Manufacturers Are Rushing ERP Modernization and Paying the Price

As AI readiness creates new urgency for manufacturers to update their lagging ERP systems, many are tempted by “big bang” go-lives that promise speed. That speed comes with concentrated risk, though. Proper sequencing may be the biggest determinant of transformation success.

Big bang implementations, where new ERP systems were brought online all at once, was a more common way for manufacturers to update their systems of record. Big bang implementations offered speed, and though it concentrated risk at the point of transition, the risks were thought to be mitigable with good preparation and communication.

Facing ERP System Complexity, Headwinds

However, manufacturing has become more complex not only from a global supply chain and geopolitical perspective, but a technological one. As the system of record for manufacturers, ERPs manage countless workflows, serving as the backbone between planning, sourcing, manufacturing, warehousing, logistics and finance.

The issue is as the demands on ERP have grown, so have the tools used to manage everything. Many ERPs rely on integrations and third-party apps on top of their base offerings to manage workflows. The amount of information and data these systems manage is much higher than before, as the explosive growth of IoT technologies contributes to the data overload manufacturers face. Globally, companies have increased the amount of data they store by 25% in the last 10 years.

The irony is despite collecting so much data, most manufacturers are operating with only a fraction of the data they actually need. The business world has been so focused on data creation that data cleanliness and data quality have fallen by the wayside.

Which was fine… until it wasn’t. The world moves faster today. Speedy decision-making, enabled by AI, is a normal expectation. Businesses are looking to close their books in days, rather than weeks, and companies that can operate in near real-time can see as much as 50% higher revenue growth than those that don’t.

The promise of speed rests on these businesses’ neglected data discipline. For many manufacturing businesses, the data foundation is uneven at best, as customer and supplier data live in separate ecosystems, floor data is inaccurate and work centers aren’t fully costed.

Challenges of Upgrading, Automating ERP Processes

Manufacturers are desperate to update and automate their ERP processes, but are met with an uncomfortable reality: Their desire to transform is outpaced by the organizational maturity necessary to support it.

While big-bang implementations may have worked when systems were much simpler, a big-bang approach today only focuses on data issues. Systems built on top of poorly structured data can create a series of compounding errors.

Worse yet, automation can make it difficult to isolate and diagnose exactly where the problems lie, making the process of untangling workflow disruptions expensive and time-consuming.

Instead, businesses need to rethink ERP implementation to understand transformation speed does not equal success. Technological transformations at this scale — and with systems so vital to business success as ERPs — are as much a matter of people management as they are data and IT. Businesses can only transform if they find a balance between the implementation, configuration and testing of solutions and the rate at which teams can adopt them.

The result is a significantly longer runway than before required. It has to start with a maturity assessment that sets the ground stakes of transformation. Many leadership groups know what they’re trying to achieve with a new ERP system, but not many understand the reality of where they’re starting from. It’s only by understanding (and agreeing on) the size of this gap that businesses can build a realistic roadmap to get them where they’re trying to be.

Maintaining a Realistic Approach

The reality is, for the majority of manufacturers, even if they wanted to do a big bang go-live, they couldn’t. The data maturity isn’t there. Companies need to be pragmatic in their approach. Instead of achieving 100% maturity across the company, manufacturers should focus on getting their highest-value use cases to high maturity first.

Pushing for an all-at-once go-live is how ERPs start to fail. Data becomes unreliable, employees begin to distrust it, and they regress. They end up working around the system and creating a data vacuum that can bring the whole program down. Finding the right pacing and sequencing for this scale of transformation isn’t a “soft” concern; it’s a legitimate constraint on successful execution.

Big bang implementations don’t fail because the software “doesn’t work.” They fail because manufacturers aren’t ready to flip all at once. Successful use cases treat modernization as a business discipline. Manufacturing winners aren’t determined by go-live speed, but by the best transformation process. In an environment where margins are tight and errors are expensive, sustainable transformation beats dramatic launches every time.

Todd Hass is a Partner in RubinBrown’s Consulting and Manufacturing & Distribution Services Groups.