How Prescriptive Analytics Can Influence The Future

Prescriptive Analytics

Yasmeen Ahmad Of Teradata Explains How Prescriptive Analytics Can Influence The Future

In sport, as in business, there is the constant interplay between marginal gains and game changing innovations.

Take the 100m freestyle swim, records have been broken year-on-year, but every so often we see not just a record broken, we see an outstanding accomplishment like Albert Vande Weghe in 1934. In one stroke he changed the nature of competitive swimming with his underwater somersault ‘Flip Turn’.

Further change followed in 1976 with the introduction of pool gutters at the Montreal Olympics, capturing excess water and resulting in less friction and faster times. The next big advance was 2008, with the advent of low friction swimwear that enabled athletes to move through the water with even greater speed.

Yasmeen Ahmad, practice partner, analytic business consulting, Teradata
Yasmeen Ahmad, practice partner, analytic business consulting, Teradata

The relevance of this story to business analytics is that just like athletes in training, data scientists make incremental improvements every day, and yet every so often comes one of those momentous, game changing innovations.

Prescriptive analytics are the catalyst

As organisations increasingly seek to drive value from historical insights, they can start predicting the future, ensuring that positive predictions are fulfilled and that negative outcomes are avoided. This is how prescriptive analytics can influence the future.

Achieving this nonetheless requires a shift away from statistical and descriptive ways of looking at data, towards considering events and interactions. Applying contextual analytics to these events and interactions allows us to investigate modes of behaviour, intentions, situations and influences.

Vast amounts of money are being spent by organisations on the creation of data ecosystems, enabling them to capture, store, and archive, large volumes of data at an unprecedented scale, in a cost efficient manner. They are responding to the headlines about Big Data, but unfortunately many end up with fragmented architectures and data silos that thwart their ability to interrogate data and create value.

Gartner predicts that by 2018, 70% of Hadoop deployments will fail to meet cost savings and revenue generation objectives due to skills and integration challenges.

Should data ecosystems be built?

The answer is firmly “yes”. The age of infrastructure opened the door to the use of analytics for extracting value from data. Essentially, the resulting insights make business decisions more accurate and intelligent and because of that, the focus has shifted. Now it is the business team and not the IT department that leads data and analytics initiatives, demanding more value from data-plus-insights capable of creating commercial opportunities and solving problems.

It must be recognised that the value of storing and organising data depends on what you do with it. Business teams want to ask questions that cross data silos; questions that account for customer, product, channel, and marketing in combination. This amounts to a fundamental realignment of priorities and means that in future, many of our data professionals will no longer be technical specialists. Instead, they will be business focused individuals using data, analytics, and technology as key enablers.

The Olympic spirit – higher, stronger, faster

Unsurprisingly, the monetisation of data and analytics will be a big differentiator. Gartner’s strategic prediction states that by 2018, more than half of large, global organisations will compete using advanced analytics and proprietary algorithms, causing the disruption of entire industries.

Without an underlying strategic framework – the organisation, the people, the processes, and the execution – businesses will drown in data. Only a judicial mix of analytics can help business leaders make decisions with confidence and intelligence, and sharpen the competitive edge.

The fact is that in any given organisation, data analysts beaver away making incremental improvements to their analytics’ “personal best”. Yet, as in the Olympics, it is the “Fosbury Flop” moments, and the Bob Beamon breakthroughs that live in the memory.

It is only such record shattering leaps forward – like prescriptive analytics – that are capable of changing corporate thinking. Or, more precisely, transform the whole data driven nature of business competition.

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