Predictive analytics: You don’t need to be a data scientist to get ahead

The race to harness the growing volumes of data for competitive advantage is putting increased strain on skills and resources within businesses. Recent independent research has revealed that 89 per cent of UK business decision-makers say that the volume of data their organisation collects or has access to has increased in the last 12 months.

As organisations seek to integrate forward-looking insight into day-to-day activities, the need for advanced predictive analytics is moving from a small population of specialists to a broad spectrum of users. Indeed, three in five agree that predictive analytics is currently an investment priority in their organisation and those that are already using the technology want the number of users to increase within the next five years.

It seems that UK businesses are aware of the benefits predictive analytics can have on their organisation. In fact, according to the research, the vast majority of those currently using the technology say it is already having a positive impact on their business (93 per cent).

By enabling them to make better use of the data within their organisation, predictive analytics is helping increase speed to market, competitive advantage and ultimately, revenue. But despite this, the research also shows that there are some barriers to overcome before organisations can get the maximum impact from predictive analytics, particularly around the perceived skills required to effectively draw insight from data and feed this back to the business; 47 per cent see lack of time and resource as their biggest challenge. Furthermore, 75 per cent of those surveyed believe that new data science skills are needed within their organisation, and 81 per cent would like specific training to integrate analytics into their day-to-day work.

Getting access to – and making sense of – data has, until recently, been seen as a complex and highly-skilled task, delivered by people with advanced degrees in statistics and prior analytical experience. This dynamic simply can't scale with the business, particularly if companies want to embed predictive analytics into all areas of the organisation, from point of sale to the call centre.

We could (and should) be in a situation in a few years where up to half of all employees in organisations are using predictive analytics in some capacity as part of their daily tasks.

Does this mean we all have to become data scientists for businesses to get the maximum return from predictive analytics? The answer is no. Whilst analytical skills are becoming increasingly important, and employers will start to look for evidence of this on CVs of people hoping to join their organisation, the fact is that advanced predictive analytics technology is making analytics much more accessible for the average worker.

More intuitive technology with easy-to-use interfaces that reflect the trends in consumer technology mean there is not always a requirement for specialist data science skills for individual lines of business to be able to interpret data and feed that insight back to the wider business.

What will be required from the workforce of tomorrow is a balance of skills, not just academic. All employees in the future will need to demonstrate curiosity, creative flair, and the ability to visualise and to communicate clearly with non-technical people throughout the business. Educational institutions can provide the knowledge and certifications but it is also important for the industry to work more closely with schools and universities to develop the workforce of tomorrow and ensure they have the right balance of skills for entering the modern workplace.

It is clear then that if businesses want to drive real value and insight across the organisation they need to empower their staff with both the skills and systems to self-service their analytics needs. As a result, they will start to see greater impact across the business as a whole; gaining competitive advantage and exploiting opportunities by having the ability to predict customer needs and future market trends.

Whilst there will always be new skills and resource challenges to work through, there is no doubt that technology is becoming more intuitive. Particularly when it comes to being able to make informed decisions, predictive analytics can drive significant business benefits for organisations without the need for employing swathes of data scientists.

If businesses can put the right investment into developing a data-driven workforce, alongside data-driven processes and applications, they can accelerate their performance, increase speed of decision making and uncover new revenue opportunities.

James Fisher is vice president of marketing for analytic solutions for SAP.