If you’ve made it through our last two blog posts of this series and learned at least one valuable tidbit of information, we’ve done a good job. As a refresher, we previously talked about the types of Key Performance Indicators (KPIs) a manufacturing company should focus on during an ERP implementation. We also discussed how to leverage KPIs proactively, rather than reactively, so you can make better more informed business decisions.
Now, we’re going to immerse ourselves in data, which we’re sure you know, goes together with ERP software like peanut butter and jelly. Companies who place high emphasis on data see an average annual revenue increase of 5.32% due to better data use. That’s why in our blog series finale, we’re providing some key tips that will help build your confidence in the data so you feel comfortable making those crucial data-driven decisions that maximize operational productivity and gain business advantage.
Don’t Doubt the Data
One of the biggest impediments companies face after an ERP implementation is doubting their data. A common concern we’ve heard from Controllers, CEOs, and Inventory Managers is “Can we trust the data?”. However, we’ve also noticed that after implementation, the concern changes to “How do I actually use all of this data to get the benefits of the ERP we were sold pre-implementation?”. We’ll be answering these questions (and more) below, but first a behind-the-scenes look on why businesses may doubt their data.
When companies go from three systems down to one unified system, where the data must be cleansed and tested, there’s sometimes data issues post implementation. This is where data-trust issues originate. Pre-implementation the data might be in multiple places and there are 4-5 key pieces of data (or data attributes) to track like address, payment method, common products ordered, etc. Post-implementation you have a LOT more data that can be captured, sometimes up to 45. That’s a big change from 5 to 45. With organization’s average estimated cost of poor data quality at $12.8 million per year, it’s imperative the data transformation is handled correctly so data-trust issues don’t undermine your ERP implementation.
Capture Pre & Post Implementation Data
The first step in learning to trust the data is during pre-implementation. It’s here where you gather the first batch of attributes that make up your data. This gives you a clear jumping off point too. Most packages allow you to capture a lot of different attributes, such as customer, supplier, items, build materials and so forth. Capturing data before implementation gives you the opportunity to compare the pre-data with the new data elements post-implementation. This step cannot be skipped otherwise a fundamental aspect of ensuring data quality can’t take place once the new system is implemented.
Capturing the pre-implementation data goes hand in hand with capturing data post-implementation. Recording post-implementation data is equally as important because, as we mentioned before, we need to compare the two separate data sets. Most companies don’t know how the new data will be utilized, so aren’t sure what data sets should be captured. We can simplify it for you: Capture as much data as you possibly can. Rich Harbin, Founder and President of IntelRise states, “The more data you capture post-implementation the better off you are, plus the more familiar you become with the new ERP system. That’s a win-win.”
Continuous Review of Data Attributes
The next step (which is where it becomes challenging) is changing the basic data to the new more complex data. There must be a continuous review of the data attributes to ensure continuous data quality assurance. No matter how hard this is, these reviews must happen. Data management and learning to trust the data is a major mindset shift, but inevitably by capturing, monitoring, and tracking the data that feeds your KPIs, you will have data quality assurance. Even after you’ve put in place a continuous review, you still might not know how all this data will be used yet. Rich says, “That’s okay! The more you get used to the new system, the more capabilities, reporting, and insight will become available.” So, the next big question is again, “How do we use this data?”
Utilize Business ERP Processes
A recent report by Fortune Business Insights finds the integration of Internet of Things (IoT) with business processes is expected to emerge as the central growth driver. The key to this is using your data to utilize business ERP processes, but how do you actually do that? It’s done by leveraging data attributes as part of your business processes. More specifically, identify yield KPIs and leverage those in various aspects of the business to improve efficiency and profitability. Look at designing new ways of working through creating new business processes that communicate information to and from your different departments.
This integration between departments forms collaboration and cohesion within the company when they normally work in silos. Rich recalls a story about a past client, “Prior to this client’s ERP implementation, the company had a stringent silo mentality. Post-implementation they were better able to break down these barriers and work in a more integrated platform where they’re sharing data, attributes, and information easily between each other.” He continues his story, “With their new ERP system, they can capture the NAICS code on all customer record, which may not be leveraged for ordering, but was very useful for marketing because it gave them information on who they could sell to.”
