We Need Better Questions, Not More Answers

Slaves to our lizard brains, we spend our days answering questions that we never ask. Addicted to vanity metrics, our obsession with data is killing business insight.

We’re all delusional

Let’s face it, we’re all delusional  – some more so than others. Every day we answer a bunch of questions. Some of these are stupid, others annoying and a few that seem worthwhile spending time on. Way too much time if we’re honest about it.
What’s common about almost all these questions is that we likely never asked them. So, we spend most of our day working to answer questions that we never asked. Questions that we never decided were worthwhile answering in the first place. Sound familiar?

So why and how does this happen. Well the why is pretty straightforward. It’s our ‘lizard brain’ as Seth Godin would say. The idea that we unconsciously select tasks that are almost impossible for us to fail at. Why, well because failing doesn’t feel good. The how is simple enough to understand too – because we let it happen, in many little ways every day. We fail to decide what questions we need to ask today. A failure which relegates us to answering the unimportant questions of others.

Unchecked, this daily habit turns bit-by-bit into a deadly routine. A routine which silently infects your team’s culture and stymie’s your enterprises’ growth.

The questions we never ask

The volume of data sources in existence is growing exponentially. The range of analytics tools available to dissect data is expanding as a consequence. The market dynamics are set then to create the perfect data storm. A storm obsessed with generating an ever greater volume of answers. And for the worst possible reason, because we can.

The problem with most of these answers is that they take the form of what’s called vanity metrics. That is narrow based measures that Lauren Smith says ‘indicate improvement but are disconnected from the progress of your organisation’s mission’. Vanity metrics are heavily biased toward reinforcing what we already believe to be so. They do not challenge accepted norms and uncover real customer truths.

“Success comes from knowing what you don’t know, more than coming from what you do know.” Ray Dalio

If we are to learn from our mistakes and repeat our successes, we need to move beyond understanding simple outcomes. We need  to look deeper at the reasons why the outcome has occurred in the first place. The reality is that most of us don’t bother to forensically understand our failures and successes. We’re too busy high fiving ourselves when we do have a win to concern ourselves with figuring out how it actually happened. And when we fail, it’s more ego friendly not to revisit the subject.

We need to ask questions that help uncover the correlations that exist in the wealth of customer data that we have access to. We need a commitment to asking questions that distil this data into actionable and auditable insights.  We need to ask great questions that have the power to prove us wrong.

How to ask great questions – 3 Fundamentals

Step #1 – Agree what needs to change

State clearly what the single most important behaviour, value, or action is that you want to change about your customer? Examples include reducing customer defection (i.e. churn) or improving customer Life Time Value (LTV). Now challenge your team to tear this assumption apart. If it’s still standing at the end of this process then you know there is something of value to be questioned and explored. There are lots of frameworks available to you manage this process. Personally I’m a big fan of the Lean Methodology ‘5 Whys Tool’

Step #2 – Build a high definition picture of your customer

If you try to soldier along with a clunky fragmented view of your customer, then guess what? Any question you ask will only yield equally muddled answers. Answers which it’s impossible to act upon meaningfully. You need instead to create full visibility of your data landscape by constructing a Single Customer View [insert link https://en.wikipedia.org/wiki/Single_customer_view] across all data sources that touch your customer. There are lots of tools available which can help you do this. We like BIME analytics.

Step #3– Use Actionable Metrics

Once you have a connected view of your customer in place and clarity on the end results you want to impact – you’re ready to use actionable metrics. Actionable metrics tie specific and repeatable customer actions to observed results. So, you need to identify those actions and behaviours which if correctly measured, will accurately predict ‘change’ in the end results you want to impact. The challenge here is developing a capability to uncover and quantify the non-obvious relationships that exist between the behaviour of your customers, and distil them into Actionable Metrics.

Asking great questions about your customers empowers your enterprise to take actions that matter. To learn more, subscribe to our blog ‘insight champion’