“Bad data causes a whole lot of unnecessary hassle.”
Getting your master data in shape pays off
Neuvolab’s experienced consultants have seen firsthand the consequences of poor master data management. Read our interview where the Neuvolab team discusses common data management challenges and how to overcome them.
The information system doesn’t work. Data is missing, and the data that exists is incorrect. No one really knows why.
The Neuvolab team has seen companies’ master data problems up close. They are extremely common — in almost every company something is wrong with data management.
Master data refers to the company’s basic information needed to manufacture and sell its products — such as data about raw materials, components, customers, and so on. Data management is about how this information is stored, maintained, and what it is used for.
Master data is also often called core data. And that’s exactly what it is. When master data is wrong or difficult to use, it affects the entire business: outdated inventory balances, delivery reliability issues, production inefficiency, work safety challenges, and much more.
– If the required component’s quantity hasn’t been updated and no one notices the shortage until the last moment, the whole production line stands still, notes Nona Onnela, giving one example.
– Or something has been delivered, but no one remembers to invoice it, continues Jukka Lehti.
– I’ve even seen situations where, alongside the information system, people have had to maintain Excel sheets because the system cannot be trusted. That means duplicate work, adds Juha Mustonen.
– Bad data causes a whole lot of unnecessary hassle, summarizes Emmi Alminoja.
Similarly, emissions calculation cannot be performed if the necessary and correct basic data required for it is missing.
Speaking the customer’s language, meeting the customer’s needs
Even consulting companies don’t always provide the kind of help companies actually need for their data management issues. The Neuvolab team has encountered its share of skepticism. Some clients have expected “yet another consultant” who speaks complicated jargon and leaves behind an even bigger mess.
Skeptical customers have been pleasantly surprised.
– We know how to solve data management problems, and we know how to explain things in a clear way. We can say: when your orders often run late, it’s because of this and that. Let’s fix this part of your system, and things will start running smoothly, explains Onnela.
– We explain things in a way the customer understands, adds Mustonen.
Everything starts with the customer’s needs. The Neuvolab team has seen industrial business operations from many angles and can tailor solutions to each customer’s unique situation. And the customer is never left alone with the work.
- We don’t just tell the customer to fill in a spreadsheet — we guide them on where to find the information and how to record it, says Lehti.
When Neuvolab’s work is done, the customer’s data management structures function as they should: enabling the business, not slowing it down.-management structures function as they should: enabling the business, not slowing it down.
What does well‑functioning master data include?
Take a look at the diagram to see the quality dimensions of a company’s master data. When all these dimensions are in order, the supply chain runs smoothly without being held up by faulty data. The example in the diagram is a car tire.
Rationality
Data follows business rules.
The tire’s weight is given in kilograms with one decimal place.
Timeliness
The data is available when it is needed.
The tire’s weight is available when the delivery is being scheduled.
Completeness
All records exist, and all required fields are filled in.
There is a field for the tire’s weight, and it is filled in.
Consistency
All records exist, and all required fields are filled in.
There is a field for the tire’s weight, and it is filled in.
Uniqueness
There are no duplicate records.
A specific tire appears in the systems under only one
item ID.
Accuracy
Data is correct.
The tire’s weight is correct and, if necessary, verified by weighing.