Analytics

Video: Finding better ways to
diagnose why your metrics are changing

By Grant Shirk - December 23, 2019

Over the past year, many businesses trying to be more data-driven have painted themselves into a corner. Not only are they collecting more data than ever before, but our data sets are starting to grow wider faster than they’re getting deeper. And that makes them very hard to use.

So, while it feels like we should be in a golden age of data, the tools we’re using for analysis haven’t kept up – or they’re trying to solve the wrong problem. We need to make the shift from “how do we access our data” to “why are changes in our metrics happening?” but our tools are getting in the way.

Most companies today don’t need predictions. They need better diagnosis of what’s happening, now. Particularly in fast-moving consumer businesses where products, preferences, and buying behaviors shift constantly, it’s more important to get fast facts about why key metrics like revenue, average order value, and customer conversion rates are changing on a daily and weekly basis.

From that viewpoint, BI teams have the potential to transform these rich, wide data sets into a competitive asset. The best analytics teams we’ve spoken with are investing in tools to help augment and accelerate the diagnostic process to answer questions more quickly and comprehensively than ever before.

Think about it this way – when you bridge the gap between the accessibility of this data and the way it’s used to drive everyday decisions, you can stop spending your day building dashboards and custom reports and focus instead on understanding the most important questions behind your business: answering “why” metrics are changing, as quickly as possible.

There are new advances in operational analytics and data exploration that are purpose built for these new, wide, and rich data sets. Our advice is to find one that can help you deliver precise, comprehensive diagnoses of your most important KPIs in a proactive way.

When you do that, you’ll spend less of your time doing rote work – slicing and dicing data manually – and more time doing the rogue thinking that will move your company forward.


Read more

Three Takeaways from SysML 2019:
More Data, Better Tools, Accessible Models

Reflecting on the research and discussions at SysML 2019, program committee member Peter Bailis shares his observations on three emerging trends.

Read more

Why Everyone Needs a Dedicated Analyst Team

With the investment we’re making in collecting structured data, everyone could benefit from a dedicated analyst team. But almost nobody does. Sisu can help

Read more