Tuesday 9 October 2018

Business Intelligence is a Service (Pt. 1)

I am back, sort of. I continue to struggle with some very large blind spots on the right side of my field of vision. The doctors I have seen are still working together to try and figure it all out, and I have some follow ups remaining with additional specialists. But enough about that, let's talk about service.

Too often in my career, I have arrived at a new project, a new company, or a new position and found one of two major cultural issues that at once perplex and infuriate me. The first is a company that claims themselves as data driven, and treats data as an afterthought instead of an asset. The second, and in my opinion worse of the two, is a company or department culture that hoards data, and treats the release of data and intelligence as a gilded prize that only the select few could ever be allowed.

I want to address these, and I will circle back in the follow up post about data driven culture, and what that means to me. For now, I want to talk about data as a service.

Data is generated every second of every day in a company. A portion of the data is directly perceived as data, be it from an ERP or other enterprise application, or a software that collects and reports data, or even just the daily record keeping. However, in addition to these obvious and structured sources, there are also the unobvious sources, such as building automation controls, wi-fi tracking, emails (so many emails), phone queues, MDM trackers, and all sorts of other methods of collecting and storing data. These other areas of data are no less sources, and no less important, they just lack the direct correlation to the business processes for users.

Providing the data from any and all sources is the primary function of Business Intelligence, and it should always be thought of as a service. We provide a service to the organization and to the business users. In order to remain in the mindset of providing a service, the first step is to take away the concept that you, as a business intelligence professional, personally own the data, the analysis, or any of the reporting objects you have created. I have alluded to this before in my post on deferred ownership, and the reasons I use this method.

Next up, is to stop and listen. Listen carefully and closely to the needs of the organization, through the business users. Requirements gathering to build new reports, to provide new intelligence, to create new dashboards: that is where we separate ourselves. We need to be attentive, to listen, and to be prepared. Understand their context, their needs and beyond that, what it is they are trying to accomplish. That is where your expertise in the data will shine.

Ask your users for feedback constantly. As I have stated numerous times in past posts, we need the users to be involved in the entire process. They need to feel that they are a part of all decision making that affects them, and that they are in control. If they want pie charts, use pie charts. Perhaps explain to them alternatives or options because pie charts are not great for anything, but use them if they are what is requested. This is not your report; it belongs to them, and they will be accountable for it.

On that last thought though, I have never expected my business users to understand the nuances of data structures, entities, attributes, data modelling; heck, I could care less if they understand basic regression. I want them to understand their business, and to be able to tell me how they understand their business. I do not need them to dictate what to report, I need them to communicate to me how they manage their business, their people, and the processes. I can then translate that into the technical needs. If someone happens to be technically inclined, I will still steer them to describe the business first, and then their technical understanding.

Without much more further ado, the advice I offer today, in no uncertain terms, is this: Change the way you provide intelligence. Provide data as a service, and follow all the tenets of customer service in doing so. Provide data platforms as a service, reports as a service, analysis as a service, and don’t build anything for your users if you cannot give up ownership.

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