Know What? So What? Now What?
Know What? So What? Now What?

Written by: Phil Husbands

My core interests and specialist expertise are in enterprise data strategy, data capability development and data-driven organisational change. My work focuses on building the operational and people-focused capabilities, which are essential for ensuring that data enables businesses to work more effectively, make better decisions and achieve their goals.

Know What? So What? Now What?

“Why do we have so many dashboards that so few people actually use? Why is it so hard to get people to use analytics properly? Why do so many people just want to export a spreadsheet? Why do our KPIs have so little effect on our bottom line?”

These questions are familiar to many businesses which have strived to benefit from the power of data insights.

The challenging fact that a lot of businesses experience is that sometimes people just don’t use data insights very effectively. Or when they do, they don’t in all honesty seem to have much impact. Consequently, the business becomes awash with reports, dashboards, scorecards, and analyses, and… well, everyone just ends up wondering what it’s all for.

If this sounds like your business, let me give you a simple and effective way that you can hone your data insights into the sharp instruments you were promised, rather than the blunt tools they feel like today…

First, a reality check – Data insights only deliver value when they are effectively actioned. No business actually wants reports and dashboards. What every business wants, is to achieve its goals! If your business could find some kind of supernatural way of achieving its goals without data insights, then it absolutely would, I’m sure.

The objective of data insights must not be to possess them, but to apply them. How’s this for a sobering thought – all of the substantial data investment that goes into the infrastructure, the integration, the software, and the people that’s required to turn data into insights – it’s all wasted if those insights aren’t acted upon. But how much focus do most businesses actually put on that vital last step? Many businesses govern their data quality, but how many govern their data outcomes?

But enough about the problem. If you boil it down, you’ll find there’s just three possible causes to unactioned insights. 1) Your data insights are irrelevant. 2) Your data insights are relevant, but people don’t know why. 3) Your data insights are relevant and people do know why, but they don’t know how to action them.

There’s a number of things you can do to fix this trio of troubles. One hugely effective thing you can do, is devise and use a data insights architecture. Learn more about that and see an example here.

But I said I’d give you a simple and effective solution now, so here it is… Memorise this phrase: ‘Know what? So what? Now what?’.

I’ve been indoctrinating businesses with that phrase for years. It’s a quick three-part test which ensures that data insights are always created to be relevant, understood, and actioned. It works by asking these three key questions whenever aiming to convert data into insights…

First, look at your goals and the processes required to achieve them and ask “what must we know to ensure this process achieves the goal?”

Then, anticipate how that information must be interpreted, by asking “so what insights should we look to take away?”

Finally, think ahead to what possible actions the insights may drive you towards by anticipating “now what will we need to do?”

Know what? So what? Now what?

It’s a catchy little phase, which slips easily into a business’s vernacular and helps to ensure that no-one churns out data analysis without first really considering if it’s relevant to what’s important, if it will make sense to the right people, and if anything valuable can be done with it.

Use ‘Know what? So what? Now what?’ thinking, to constructively challenge new data insights that someone brings to the table. An essential part of being truly data-driven (and not just data-busy), is building a data culture that questions the validity and purpose of data analysis. In reality, that can often be hard to do. But by normalising this approach, it becomes a lot easier.

If you can get everyone in your business asking those three questions whenever seeking insights from data, then you’ll not only greatly improve the effectiveness of your data insights, you’ll also diminish the the amount of useless information which saunters around the place.

Now repeat after me, please… Know what? So what? Now what! 🙂

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