Accenture CIO Frank Modruson tells JOHN KENNEDY the future of economic life will be defined by a revolution in the use of analytics in organisations to know what lies ahead.
If you were to ask Google or homegrown e-commerce powerhouse Paddy Power what kind of people are most in demand at their growing operations in Dublin they will tell you: business analysts and statisticians.
According to the Analytics Institute of Ireland, there are at least 400 jobs available now in data management and mining, but the right candidates are not available to fill the roles due to a shortage of skills in this area.
“There’s potential for thousands of jobs in Ireland if we can provide enough of the key ingredient – skills. Ireland needs to become a data-friendly location attracting the analytical market leaders to base here. Creating high-calibre, well-trained analytics graduates and a vibrant analytics community is instrumental in achieving this,” explains Kevin Magee, CEO of the Analytics Institute.
The definition of business’ future
If you ask Accenture CIO Frank Modruson, a man responsible for defining the IT needs of a global workforce of 217,000 people, he would tell you that the future of business will be defined by analytics.
To cap that, Accenture this week opened a 100-job research and innovation centre in Dublin and its role will involve advanced statistical modelling for companies and governments.
The jobs will be aimed at graduates to PhD-level candidates who have analytical and statistics experience. Predictive analytics – until now known as business intelligence – applies advanced statistical modelling techniques to internal and external data sources to generate deeper insights that help businesses and governments drive better outcomes.
Modruson tells me an anecdote about how the CEO of one of the largest electricity firms in the US was asked who were his most valuable employees. “He replied: Meteorologists.” The reason? “Because they could forecast weather patterns which influenced how much that firm would spend on fuel to drive its power stations. Their forecasts were core to the business.
“The same analogy applies to almost all businesses and governments going forward. Predictive analytics is going to be one of the dominant forces in IT in the next to near future.”
As he says this, I can’t help but wonder if any of the Irish banks or State officials made any use of business intelligence technology and if this might have helped offset the overheating of the Irish economy.
Returning to the analogy of the utilities firm in the US, Modruson explains: “You need to be careful with the level of certainty because prediction or forecasting by its very nature will have some level of imprecision to it, but you need to start somewhere and you need to be looking into the future.
“The further out you look, the less precise things can be, but, in terms of productivity, knowing, for example, what the climate is going to be and what the weather will be like has an impression on the use of power and by working closely with the guys who buy and hedge fuel. You want to generate more power but do so at the lowest possible cost. That’s an example of analytics at work.”
Applying analytics
Modruson says the example could be applied across a number of industries, from shops deciding how much stock to hold in their stores, governments making budget decisions about their economy to banks making credit decisions. The key is gathering the right data from a variety of sources and letting the technology do the rest.
He foresees a time when analytical technology or business intelligence will be in the hands of all businesses, large or small.
“I think the technology is becoming more in reach. It’s fundamentally hard to figure out what’s ahead but if you can actually work on the data that your firm or organisation gathers and construct a data model around it, you can then figure out a realistic prediction.
“I see the potential but I can also see how it can go off the rails. The key is in how you gather the right data.”
In the past, business intelligence systems were known as management dashboards that told senior bosses the state of health of their organisation in real-time. Now the future is real-time information with as likely as possible predictions of future outcomes.
“The hard part is making sure you gather the right data, but the benefits are potentially huge for the business world. These are not slam-dunks but something you really do need to think about. It’s sophisticated and you need to get it right. It’s not just about buying analytical software but you need to really understand your business and the nature of the core data that is being collected.”
For governments, Modruson says there’s not enough forecasting around the level of services that will be needed in areas like healthcare, for example. He points to the Revenue Commissioners in Ireland, which is putting in place analytical systems to make judgments on tax collection.
“Knowing what’s in the pipeline means you can make better decisions about the resources you need to handle situations.”
Financial Times‘ use of analytics
Newspapers such as The Financial Times have been using analytics to define their mobile and web strategies and as a result are leading the media industries with their paid content strategies.
Accenture’s executive director of strategy and enterprise analytics worldwide is Irishman Brian McCarthy. He explains that the new analytics centre in Dublin is part of a global set of innovation centres the consultancy firm is setting up to develop the next generation of analytics technologies.
“The analytics revolution is widespread and is developing in surprising ways. It’s business intelligence but more dynamic real-time information about your organisation’s performance.
“Once it was about telling me what’s happening, but now new sophisticated data modelling technologies will tell me what’s going to happen. In terms of management science, this is effectively about better information to make sharper decisions.
“For example, retailers can decide stock levels of certain products based on various factors, from weather to consumer sentiment, economic conditions, demographics in certain areas and spending power. They can then ask themselves what services and promotions they want to wrap around products, assess the kind of uplift this will mean in terms of the bottom line and be more predictive about revenue and margins.
“They can also find out for themselves why a promotion in stores didn’t work. Was it because of a supply chain issue, was it because the sales force didn’t engage with the customers or was it a competitive issue?
“The key is being targeted with the kind of information you need to make decisions on a daily, weekly or monthly basis by narrowing it down to the 10 or 20 key pieces of information and where it sits – on the web, on social networks, in your stores or somewhere else within the four walls of your business,” McCarthy adds.