Forecasting, Planning and Reporting
It should be clear by now how reporting capabilities company-wide are enhanced with a unified ERP system but what about forecasting and planning? Companies around the globe spend millions of dollars on ERPs to enrich their data and because of this, the expectation from management is to find something tangible to prove that. A real-life example of this is another client of IntelRise. This client successfully implemented an ERP system under budget and on time, but they were looking for more. For their ERP project to be considered a success they needed proof they were better off than where they were before. Rich steered them to the data for answers. He asked them, “Are we trending? Where were we before?” Since they captured pre and post implementation data attributes, they could easily compare the numbers to show they were receiving 30% more than pre-implementation. This was proof enough that their ERP implementation was a major success.
Previously we told you what KPIs to prioritize and how to leverage them proactively, but now you know data quality assurance and how that can impact an organization. Doubting the data is an easy mistake that can have long-term harmful effects especially on your ROI. From our many years of experience working closely with clients, we can help put the mistrust about the numbers to rest so you can focus more on business growth and boosting cash flow. IntelRise’s friendly and knowledgeable experts are always here to help you along your ERP journey.
Table of Contents
Key Takeaways
- After moving from multiple systems into one unified ERP, businesses often go from tracking just 4-5 data attributes to as many as 45 — that jump is usually the root of “can we trust the data?” concerns post-implementation.
- Capturing data both before and after implementation gives a baseline to compare against, and skipping that pre-implementation capture step makes it much harder to verify data quality once the new system goes live.
- Data trust isn’t a one-time fix — it requires continuous review of data attributes to catch and correct issues as the business gets more comfortable with the new system’s capabilities.
- Once data is trusted, the real payoff comes from using it inside actual business processes — for example, one client used a previously uncaptured NAICS code to identify new marketing and sales opportunities.
- Comparing documented pre- and post-implementation data is what turns “we think this ERP helped” into a provable result — one client used this comparison to show a 30% improvement over their prior baseline.
- Doubting the data after an ERP go-live is common, but treating that skepticism as a signal to double down on capture and review — rather than abandoning the new system — is what lets companies actually realize the ROI they were promised.
Summary
The gap between an ERP implementation that pays off and one that doesn’t often comes down to whether a company trusts the data enough to actually use it. That trust doesn’t happen automatically — it’s built by capturing data before the switch, capturing it again after, and reviewing it continuously as the new system reveals far more detail than the old patchwork of spreadsheets ever could.
Once that trust is established, the data stops being a source of doubt and becomes a tool: for spotting inefficiencies, breaking down departmental silos, and proving — with real before-and-after numbers — that the implementation delivered what it promised. If your team went live on a new ERP and still isn’t sure the numbers can be trusted, the fix usually isn’t more software; it’s a more deliberate approach to capturing and reviewing the data you already have.
FAQ
Why do companies stop trusting their data after an ERP implementation?
Moving from several disconnected systems into one unified ERP often means going from tracking just a handful of data points to dozens more — sometimes jumping from around 5 tracked attributes to as many as 45. That sudden increase in data, combined with the cleansing and testing every new system requires, is usually what triggers the “can we trust this data?” concern after go-live.
What’s the benefit of capturing data before an ERP implementation?
Capturing data before implementation gives you a clear baseline to compare against once the new system is live. Without that pre-implementation snapshot, it becomes very difficult to prove whether the new ERP actually improved a specific metric, since there’s nothing accurate to measure the “after” against.
How much data should a company capture after going live on a new ERP?
As much as is realistically available. Since most companies aren’t sure yet how new data will ultimately be used, capturing broadly post-implementation — rather than guessing which attributes matter — means the data is there when a use case does emerge, whether that’s for reporting, forecasting, or spotting a new business opportunity.
Can better data actually change how departments work together?
Yes — when data is captured consistently across a unified system, it becomes easier to share information between departments that previously worked in silos. One example from this post: a company began capturing a customer’s NAICS code for operational reasons, only to find marketing could use that same data to identify new prospects — an integration between departments that wasn’t possible when data lived in separate systems.
How can a company prove an ERP implementation was worth the investment?
The clearest way is by comparing pre- and post-implementation data on the specific metrics that mattered most going in. In one example from this post, a client captured data attributes both before and after their implementation and was able to show they were receiving 30% more than their pre-implementation baseline — concrete proof the investment paid off.