Three ways a data analytics solution helps with ERP migration

There are many benefits for companies to invest in enterprise resource planning (ERP) technology, including enhanced automation for the ability to deal with a complex data landscape. Businesses who are upgrading from legacy systems to cloud-based solutions also reduce costs, improve security and easily integrate with other solutions. Implementing a new ERP is a big project that requires planning. So how can you keep all your data intact and accessible as you’re switching ERPs? ... a data analytics solution

Many businesses find the migration more successful with an accompanying data analytics solution. An ERP plus a data analytics solution has a powerful impact on your core business processes. You can rely on real-time insights from data at each decision point, improving productivity and empowering informed decision making.

However, implementing an ERP project impacts and demands changes in all your other data management projects, such as reporting, analytics, IoT, data governance, custom innovation projects or cloud adoption.

We look at three critical phases of the ERP migration and demonstrate how data analytics is key to a successful implementation and ongoing fast reporting.

Phase 1. The preparation

A vast amount of work goes into the preparation for an ERP migration. Much of that effort consists of prepping the data from the legacy system so that it imports well into the new ERP.

The problem:

Most companies underestimate the time and expertise involved to do this. A common problem is the people who best understand the data — product managers, collections specialists, pricing managers — do not often have advanced database management and data manipulation skills, so aren’t often involved. However, they need to be included, which means adding resources, steps and time into the process of understanding the old data and getting it into the new system, which often delays the project.

The solution:

Increase the time for prepping from the outset, which helps avoid delays and undermining the ERP’s integrity in the eyes of the users.

Here’s when a data analytics solution is really beneficial, yet most companies don’t want to add or use another solution during ERP preparation. Many don’t realize a data analytics solution can do much of the clean-up work because it can find and correct bad data. Data analytics can detect missing or incorrect fields such credit limits, product classifications, pricing groups and get your fields in good shape.

During this phase, it is also a good idea to consider what new data you want to add to the ERP. The extra may be new data sources you want to include, new reports you want to add across each business unit and extra fields you are not capturing now.

Ideally, you want to make it simple and easy to identify and process the data and get people in the company using the data. A robust but easy-to-use data analytics solution that is deployed upfront means users of the data, such as product managers and sales managers, can provide feedback on their needs prior to implementation and start to use the information without the relying on the IT team.

Phase 2. The initial go-live

The problem:

An ERP migration is a departure from business as usual — but it is neither entirely a one-off clean break nor completely a staggered break. An ERP migration is a cut-off in that business processes must shift from one system of record to another. Yet, an ERP migration is a staggered break, which means the processes, relationships and the historical data from before the migration do not suddenly disappear on the go-live date.

It is necessary to find an approach that accommodates the shift between ERPs while still providing the flexibility to incorporate rolling changes to processes and data management.

Many companies choose to migrate in batches. Retailers with many stores and wholesalers with a number of branches select a smaller outlet to test and gradually roll out to all stores and branches once training on the new system is complete. Most successful implementations have field trainers who visit branches and stores to do onsite training.

Some migrations involve running two systems simultaneously (e.g., different locations on different ERPs as part of a rolling migration). Maintaining historical transactional information from the legacy ERP is critical — but the costs and complexity of importing that data into the new ERP can be high.

The solution:

Try storing valuable legacy data somewhere accessible, such as a data analytics solution.

The goal should be to have one solution that combines data across ERPs into a “single source of truth” that can be used across locations, across months within a single financial period, and so on. This is both a short-term goal and a long-term necessity for reporting data stored in both the new ERP and the legacy system. To meet this need, a data analytics solution should be able to integrate and combine transactions and records from multiple sources.

Phocas 3. The long-term aftermath

The problem:

ERP conversions are at most risk of failing in the second or third month after go-live. It is in these months after the migration that the focus and energy of the conversion dissipates. Often the IT team has stopped its intensive daily testing, used up its allocated time and moved its resources to the next project.

The immediate emergencies of the conversion are complete, but perhaps ongoing problems don’t get resolved entirely as temporary workarounds inadvertently become permanent processes.

The longer these inefficiencies and flawed processes hang around, the more difficult they become to correct and the more limited the ROI from the conversion.

The solution:

This is when a data analytics solution can be invaluable. The software can quickly identify if products are not converting correctly or sales are not coming across as they were meant to when the new ERP is live.

Data analytics will also allow you to automate reporting, KPIs and metrics. Alerts can be great tools to surface ongoing areas of concern impacted by the migration — order turnaround times, warehouse productivity, declining or lost customers, etc. This frees up the IT team to do “fire-fighting” inherent in an ERP migration and the other users can identify issues relevant to them such as negative inventory, low margin sales and do their own reporting.

A data analytics solution helps show you the data on which you need to keep tabs — not merely give the possibility of finding it on your own. Data analytics adds value to your ERP not only during migration, but for the coming years by automating reports and KPIs early in the process.