Reality: There have never been more ways of collecting and measuring data on your business, but the real value doesn’t lie in the volume – it’s in how you use it.
With new data and analytics technologies, and forthcoming advances such as the Internet of Things (IoT), there is far more data accessible to enterprises about their products and services than ever before. The breath and detail of data is fundamentally shifting business and everyday life, says Michel Alf, Director, KPMG Enterprise.
“Everything is becoming digitised to a smaller and smaller degree, and the data opens up completely new views,” he says.
Fitbits and wearable health monitoring technology are enabling individually tailored health care; IoT is increasing the yield of crops; and content providers are analysing what their customers read, to tailor content recommendations.
“In the near future, your mobile phone or Kindle will ‘read you’ while you are reading a book, and Amazon will know which paragraphs you like and which ones you flip over. If they know what you like, they can tailor that content to you,” Alf says.
But with the ability to measure basically anything in ever-increasing detail comes a new problem: how can you discover the cutting edge insight that will help you make sound business decisions?
Brad Miller, Partner, KPMG Enterprise, says the answer is to keep focused.
“Don’t think about how much you can measure and try and do everything,” he says. “Instead, use data to prove or disprove some of your thinking, and test things. Think about what you want to know, how you want to measure it, and then generate insights.”
Before determining the insights you can glean, look at the data that is in your system and where it is coming from to ensure it is quality, Alf says.
“You need to look at the inputs of external sources and systems. These are prerequisites for actually doing something with the data,” he says.
If you don’t have a consistent methodology for data gathering, and benchmarks to compare it against, then the insights are of less value.
Miller says it is important to also understand the processes that are creating it.
“Is there something you can change at a process level to increase the value of that data?” he says.
When it comes to interpreting that data to help make decisions, start on a simple level, Alf says.
“Sometimes analysing the existing data can assist in making meaningful insights and improvements which can help finance the next level of investment.”
He says to ask: what would I like to know about my business; what do I want to know about my customer; and what I can do better?
Miller says another good question is: how much profit do I make on a customer?
“If you can answer that question by looking at your data, then that’s a good starting point, and it starts to convey what you can do with it, and you can go from there.”
Wading through spreadsheets of figures is unappealing, so thankfully modern cloud software provides easy-to-use analytics programs to suit everyone, Alf says.
“It’s easier than ever before to use these tech solutions, and there are options in every price range.”
These cloud services mean the skill set you require to interpret the data is attainable – and it is more about how clever you become at framing the right questions, Miller says.
“If you’re in retail, the question is, tell me everything about the customer. If you’re in manufacturing, it’s what efficiencies can I gain? If you have a complex supply chain, it’s how can I connect it better?
“If you move to modern cloud platforms they all have inbuilt analytics. They’ll tell you anything you want to know.”
Getting the best return on investment from data and analytics technology, and the time you take to analyse data, comes down to acting on the knowledge it offers, Alf says.
“Efficiency is on one side, and agility is on the other end of the spectrum. Mid-market enterprises have a great opportunity at the moment. They are smaller and should be able more agile, but they still need to go through this journey.”
Miller sums it up: “Fundamentally, everything is heading towards customer centricity”.
“Are you creating the right data for your business, or is there something you can change at a process level to increase the value of that data?” he says.
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