Your organisation needs data to function efficiently, it’s a simple and undeniable fact.
Competition in business is more prevalent than it has ever been, and intelligent working is increasingly important to ensure success – We are all likely tired of the phrase ‘now more than ever’, but truthfully, there has never before been a greater need to understand the intricacies of your business for it to prosper.
How you access information, what you do with it and how you define any kind of data strategy is of paramount importance in making your business thrive, but all too many times this seems to be overlooked, or not given the level of attention it deserves.
We can talk data governance, repeatability, security, accuracy and usage in great detail, and these are of course hugely important factors in your information journey, but there are also some basic fundamentals that are often ignored, and which have a huge influence on how your business operates……
What, why and how?
Data-driven projects frequently start with a ‘what do we have now’ approach, with each business unit in a company being asked to capture all of their existing reporting needs, then to add any potential data needs that they may think will be required in the future.
The net outcome of this is usually a huge and cumbersome requirement specification covering a vast amount of data and diverse requirements across the business, but without any real thought about why the information is required in the first place. How often in your organisation do you hear of a process being in place because ‘That’s how we have always done it’?
All companies are guilty of this, and it is an easy trap to fall into – Innovation in data and its usage needs greenfield thinking to drive the intelligence that we all strive for in our ‘Business intelligence’ and data-driven world.
This is where the ‘what, why and how’ aspect comes into play – A top-down methodology to capture needs, accept their usage and derive their viability, based on the following principles:
Put simply, ‘what questions are you trying to answer’ is the fundamental start point for a data project or strategy.
For example, instead of ‘I have a report I need to replicate’ ask yourself what question or questions do I need to answer to support the needs of the business. This approach forces fresh thinking and allows for compilation of a top-level requirement specification driven by innovative thinking instead of blindly replicating legacy needs.
Once requirements have been captured, a justification on ‘why’ is a vital step to ensure that there is a benefit to your business. This is not to say that you should be overly selective, quite the opposite!
Reviewing your requirement will trigger further thought on your business needs and more often than not, will add to them. This should also be used as a convenient point to introduce some prioritisation using the MoSCoW principal (or similar)
This is the more technical piece of the puzzle – Working out the ‘how’ side of fulfilling your needs. It goes without saying that you will of course need data to be present in your systems in order to be able to make use of it, but it is key to ensure that data vs usage is defined so that you have a single version of the truth across your data estate.
For example, how do you define ‘margin’ does it differ by business area, is it a single definition – Are there multiple versions of ‘date’ that you need to use etc.
The result of this work should be a data dictionary and definition specification that is published to your business and maintained at all times – It will be for all intents and purposes, the overall definition of your business data.
The above steps will result in documented and prioritised business needs with a supporting data usage definition, which should form the starting point for a comprehensive data strategy.
Where you go from this stage dovetails into the various factors that were mentioned earlier in this article – Data governance, Repeatability, Security and Accuracy.
The governance side of things we have touched upon in the ‘How’ element of ‘What, Why and How’, as from the outset your business should be focused on clear definition and usage of data, however please reference our previous blogs on ‘Why Data Governance Before BI’ and ‘How to mitigate against self-service polluting data’ for some deeper insight.
Repeatability, Security and Accuracy go hand in hand with Governance, all pushing toward provision of truly trusted data and the single point of truth that we should all strive for within our organisations, but is this too much for most organisations to take on alone, or without dedicated resources?
Potentially yes – definition of ‘What and Why’ is something that each individual business must articulate (with or without external assistance) as this is the foundation from which to build, however, the ‘How’ and all that comes after will, more often than not, be better served by introducing a third-party specialist.
Our blog ‘BI and Data warehouse – Why wouldn’t you’ highlights why this may be a prudent move for your business and how it can fast track your data-driven project, whilst maintaining all the best practice elements that you would enforce during a well-controlled internal project.
Hopefully this gives you some food for thought – In essence data-driven projects and strategy are complex undertakings that need to focus on planning and execution, but taking a step back and giving consideration to the multiple facets required will allow you to better understand how to derive innovation and value from your business information, likewise you don’t need to undertake the journey alone.
At PrecisionPoint, we are experts in delivering data solution to the Dynamics ERP community, why not reach out to see how we may be able to help your organisation unlock true business intelligence…
PrecisionPoint – Where data becomes trusted insight