Data, information, noise and …
not seeing the trees for the forest!
Today everyone has understood how important it is to collect and process all types of data, even in large quantities, and to store them for current or future evaluations. Storage space is cheap and there is enough data in every business process … But what then?
How to avoid “DRIP”?
We are increasingly seeing the problem that companies are rich in data but remain poor in information. An experience known as DRIP (“data rich, information poor”). Despite extensive data collections, it remains difficult in many companies to derive real benefits from it.
Intelligent data analysis is
the key to success!
Professional data analysts can handle artificial intelligence (AI) methods well and can use machine learning to identify influences and their effects. But that is only “half the battle”, because the lack of experience with wholesale and retail processes did not let them experience the “typical errors” that first reveal how and which “noise” has to be filtered from available data in order to gain actual knowledge and added value …
Forecasting is only the first step
When using AI methods, the focus is often on demand forecasts. Data, however, cleverly collected, cleared of the “noise” and interpreted in a process-oriented manner, has so much more to offer. “They allow a better evaluation of the movement of goods and receiving information, the optimization of order strategies, the planning and forecasting of promotions (events). Cleansed data ensures automation, provides strategic information for management and helps to check decisions in advance and to plan better, to simulate influences more precisely and to monitor results.