Where to start with a data project

The data and analytics domain, like all technology-related topics, is littered with an ever growing collection of buzzwords and jargon, often misused and misunderstood.

These buzzwords define the membership of the “data” community, and give that community an easy way to discuss complex ideas, but prevent progress and innovation for some organisations. Innovation is dependent on the exchange of ideas. If experts can’t give non-experts a basic understanding, and critically, an explanation that translates into business terms, they fundamentally stop that exchange. This in turn, can cease appetite for investment.

Of course, there are organisations where decision makers might associate the jargon in marketing messages with credibility. Those decision makers might take the view that the answer is simply to put a reporting technology in, and success will come out the other end. This approach also prevents progress, because ultimately the conditions for success aren’t created and the value is never delivered.

Then we have the more fragmented organisations, where collaboration isn’t a natural feature; in this case, how does a data project start without it immediately being owned and directed by a single function or business area, and at risk of being one of many siloed attempts that will ultimately never be joined-up?

It can be daunting for organisations looking to progress data and analytics initiatives, when they are unclear on the first step, let alone the steps following.

Begin with the end in mind

If there is a view in an organisation that value, not yet realised, could be derived from the data it holds, or could gather, then a motivation exists.

This motivation must be used to drive an urgency within the organisation, and to build a coalition; a collection of cross-functional, cross-discipline, like-minded individuals with the commitment and influence to initiate a call to action.

This coalition must work to the premise that the probability of success will increase by clearly defining a vision of the end solution. But to do that they must take sufficient time to, identify a business “data” problem to be solved (perhaps a required insight), develop hypothesis for how it will be solved, and define how they will know when it is solved.

This vision is not an all-encompassing data and information strategy (although that will be necessary when a certain level of maturity is reached). It is a small visionary statement of the end solution to solve a single problem identified. First ventures into data and analytics should be small, manageable projects, each of which adds value to the organisation, enabling the next, and building momentum.

The vision should be communicated, to inspire, clarify, and focus efforts. It should be simple, short, engaging, and jargon-free. This is the exchange of ideas. It should provide an explanation of how the business “data” problem will be solved, and it should translate clearly into business terms and benefits.

Remove barriers

Another critical role for the coalition is to remove any barriers that prevent the necessary action to deliver the vision.

This is an iterative process. Barriers will be identified throughout the project, and they will be both technical and non-technical. For example:

• Budget
• Resistance to change
• Availability of skilled technical resources to provision a data platform and identify and access the appropriate data sources
• Data quality and accessibility (see our previous article on the primary reasons for data project failure)

Achieve short-term wins

If the project team can achieve fast and frequent deployments, measure value, and communicate that value, then the approach can be validated with feedback from users quickly. Even for a small first data project, this allows any hypothesis to be tested, and adjusted if necessary.

Repeat and review

Once a project is complete, momentum can be sustained by repeating the steps and ultimately solving the next problem. However, it is important that embedded changes are regularly reviewed, benefits measured, and success communicated frequently. This provides justification for ongoing investment, and supports a culture of continuous improvement.

For advice and support on data, analytics, reporting, and business intelligence, visit us at Endpoint Tech