Scott Hebert is the Americas Chief Revenue Officer for SYSPRO, a provider of industry-built enterprise resource planning (ERP) software.
Middle-market manufacturing is a large but often overlooked segment of the economy. Middle market companies, defined as those making between $10 million and $1 billion in revenue, account for 3% of U.S. businesses, but are responsible for about one-third of private sector GDP and employment, according to a 2023 report from the National Center for the Middle Market. It’s also a fast-growing segment of the economy, and according to the same report, the mid-market grew revenue at 12.2% in the fourth quarter of 2022, while the S&P 500 companies grew revenue by 4.4%.
As can be seen, it’s a critical economic sector whose growth outpaces those of much larger companies, with manufacturing making up a large part of it—about one-sixth, according to research from Generational Equity. That said, I see the mid-market facing significant challenges, many of which revolve around technology, and more specifically, data analytics. While large manufacturers are starting to deploy advanced AI, including generative AI, the large data analytics systems that most large companies now take for granted are not as widely adopted within mid-market manufacturing.
Hurdles For Mid-Market Manufacturers Deploying Analytics Platforms
Mid-market manufacturers are not technology-averse. However, large analytics platforms are expensive to operate and maintain, and mid-market manufacturers don’t tend to have the same level of financial resources as large public companies. Mid-market manufacturers also usually employ relatively small IT teams, and they don’t often have access to the kind of expertise or budget to deploy and operate the complex data stores these platforms require. These platforms typically need the expertise of two or three data analytics specialists or data scientists to operate them properly.
This lack of analytics capabilities can put mid-market manufacturers at a significant competitive disadvantage. Ted Lasso put it well: “There’s two buttons I never like to hit, all right? And that’s ‘panic’ and ‘snooze.'” Without timely, actionable information, the likelihood of pushing one of those is all too likely. In some cases, if you can’t respond to a new situation within 24 hours, you’ve lost an opportunity. In others, what appears to be a crisis may actually not be, and a company may overreact by, for example, laying off key employees unnecessarily and placing it in a weaker position.
I believe that there is a way for mid-market manufacturers to leverage analytics without running into the above challenges: Leverage the ERP platforms that they have already deployed.
ERP is the mid-market manufacturers’ system of record; all critical data related to running the business lives there, including inventory, purchase orders, accounts payable, supply chain, equipment, labor and much more. Most mid-market manufacturers do have an ERP system, and even if the ERP doesn’t have analytics already embedded within the platform, vendors will almost certainly partner with other companies that can provide pre-integrated analytics add-on capabilities.
Getting The Most From A Mid-Market ERP And Analytics Combination
Leveraging the ERP platform can enable mid-market organizations to utilize analytics without having to invest in a data lake, data scientists and a large analytics software platform. But business leaders need to be careful about how they implement ERP analytics.
In some cases, analytics may be built into the platform, but make sure to conduct strong due diligence to ensure that the organization will get truly valuable analytical insight and not just a data presentation dashboard. If analytics is not built in or if the existing analytics functionality is poor, the vendor may have analytics add-ons from independent software vendor partners.
IT and business leaders don’t have to do this alone. In my experience, any organization that has deployed an ERP platform has almost certainly contracted with third-party experts to assist with its selection and deployment. They can help select the right add-on analytics package, and, if analytics is built in, they can help optimize it to gain maximum value.
Next, once the IT team is confident that the analytics add-on or built-in functionality will provide useful insights, they should ensure that it can use the data in the platform. One of the big advantages of using ERP data for analysis is that it’s already relevant, clean and—as long as the analytics package can use it—ready for analysis. Add-ons pre-integrated with the ERP platform should use ERP data without any ETL (extraction, translation and loading) required, and, of course, built-in analytics should do the same.
If the analytics package requires the company to perform ETL of the ERP data, then your organization will likely be right back in the same situation that prevented you from using analytics in the first place; ETL requires data experts to perform.
Next, since the ERP is already the system of record for key business functions—financials, inventory, operations, supply chain and more—insights from analytics should be integrated into business process flows within the ERP. After all, insights won’t do an organization any good if they can’t be translated into action.
The Roadmap To Efficiency Through Analytics Integration
Business leaders need to take a careful, methodical approach to integrating insights into their processes. To become more informed, look to speak with other business owners as well as the employees who work within the relevant processes day to day. Using these insights, look for opportunities to optimize various processes through analytics. Likely, many existing processes within your business involve information gathering and manual analysis that can be replaced with analytics, enabling your employees to perform their jobs more efficiently and spend their time on more valuable tasks.
The ERP platform is already a powerful tool for running a mid-market business. But I believe it can be even more valuable if you effectively leverage the data that’s already in your system to integrate into existing workflows.
Mid-market manufacturing is a sector to watch in the coming years. It’s a massive source of both economic and employment growth, and with these companies having access to the analytics power that those in the Fortune 500 have employed over the last decade, I think we can expect even bigger things to come.
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