10 months of data and tech: Insights from my journey

By Andy Jackson

When something’s not as important as other stuff, it’s really easy to discount it – “it’s not on my radar; ergo, it’s not something I need to worry about”.

Then every so often something smacks you in the face and you end up re-evaluating your life choices. Ok, so maybe not to that extreme, but those ‘Oh yeah…of course!!’ moments can, at the very least add a different layer of understanding that affects the way you see things.

In my case, it was joining DATA³.

10 months in and I see the world of organisational effectiveness through another lens. It’s not a new lens, it’s always been there, but now I’m firmly in the tech/data world and that extra layer of understanding has given me a new perspective.

I now firmly recognise that data – and its utilisation through various products, tools, techniques and platforms – is a key part of the revolution we’re currently experiencing.

The BIG picture

According to a report by McKinsey: What is industry 4.0 and the Fourth Industrial Revolution? The 4IR is building on the inventions of the 3rd (computers, micro-electronics the internet etc).

“These inventions are being developed beyond the previous realm of possibility with four foundational types of disruptive technologies (examples below) that can be applied all along the value chain:

1. Connectivity, data and computational power: cloud technology, the Internet, blockchain, sensors.

2. Analytics and intelligence: advanced analytics, machine learning, artificial intelligence.

3. Human–machine interaction: virtual reality (VR) and augmented reality (AR), robotics and automation, and autonomous guided vehicles.

4. Advanced engineering: additive manufacturing (such as, 3-D printing), renewable energy, nanoparticles.

Yes people … we’re in it, and it’s moving faster and faster.

The more ‘immediate’ picture

… is that there’s a mahoosive opportunity to accelerate the growth of our businesses by taking advantage of the innovations in data, data software and AI. It’s phenomenal the kind of insights that can be gleaned from the data that’s generated from a business’s data – financial, marketing, website engagement, customer relationship management, sales etc.

The problem is that each of these functional areas will have its own software, platform and/or spreadsheet (because who doesn’t love a spreadsheet!) that will often be completely disparate and disconnected from each other. This WILL result in inaccurate or conflicting data which at best results in a delay in say, being able to publish a report but at worst, the information could be used to inform a strategic decision. Not good.

The impact on AI implementation

The quality of a data environment is particularly relevant if considering exploit analytics and intelligence (No 2 in the 4IR list above). Any kind of AI will only be an effective tool if the environment it has access to has the right architecture and the data stored within is of good quality and managed effectively.

And then, the quality of the information an AI might present to you, will be influenced by two things:

1. The specificity of the question that is being asked.

2. The quality of the data being accessed.

Imagine being given exclusive access to a particular library and wanting the answer to a specific question. The librarian can head off and look for the information you need, but what if …

  • The book they need hasn’t been categorised correctly and has been placed on a shelf in a different part of the building?
  • What if the information is in a section that needs special access that hasn’t been granted or isn’t available for this particular person?
  • What if the information being accessed isn’t the most up to date version or conflicts with information in a different source?

Most businesses are in their infancy when it comes to data and being able to establish, develop and utilise mature data systems and processes. In fact, it can be said that most of the business world is still finding its way when it comes to data. Some organisations are rockin’ it … but most still have a fair distance to travel to be able to say they’ve reached Data Maturity.

Interested in knowing your Data Maturity Score? Take our free assessment here.