Companies experience challenges getting value from their investments in data and analytics. Large consulting companies recommend that you collaborate and connect to the business. They also recommend being innovative, agile and creative. I’d like to take a shot at providing a level of level of detail on how to achieve that.

It can be quite effective to take a step back from technology and organize the work into logical components. I have always found it very helpful to consider the following components; Data Analysis Insight Decision Feedback and Measurement. Six important components of successful data-driven decision making (3DM6). Data analyzed for insight does not have value until it impacts a decision. Feedback avoid errors and find opportunities to improve. Measuring the overall impact helps justify and manage project scope and objectives.

No rocket science there, but don’t underestimate the value of the approach because it is simple and logical. Being serious about ensuring components are present and connected, combined with keeping logic visible and working towards a state of continual improvement will help build a data culture and directly benefit customers, consumers, and suppliers of data and analytics services. It can help recognize opportunities, build the business case, scope the project and monitor implementation. It can be helpful to a C Suite who would like to create a more data-driven culture, managers responsible for delivering value beyond technology, solution architects, project managers, statisticians, data scientists etc. It can help build a data-oriented culture that is collaborative, creative, agile, and business value oriented.

I just made any claims that probably sound too good to be true? I plan to back up them up in follow up blogs as well as illustrate why this approach, while it does require some determination and belief, is not difficult to implement. Please reach out if you would like to discuss those claims directly.