Death by Data Your business can't afford a digital detox, but here's how to avoid death by data

Most business leaders I speak to have a complicated relationship with data. They know data is an essential tool in making the right decisions at the right time, but which data? Where once business leaders were desperate for more data, today they're in danger of being buried by it. And too much data analysis, they say, leads to decision paralysis — much like endlessly scrolling through Netflix, unable to pick a movie because of too many options.

The problem is that businesses need to have uncomplicated relationships with data to succeed. While we can sign ourselves up for digital detox retreats in off-grid cabins, putting your business on a digital detox would not benefit anyone's mental wellbeing (or the bottom line). We can't just bemoan information overload and wish for simpler times – data is everywhere and it isn't going anywhere. We need to learn how to work with data skilfully and tackle the "death by data" challenge head-on.

So, how to avoid death by data?

Do the hard thinking first.
The first mistake many make is blaming the quantity of data. "How much data is too much data?" is a question I get asked a lot, but it's the wrong question to ask. It assumes that reducing the total number of data points will magically give you the most important data you need. Spoiler alert: it won't.

Actually, the first two questions you need to ask yourself are:

1. What business decisions do I need to make?

2. Can data help me make them?

You need to understand what your business priorities are before you start bringing in the data. It takes more time to think through, but being clear about exactly what questions you need answers to will immediately narrow down the data you need to pay attention to. It's a similar process to crafting precise search queries; just as a well-defined search string yields far more relevant results on Google, being specific about your objectives provides you with much greater control over the quality and relevance of your data outputs.

Japanese professional organiser and consultant Marie Kondo famously asks people if an item in their home sparks joy – if the answer is no, she wants you to chuck it out! Well, I say – does your data answer the question you need it to answer? If not, chuck it out! Knowing what you really need gives you a way to filter out the rest. There will always be more data to look at; you need to feel confident in knowing what data actually matters to you.

Know your audience.
Not all data is created equal for every person. What's vital for a Chief Human Resource Officer (CHRO) probably won't be as essential for a Chief Financial Officer (CFO), so you need to make sure data shared is actually relevant to the audience it's going to. You often see enormous weekly/monthly reports get sent to far too many people; they're tough to digest and everyone reading them is looking for something different.

If you spend the time really thinking through what data is helpful to what teams, you'll almost immediately cut back a lot of the unnecessary data noise for those teams, whilst still making sure they have the core information they need.

Don't over-rely on artificial intelligence.
Artificial intelligence (A has huge potential to automate data capture and streamline data analysis; no one is denying this. But it should not be seen as a silver bullet to for businesses looking to improve their data strategies.

The easier something becomes, the greater the risk of laziness. It's tempting to 'let AI do its thing' and loosen the reins on establishing clear objectives before gathering data. A few clicks on your computer is a lot easier than a strategy meeting. But AI outputs will only ever be as good as their inputs; you need as much clarity as possible about how data can support your organisation before you bring AI into the equation. Automating before strategising rarely ends well.

Data done right – the essentials
The irony of providing more information about how to avoid information overwhelm is not lost on me. But this is the time where most businesses are reflecting on learnings from the past year and what they'll do differently going into the new year – I'd argue reviewing your data strategy should be a priority.

If you're fed up with sifting through streams of data reports you know are important but can't wrap your head around, my advice would be to take a step back and forget about the data for a minute. Get your big picture priorities and objectives in place first, then bring in technology experts (internal or external) to identify how best you can use data to measure your success in achieving them.

The value of data is clear; so is its capacity to swamp us. The best way to avoid that overwhelm is to be disciplined in how you capture data to start with and crystal clear on what data is of real value for you. Neither can be achieved without doing the hard thinking first.