To some use of the word ‘data’ signals the beginning of one of the most boring, technically esoteric and generally useless topics of discussion they can imagine. Data model, data dictionary, data schema, data cleansing, data coding & classification…. or just plain old data.

HELP! How much boredom and technophobia can one person be expected to cope with! Can’t those sad techie’s keep all that gobbledy-gook stuff to themselves and just talk to the rest of us about normal business things?

Oh dear, a response common to many technophobes we know. We even have some sympathy for this perspective. However, we also know from hard experience that the technophobes are dead wrong to place this conversation on one of the lower rungs of technical hell.

Unfortunately, although we’d never claim the topic was scintillating to most listeners, we know how fundamentally important good data is to modern organisations. It is not too much of an exaggeration to say that without it they are lost with little hope of rescue!

You see, business processes, functions, workflows, metrics, org charts, etc, etc change quite regularly… sometimes at the whim of a passing management fad. Where-as base data on the other hand generally changes relatively little on the whole… while underpinning all the rest of the faster changing artefacts that rest on top of it.

To understand this, while trying to avoid the more technical aspects, it is useful to think of (business) data as being split into three camps: meta data, static data and dynamic data.

Meta data is simply data about data. This camp covers such things as should data be ten digits long or fifteen digits long. Should it be numeric or alpha-numeric. Should it use an existing classification system (e.g. NATO schema) to group and relate items or one you invent for yourself. These basic decisions underpin every data structure (e.g. database) ever devised and are essential to being able to speak a common data ‘language’ that uses consistent definitions and formats.

A very common business example of meta data is the structuring of an organisation’s financial chart of accounts… i.e. what locations and functions, what departmental / budget codes, what time periods, what currency, what consolidation roll-up, what accounting standards, etc.

Look more widely and you will also see that the concept of  data hkan invoice, an order, a requisition, a product, a part and many, many other familiar business artefacts are also meta data entities. That is, an object or item with an understood set of data attributes and rules that define and specify it and its relationship to other data entities. In fact, a map of such things is known as an entity relationship diagram or data schema!

Once the basic data entity building blocks are defined, for both operational and maintenance purposes, they are often then divided into two further camps… static data and dynamic data.

Static data, as the name implies is data that either does not change, or more typically, changes relatively infrequently. Into this camp we can place data items such as products, customers, suppliers, BOMs, routings, etc. It is not that these data items never change, but that once created they commonly change little and infrequently… for some organisations, sometimes verging on never… which can be a problem in and of itself!

Finally, we have the camp of dynamic data. As this name implies this is data that changes fairly frequently. Into this camp we can place data items such as quotes, orders, requisitions, GRNs, invoices, etc. These items by definition change regularly as part of the normal cycle and rhythm of conducting business.