Over the past 15 years, XFlowdata has executed a wide range of ERP and data projects. We’ve accompanied clients through data migration, implemented new data models, revised data management processes, cleaned up master data, and much more.

These varied projects have taught us a number of lessons over the years. Here are 6 key things I’ve learned :

1. Bad data can be a matter of perception

There are a number of situations that may lead a company to re-evaluate the quality of its data. Innovations or changes in legal requirements can make it seem like there is no good data available. Conflicting departmental needs can also skew perspectives: good data for a storeroom operator might be bad data for a production planner.

It is tempting to want to solve the issue by building new systems, new tools, new processes, or even new teams. But wait! The data you need may already exist, just hiding behind a slightly different model or another name. Taking the time to investigate existing resources and maximising under-used applications, especially ERP tools, can often help resolve the situation, with minimal additional investment.

2. Bad data is caused by poor processes and governance

No one intends to create bad data but when working under pressure, mistakes can easily happen. Simple errors like a misspelled address or incorrect order quantity can have significant business repercussions. In many cases, the fix is easy but it requires an engaged team willing to adopt new processes and follow governance.

3. Data solutions begin with people

Effective data management depends on collaboration and strong leadership. People need to work together to define, refine and adhere to data standards and processes. But that’s only half the battle. Proper governance must be put in place in order to ensure that these standards and processes are followed. Without this, people will eventually find good reasons to shortcut processes, negating all the data cleaning efforts. Strong management backing is essential to empower those in charge of governance and sustain the efforts in data quality.

4. Quantifying the value of data is challenging

While it’s now easier than ever to persuade management of data’s intrinsic value, the real challenge lies in conveying the importance of understanding the data. For example, it’s impossible to convince management that duplicate customer records have a bad impact on sales if one can’t explain what the duplicates are and how they affect the sales process.

Understanding data requires collaboration across teams and departments. Together, we can understand how data is organized, what it means for the business, how information moves through the organization and where opportunities (and threats) are hiding. Tools can help accelerate this process but they can never replace people’s input and collaboration

5. Not all experts make good managers, not all managers make good project managers

We often assume that senior experts should manage people or projects. This can of course work if the context is right: clear goals, a strong team and a realistic timeline. If the right context is not in place, experts pushed into management positions can easily become overwhelmed, putting their health at risk, creating tensions with colleagues and ultimately derailing the project. Often, things take a wrong turn when their senior management is not attentive to the project.

Similar issues can affect managers, people with skills to deal with other people and operations. Managing a business operation often means improving workflows and keeping people motivated. We often assume that a successful manager can take on projects of growing complexity without taking into account their ability to manage the workload. And once again, if their senior management is not supportive, the situation can spin out of control.

6. Change management is a joke if management is not serious (pun intended)

In my experience, effective change management requires more than just executive sponsorship; it demands their active participation and understanding. Projects thrive when leaders know who is who, understand the work and most importantly, drive the team for results. Executive engagement is instrumental for ironing out concerns, resolving conflicts and encouraging people.

Every challenging project we encountered suffered from a lack of senior management involvement, which invariably led to poor outcomes. On occasion, reevaluating and adjusting the project’s scope, objectives, and other aspects can mitigate these issues but generally, when a project lacks support, it’s often because its value hasn’t been adequately communicated or recognized.

So, what did we learn?

After all these years, my key takeaway (and the reason why I enjoy this field so much) is that no matter how technical, how conceptual, how complex the work can be, success lies in our interactions with one another, in collaborating to build value and resolve conflicts.

Like kids, we find pleasure in new gadgets, in solving puzzles and learning new tricks. But the real thrill is when we help others improve their situation.

Picture of Jean-Francois Minsart
Jean-Francois Minsart
Jef is a veteran SAP data consultant with over 20 years experience. His career took him around the world to support initiatives as varied as mergers, systems integration, upgrades, software development and roll out, etc.​