Master data management: a practical guide

This is cheap to get right at the start and expensive to retrofit. This guide covers what master data management actually involves, where it usually goes wrong, and how to tell whether yours is in reasonable shape.

Most data problems are ownership problems that turned into technical ones. Nothing below assumes a large team or a large budget — most of it is a decision somebody has to make and then write down.

Why it matters

Two systems with different customer records will disagree at the worst moment. The cost of getting this wrong is rarely visible on the day it happens. Write the reasoning down alongside the decision, because the reasoning is what changes first.

For most businesses the question is not whether this matters but how much of it is worth doing right now. That depends on what you are trying to achieve in the next few months, not on best practice in the abstract. This is the sort of thing that compounds, quietly, in both directions.

How to approach it

Decide which system is authoritative for each entity. The teams that handle this well are rarely the ones with the biggest budgets. Doing this properly once is usually cheaper than doing it approximately three times.

Numbers get quoted in meetings long after anyone remembers how they were calculated. The version that works in practice is usually less elaborate than the version described in the guides.

Reconciliation is cheaper than arbitration later. Where this goes wrong is almost never a lack of knowledge. The teams that stay on top of it are the ones who put it on a calendar rather than a wish list.

A working checklist

If you want a quick read on where you stand, work through this. Anything you cannot answer confidently is where to start.

• Two systems with different customer records will disagree at the worst moment
• Decide which system is authoritative for each entity
• Reconciliation is cheaper than arbitration later
• Someone is named as the owner, not just assumed to be
• There is a date in the calendar to review it again
• The decision and the reasoning behind it are written down somewhere findable
• You could explain the current setup to a new hire in five minutes

What to watch for

The most common failure is not doing this badly. It is doing it once, during a launch, and never revisiting it. Circumstances move, the setup does not, and the gap widens quietly until something breaks or somebody notices the numbers.

• It was configured during a launch and has not been touched since
• Different people in the business believe different things are true about it
• There is no way to tell whether the last change helped or hurt
• The only person who understands it has left, or is about to

Data outlives the applications built on top of it, which is why the model deserves more thought than the screens. Where this goes wrong is almost never a lack of knowledge.

How we approach it

On our projects this gets handled during the build rather than added afterwards, because retrofitting it costs several times more than including it. We write down what was decided and why, so the next person to touch it is not guessing.

If you are working with someone else, the questions worth asking are simple: who owns this, how will we know it is working, and what happens when it needs to change?

What to do next

Pick the single item from the checklist above that would cause the most trouble if it turned out to be wrong. Fix that one, confirm it worked, then move on. If you are not sure where your systems currently stand on this, it takes us about an hour to find out.