A minor step towards becoming insights driven
These days I tend to hear a lot of: "We want to become a data driven company". What people normally mean when saying that after doing some digging, is to leverage data to improve operations and customer experience and faster time to insight. There is really no simple answer and overnight cure, on how to achieve that change. It's a journey, and be prepared, it will take time. And in the time we are in now, it's honestly more cruical than ever to have those insights and make fact based decisions timely - before it's too late! The other day I was playing around with AI in Power BI (without writing a single line of code) to see how for instance sentiment (positive or negative attitude towards something) on tweets with the hashtag #vaccination is changing before and after the covid19 pandemic. Are there other insights we can derive from big amounts of data laying around? For sure. What if we could somehow use data from forums, call centers to predict depression so we can take measures before it gets to bad. That's what I call meaningful use of data. And being able to turn around quickly in the moment when you need it, now that's insights driven.
To help a company become more data or insights driven (and this is one of my favorite topics btw), I would normally start with understanding the maturity of the organization and or industry as is, in terms of culture, analytics architectures, ways of working with data and analytical use cases. And also how ways of working is distributed across the organization. Not everyone prioritizes to become insights driven. Some teams might struggle more with new tools and processes than others. Some even struggle with a gap in skillsets, and harvesting data talent is not easy.... Learning new tools like Power BI is for many (or I would actually refer to it as a platform, that's what it is) easy to learn standalone, and difficult to master all the way to delivering these insights driven solutions. Power BI does also very seldom come alone, it's often part of a larger platform and ecosystem. I am a big fan of failing fast and cheap strategies for analytical development, but you also need a basic foundation to lean on before you can deliver a solution. Power BI doesn't do magic (or hehe if you ask someone else, they migh show you a magic trick or two).
Harvesting data talent is not easy...
Microsoft Power BI was yet again named a Leader in Gartner’s 2020 Magic Quadrant for Analytics and BI Platforms, read my deep dive into that here. Even better positioned than last year. And the reason for that is mainly due to partners, customers, community and a fantastic product team listening to feedback and delivering innovation at a high pace. Watch me when I say that, as we are about to go into the Virtual Business Apps Summit next week (May 6th). Great things will be revealed.
This fast pace and need to deliver quickly, also requires us to follow the developments, and continue to learn non-stop. Those learning needs to be incorporated into a larger Governance and operations model. And I would put emphasis on; The Power BI governance should be considered as part of a larger analytics / BI governance initiative, including the WHO, WHAT and HOW's. I'll expain a little bit more in the below sections (this is based on my personal experiences):
Rule Nr 1: Define the as-is and the to-be goal
- What is the strategy for the company overall and how does data culture and a BI & analytics platform fit into that picture? Is the strategy a IT-driven, thick centralized hub or a more blended hub and spoke approach leaning towards managed self-service BI? What is the overall model for governance? Strategic, tactical and operational. Tie these things together, It all will make so much more sense.
Rule nr 2: Define the WHO
- Who in the organization will have accountability for both the business side of things and the IT side of things in terms of prioritization, infrastructure, data quality, KPI definitions, glossary, catalog, training and support. Executive backing is KEY. Who is resposible to the different components of the BI and analytics platform? And who are the champions that will drive the change across the business? The data enthusiasts? Do they have sufficient SME knowledge in the WHAT's?
Rule nr 3: Define the WHAT
- What are the processes and tools that will be used to govern the different areas- and what needs to be governed? How will information needs be gathered and how will the use cases be prioritized against the strategy and effort, what components do you have in your analytics and BI platform, do you have a BI and analytics platform? What will be used for cataloging data, for communication and in the end monitoring adoption and impact?
Rule nr 4: Define the HOW
- How are you going to deliver the insights or foundations for business end to end and be able to give the opportunity for timely insights (yes you will need 1 or several cross-functional team of some sort), what's the delivery principles, how will you measure adoption and provide training and support? How will you communicate? A roadmap with small milestones along the way, quick wins in the beginning is important to get further buy in from top management. Don't create the entire platform up front. You might end up with a massive investment and no adoption.
These are the 4 key pillars as I see it, and all of the puzzle pieces below will not be covered in this post. That is more proper for a book in my opinion. But do let me know if that would be a interesting read.
If you are struggeling with any of the topics mentioned above, I'd be happy to advise!
Stay safe everyone