While I have no idea if anyone is silly enough to call them the 'good old days,' I remember the beginning of using technology for widespread analytics in business back in the late 1990s. Armed with Excel, I put together big, complex spreadsheets. I used what felt like a magical programming language (VBA for all the Office nerds like me) to help create and automate analytics and reports. I was able to do reporting in a way that by today's standards might be kludgy but seemed ground-breaking at the time.
Today, we are light-years ahead of those times. I can use Power BI and other tools to do analytics for an organization that automates the connection of data sources and enables advanced analytics with relative ease. I can bring together data from across the enterprise and serve it up where and when needed. I can do real-time analytics on a volume of data that would make the old Excel cry.
Yet to this day, most organizations are still dependent primarily on older, outdated reporting tools for their analytics. Again and again, when I talk to organizations about their reporting needs, they plop an Excel workbook in front of me and tell me to rebuild it exactly.
Modern BI tools do not just improve on the older options for business analytics. Power BI is not Excel 2.0. Businesses need to think differently.
Modern BI tools redefine what business analytics can do to the extent that businesses need to approach things in a whole new way.
Modern BI tools use a data model. The old way used a data set: This changes everything. Over the decades, I have seen thousands of Excel spreadsheets. For a super-majority of them, the data used either lived in a single sheet as a dataset or in multiple data sets across multiple sheets. Modern BI tools do things differently. The data model defines how the data comes together. Building a suitable data model is critical for success.
The old way risked everyone telling a different truth. I can't recall the number of times I've heard organizations say that the number one problem they have is everyone having different numbers. People often show up with different Excel sheets, telling a different story. A well designed, modern BI solution gets rid of this problem.
Modern BI tools keep the data always fresh. What does it mean to go from manually updated files to a fully automated process where the data does not ever have to go stale? It means that updating data is no longer painful and cumbersome, unlike with Excel. And gone are the 'one and done’ days of creating a report only to have it never be updated again.
Data model control resides with experts, but SMEs control the analytics. Subject Matter Experts (SMEs) in the business know what they want to analyze. But the art and science of preparing data are not for everyone. But in the old model, either the SMEs were left to fend for themselves, or they had to wait for their data to pull from the keepers of the data warehouse. Modern BI lets the professionals prep the data model, allowing the SMEs to focus on what they do best - solving business problems.
This is incredibly exciting stuff! With proper use of Power BI, data-driven decision-making becomes a reality. This is true digital transformation. But it comes at a cost. In this case, the need to think strategically is critically important. The 5th way that modern BI tools are different is the following.
With modern BI tools, ignoring strategy can ruin everything. There is no way to overstate this. In the old, ad-hoc environment, BI or analytics strategy was pretty much ignored. With no ability to enforce controls, what is the use of strategy? But with Power BI, organizations need to take a strategy-first approach. And luckily, Cambay is here to help.
It occurs to me that maybe part of the challenge for organizations is that many are unsure in their understanding of BI. Here is my current working definition of Business Intelligence:
Business Intelligence uses KPIs, visualizations, metrics, and analytics to address impactful business problems in a way that lets people in organizations take meaningful action. Using clean (enough) and trusted data, BI enables organizations to address their most important problems to engage in continuous, intelligent transformation.
Is it a perfect definition? I don't think such a thing exists.
But it is pretty good and feels as accurate as I can get. Bonus points to anyone that noticed the missing keyword - reports! My working definition of BI is not focused on reporting. The report is just the vehicle for continuous, intelligent transformation.
Why is this important? Built into the very definition is an emphasis on taking action to address critical problems. In other words, any discussion of BI strategy needs to focus on how it can dramatically benefit real issues. Anything less is just reporting.
So, what does BI strategy look like? I have spent many years helping organizations with this question. The result of all this work is the Cambay BI Strategic Lens. Think of it as a strategic planning process for intelligence and analytics.
Picture this. An organization has never done any real road mapping or strategic work to approach BI. They have many big, tabular reports (think Crystal Reports or SSRS) and Excel files, and they have tested some modern BI solutions such as Power BI. They have data they want to report on in various systems such as Azure, SalesForce.com, SAP, and others. And they have people doing report writing across the entire organization. This kind of setup can feel out of control. But with the BI Strategic Lens, we can bring it all into focus. Here's how.
When done, organizations have a way to focus their energy and efforts. That is why we call this process the Strategic Lens. It is about ensuring focus and clarity, driving impacts, and maximizing return for every dollar spent on BI.
Hopefully you see the value of BI strategy and why it so important to accelerate digital transformation. Want to learn more? If so, please talk to our BI experts at Cambay to see if it’s right for your organization.
Vice President of Strategic Business Analytics