a vital lesson about the importance of flexibility and preparedness. While not every supply chain disruption is predictable, advancements in artificial intelligence-powered data analytics are helping business leaders get closer to accurate and actionable forecasts that can mitigate supply chain risks, from demand fluctuations and supplier collapses to weather disasters and geopolitical turmoil.

Predictive supply chain analytics is an area of rapid growth and innovation, say experts, because the technology gets to the heart of supply chain management’s objective.

“The ultimate goal is to create a more efficient system to help drive the bottom line, but also create a system that helps you better serve your customers,” explains Gordon Mackay, managing director, logistics and supply chain, at investment bank and advisory firm Capstone Partners. “Inherent in that is the ability to predict what’s happening within your ecosystem.”


This article is part of Next Target, ACG’s partnership with Grata.


For innovators and their potential investors, intensifying demand for and investment in such solutions continue to drive product development. Yet as excitement over AI comes to a head, end-users and investors are hard-pressed to find service providers that can live up to their hype.

Luckily, experts say, the predictive supply chain analytics space continues to mature, leading not only to solutions with measurable impact on customer supply chains but a market blossoming with M&A potential.

Maturation Through Trial-and-Error

Anticipating supply chain disruptions has always been crucial for organizations of all sizes and industries. But the rapid evolution of AI has heightened chatter about the potential for advanced data analytics to not only help organizations quickly adjust inventory levels or pivot to new suppliers when those disruptions arise, but to forecast upcoming changes and adjust supply chain strategy before they occur.

Technology may be advanced enough to achieve this in theory, notes Mackay, yet the reality for many early adopters hasn’t always met expectations. “Yes, these outside software platforms—many of which have bubbled up just over the last four or five years—are really interesting technologies,” he says. “But there is also a lot of disappointment in terms of what the results are.”

It’s not that the technology itself is bad, he emphasizes. It’s that the supply chain ecosystem is incredibly complex, even with cutting-edge predictive AI at the helm. Quality of data remains one of the largest hurdles for these solutions to achieve their objectives in accurate forecasting, particularly for large organizations in need of systems that can ingest information from disparate platforms.

Related content: The Investments Required for a Resilient Supply Chain

Mackay says product innovators and their corporate clients will have to endure a period of trial-and-error to support progress in the industry. With demand for predictive supply chain analytics solutions continuing to intensify (particularly among organizations with complex global supply chains in areas including pharmaceuticals, consumer retail and high-value goods like semiconductor equipment), Mackay says adoption will continue to grow despite these headwinds.

Forecasting Supplier Lead Time

Walla Walla, Washington-based Vizen Analytics is one predictive supply chain analytics solution provider positioning itself to address complex needs of midsized enterprise and Fortune 500 consumer goods customers.

The company services clients across a variety of end-markets, including fast moving consumer goods for automotive, consumer packaged goods and consumer electronics, with a subscription-based SaaS product that can develop two different models based on user data: a historical model, and a second model that blends historical data with near-term external data to predict changing event patterns. These models uncover root cause factors that impact supplier lead times, allowing clients to achieve more effective production planning and accurate demand forecasting.

If you come in with a flashy platform that looks good but isn’t customized and tailored to the uniqueness of a customer’s problem or use-case, it won’t work. It just looks good on paper.

Greg Foster

Vizen Analytics

Founder and CEO Greg Foster says he is aware of the headwinds facing the industry today, not least of which is the rise of solutions with showy demos that fail to fulfill lofty promises. “If you come in with a flashy platform that looks good but isn’t customized and tailored to the uniqueness of a customer’s problem or use-case, it won’t work. It just looks good on paper,” he says.

Positioning Vizen apart from competitors means taking a grounded approach to growth and product development, he adds: “For us, it’s all about being pragmatic, because just having great predictive analytics and the ability to look into the future doesn’t really matter if we’re not able to prove our customers’ responsiveness to their customer fulfillment.”

Foster isn’t fazed by adoption challenges. “I think there’s a healthy dose of skepticism about software players like us,” he says, adding that he acknowledges how important it is to develop trust with customers in need of custom problem-solving capabilities. Often, he says, organizations will develop bespoke tools internally rather than risk handing data over to a third party. “I think that’s the biggest challenge we face,” Foster says.

But today’s market turmoil offers Vizen the opportunity to put its money where its mouth is. Foster highlights the ongoing conflicts in Gaza and Ukraine, as well as global labor shortages, which have kept supply chain issues at the forefront long after pandemic-era bottlenecks captured headlines.

One major pain point he’s seeing is businesses increasingly maintaining both cycle stock (inventory necessary to meet current demand) and a buffer safety stock (extra inventory kept on-hand in case demand spikes or supplier shipments are unexpectedly delayed). “Over time, our technology smooths out that inventory buffer, saving customers millions of dollars a year by following our forecasts,” Foster notes. “We guarantee a 5x return on whatever clients pay us in a subscription fee in the first year.”

New Tech, and an Old-Fashioned Approach to Growth

Vizen may be working with and developing cutting-edge technology, but Foster emphasizes the company’s “old-fashioned” approach to growth.

“We’re really focused on building our relationships deep and wide,” he says, adding that Vizen’s goal is to retain clients long-term. “Our growth strategy is around our existing anchor clients, building additional anchor clients and deepening our growth within there. That will create a reputation that will get us to the next phase of growth, which will probably be around this time next year.”

Vizen, which Foster says is currently in the “walk” phase of the cradle-crawl-walk-run trajectory, is currently on track to quadruple its client base and sales revenue this year. Backers—including angels, strategic partners, accelerators and institutional investors—have placed just under a million dollars with the company so far. The company will look to raise more seed funding this year and into next, though it will do so diligently and gradually, so as not to dilute value, Foster notes.

Related content: Setting Up Mid-Cap PE Funds and Portfolio Companies for Data Analytics Success

Capstone’s Mackay says investor interest in predictive supply chain analytics remains strong and is growing stronger. “There’s a lot of money going into this space, and there are a lot of startups in the space,” he says. An inquiry within middle-market search engine Grata reveals a whopping 19,810 companies operating in the supply chain analytics space—though only 2,530 of them position themselves within the predictive supply chain analytics arena. Nearly all—2,378—are private and are either bootstrapped or supported by venture capital. Only 56 are listed as private equity-backed.

According to Mackay, some attractive strategic targets can be found amongst supply chain analytics businesses that for one reason or another did not scale or pursue large rounds of funding back in 2021 and 2022 when supply chain challenges dominated the headlines. “These companies can potentially be really interesting M&A targets for strategic parties going through a buy-versus-build decision,” he says

While those headlines may have faded, organizations continue to take the hard-learned lessons from the pandemic and prioritize supply chain visibility and predictability, particularly as AI unlocks the potential for greater sophistication and accuracy of these tools.

According to Foster, strategics and private equity acquirers alike should be paying close attention to this space, because the need will only continue to grow. “The supply chain is still very much broken,” he says. “I hear it every single day.”

 

Carolyn Vallejo is Middle Market Growth’s digital editor.

 

Middle Market Growth is produced by the Association for Corporate Growth. To learn more about the organization and how to become a member, visit www.acg.org.