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DATA: is it overhead or insight?

Written by Patrick Murray
Published on
When it comes to data, value is the name of the game. We headed to the AI Tech North Summit 2022 where Patrick Murray, our Head of Data Analytics and AI shared his thoughts on Implementing Real Data and AI Projects.

When it comes to data, value is the name of the game.

We headed to the AI Tech North Summit 2022 where Patrick Murray, our Head of Data Analytics and AI shared his thoughts on Implementing Real Data and AI Projects.

Watch the video, or read on for Patrick’s low down on data and AI.

When you’re implementing ‘real’ data and AI projects, the focus shouldn’t actually be on their ‘realness’. The focus should be on whether they’re right.

All data and AI projects are real. But not all of them are justifiable; despite many more businesses implementing these strategies, there’s a low percentage of those getting any benefits from them.

Thanks to the chasm

In my role as Head of Data Analytics and AI at Razor, I’ve worked with businesses of all shapes and sizes. Data and AI is no longer a tool reserved only for the finance or retail industries – we’ve found charities (and even stairlift companies!) can make use of it.

We’re quickly moving from on from early adopters of this tech to majority adopters. So, whereas early adopters are comfortable with a degree of uncertainty, majority adopters need proof of success. They need to know that adopting data and AI strategies will have a clear and demonstrable impact.

That’s the ‘chasm’ and it’s something that any new product or service needs to jump over in order to have lasting staying power. We’re not short of HYPE.

– Especially when it comes to data, AI and major breakthroughs.

But as technologists and data professionals we need to prove its value – and staying power – to the majority. Democratising and making this tech as accessible as possible is just as important as the next ‘big thing’.

That’s the why. Here’s the how:

Aim for the bullseye!

If your primary focus is to deliver value at the end of a project then every piece of data needs to add value. It needs to give you insight – it needs to be the right project.

The Trough of Disillusionment

Is the stage of a project where the initial enthusiasm has worn off.

You fall into the trough when you’ve got the right project, but you’re delivering it in the wrong way and focusing on the wrong things. It might be the ‘right’ answer, but people will lose faith in the project if you can’t provide tangible results quickly enough – impatience will derail your project.

Start at the top of the pyramid…

The aim of a data project is to turn meaningless data into something that can be used to inform and drive action.

The DIKW Pyramid shows you how you can move from data (D) to information (i), knowledge (K) and then wisdom (W). Wisdom gives you the insight to take action.

Herein lies the problem: by starting with the data (at the bottom of the pyramid) it’s easy to lose sight of your end goal. And that end goal is why you’re doing all of this in the first place.

Focus on data and you’re heading straight for the trough. That’s a really tough space to climb out of.

Start small and focused: start with the end value.

I believe you should start from the top of the pyramid instead. Start with wisdom (= actionable insight) and use that as the focal point of your project.

Frame your early conversations around value: what are you trying to solve? What are you trying to achieve? That’s your starting point.

Value really is the name of the game

It’s good to remember that it really doesn’t matter what problem you’re trying to solve.

Your solution doesn’t need to be groundbreaking. It just needs to add value to your business.

Some organisations aren’t ready to become AI driven businesses and that’s okay – AI can still play a role, even in the early days. Off the shelf tools are a great way to enrich your data and get that tangible value.

If you focus on value from Day One, you can:

Ride out the hype.

Avoid the trough and get tangible results.

And never forget that data is overrated: if you can’t use it for insight, it’s just an overhead.

If you’re not sure what kind of insights you’d get from data and AI, read our run down of 10 real-life applications of AI for your business…