A major challenge for businesses undergoing their essential digital transformation is deciding how they deal with the deluge of data that is an inevitable part of the evolution process.
Today’s digital engagement with customers across multiple platforms produces unprecedented volumes of information and there is a fear that having to deal with this tidal wave of data can be more of a liability than an opportunity.
But here’s the good news: the rise of “big data” and the analytics that go along with it shouldn’t be seen as a resource-sapping grind necessary to simply stay on top of what your customers’ needs are and monitor how well you’re delivering them.
Instead, consider the data deluge a catalyst for change that has the potential to generate new ways of thinking about and understanding your place in the market, and creating growth and value for customers.
Here are five truths about the role that data and analytics are playing in digital transformation, and the opportunities they bring with them.
1. Thanks to the cloud, data disruption is inevitable
Dealing with data used to be easier: businesses would simply capture and corral it in “data warehouses”. But as Klipfolio reminds us, more than half of the data being analysed today is housed in hundreds of cloud applications and data sources.
This phenomenon – part of the wider, inevitable migration to cloud services – shouldn’t be feared, however, because using the cloud offers advantages of agility and scalability.
But it does require a mindset change when considering the role and scope of data analytics, and what it can deliver for your business.
2. Business Intelligence is just the start of the journey
I’ve previously explored the benefits of cloud-based business intelligence solutions, but they are just the start of harnessing the full potential of big data analytics.
The 2005 best-selling book Freakonomics heralded the “belief that the modern world, despite a great deal of complexity and downright deceit, is not impenetrable, is not unknowable, and – if the right questions are asked – is even more intriguing than we think. All it takes is a new way of looking at things.”
With big data now so widely available and distributed via the cloud, the question arises as to whether BI’s focus is too much focused on what we know, rather than what we don’t know.
As far back as March 2016, Gartner was saying that the previously-lauded concept of the “business intelligence competency centre” had been superseded by evolving science, technologies and skill sets.
The BI landscape is continuing to change, Gartner says, with all kinds of more predictive and prescriptive analytics becoming popular.
This opens up further opportunities for businesses to gain insights from their growing volumes of data.
3. Analytics is evolving from ‘hindsight’ to ‘foresight’
The real value of data and analytics is that it enables businesses to see things in a different light.
Gartner has an analytics maturity model. This sets out how value is added as we move from descriptive analytics (“what happened?”) through diagnostic analytics (why did it happen?”), predictive analytics (“what will happen?”) and ultimately prescriptive analytics (“how can we make it happen?”). In other words, a model of evolution from hindsight, through to insight, and on to foresight.
The traditional BI approach takes in the descriptive or “what happened?” stage, so you can see there is a great deal more on offer by mining big data.
Imagine the potential for unleashing business growth and competitive advantages once analysis of your data is able to deliver predictive and prescriptive solutions at the foresight end of the spectrum.
4. Be prepared to leave your comfort zone
While the potential is huge, the journey to foresight through data will be a challenging one, and will most likely involve significant corporate disruption.
That disruption is likely to involve opening up the digital flood gates even further to gather more data and then digging deep to find anomalies.
You will need to be prepared to be proved wrong in your business plans and projections by the insights and foresights the analysis reveals. That’s fine because failure is your friend, as long as you fail fast.
You’ll also have to be ready to get out of your comfort zone in order to extract real value from your data. Look at raw data, don’t normalise it or clean it – you need the raw material to eke out the best results.
Using data and analytics to move on from a state of “we don’t know what we don’t know” to “knowing what we don’t know” involves taking a fresh perspective. Don’t gather data with the aim of justifying where your business fits. Instead, use analysis to find out where you don’t fit, so you can identify opportunities.
Don’t make assumptions about how your customers or potential customers behave, and step outside the context of the business to get a fresh perspective.
5. Let the machines do their thing
Fortunately, finding that fresh perspective has become possible thanks to artificial intelligence and machine learning – although there is a catch to be aware of.
Machines don’t learn the same way we do and they don’t start with our preconceived ideas, so in theory it should be possible to generate insights and foresights that are not tainted by our conscious or unconscious biases.
But studies are finding it’s easy for human biases to slip into AI models and when it comes to business analytics this is something it’s important to avoid, otherwise we risk missing out on the invaluable growth and transformational opportunities available through deep analysis of our data.
Learn more about the power of data and analytics
Want to learn more about where data and analytics are heading, and how your business can benefit from these developments?
An ideal place to start with our forthcoming event, Data and the Digital Future, proudly presented by us at Dynamo6 in association with Amazon Web Services (AWS). This event brings together a range of technology leaders who will use real business examples as they share their knowledge and experience around digital transformation and the power of data, analytics, artificial intelligence and more.