Data: the fuel powering digital transformation

There are few corporates today that aren’t focused on digital transformation in some form. That transformation will take many different directions, led by core business and company strategy, but there’s one central element that is essential: DATA.

As a result, companies that aren’t already collecting, protecting and analysing their data will not survive the age of digitisation.

Why is data so important?

In most organisations, digital transformation is focused on using new technology to accelerate key processes. Artificial intelligence (AI) will play a growing role in automating a wide variety of functions – from tracking shipments as they progress along a supply chain, to instant decision-making in a manufacturing line.

But building artificial intelligence and machine learning in any form relies on vast swathes of data, acquired across a myriad systems and months or years of historical performance. Sophisticated analytical tools turn that data into rules and algorithms that give deep insight into the consequences of various actions and inputs.

Water companies, for example, will combine data on the levels in its reservoirs with weather predictions, historical patterns of demand and pressure readings in its networks to automatically deliver a steady and optimal flow of clean water to businesses and homes.

What are the possibilities?

The more data available, the more sophisticated the analysis, giving business unprecedented insight into trends and possible new directions. Many believe that AI will help companies deliver new services and experiences that have never been imagined before. Data from Accenture suggest that AI could double economic growth by 2035 and boost productivity by 40 per cent.

So organisations today should be focusing on data science and artificial intelligence capabilities. They need to change the commonly-held view that data is the output of a company’s processes, and instead see it as the fuel.

What are the obstacles?

Of course, unlocking all the data within and linking it  to your business is the challenge. And there are a number of hurdles to overcome. These include:

Resources – Data science experts are in short supply. As a relatively new discipline, data science is largely the domain of the under-30s, and so the commercial world should invest in boosting resources by attracting students into this field and retraining their existing IT employees.

Cleaning and aggregating data – with data generated from a vast range of sources, it must be processed and filtered to be useful. Part of the challenge is to create AI that can automate this process itself, to help businesses make use of proven, workable data.

Interpretation – companies must always remember that data doesn’t necessarily state the truth. It suggests what’s likely or probable. Nothing is infallible.

Can we catch up?

If reading this is causing you to worry that your organisation is behind the curve… you’re not alone. According to Gartner, 91 per cent of organisations have yet to reach a ‘transformational’ level of data maturity.

To begin your journey towards digital transformation, start considering data as the fuel. Invest in amassing and analysing your data and start building your data science capabilities. As your insight grows, your future direction will become clear.  Contact the WIL Group



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