datasciences

When it comes to embracing data sciences in the business world, there’s no middle ground, according to recently released research.

A joint survey conducted by SalesChoice Inc., a SaaS company which focuses on predictive analytics to optimize sales results, and the University of Toronto, found businesses can be categorized as being either at “low readiness” or “high readiness” in terms of their maturity in embracing data sciences to improve sales outcomes, said Dr. Anthony Wensley, professor at the university’s Rotman Business School.

Those who fell into the low readiness category recognize the value of data sciences, he said, but are generally not investing in the technology, processes and talent necessary, at least not effectively, while high readiness organizations are sophisticated in their use of data sciences, have integrated it into their sales process and are continually improving on how they use it.

Dr. Cindy Gordon, SalesChoice’s CEO and founder, said 92 per cent of the organizations answering the 30 research questions were from North America. The survey queried 189 C-level global executives, sales leaders and others, and addressed four keys areas around data sciences: talent, process, technology and measurement. More than half of respondents – 57 per cent – work in professional services, software or professional services, while 44 per cent were C-suite executives.

Within the dimension of talent, 35 per cent respondents think their CEO does not value data sciences as a competitive advantage. “That’s definitely a concern,” said Gordon. Meanwhile, about three quarters of respondents do not have a chief data officer or chief data scientist, which she said is actually not surprising. Those that do are quite mature in their use of data science, with the insurance industry being one of the early adopters.

From a process perspective, the survey found that few organizations can meaningfully and easily engage with data in real time, although 69 per cent of respondents have clear definitions for data science terms, such as big data, business intelligence and predictive analytics, said Gordon. However, about three quarters do not have access to predictive analytics or prescriptive analytics.

datasciences-capabilities

“Organizations are starting to use data science technology but not effectively,” she said. The technology section of the survey found that 69 per cent of respondents do not have an enabling software for predictive analytics in sales and marketing, and of those that do, about half are not using win and loss patterns, while 70 per cent don’t have a senior technology leader with the expertise in data sciences to mine sales insights.

Wensley said the current reality is that data science practices are adequately measure or rewarded, which is not surprising. “Companies don’t generally benchmark themselves very well.” Of those surveyed, 73 per cent do not use data sciences to benchmark against best-in-class companies and only 22 per cent feel their organization is a leader in data science approaches, he said.

Lack of skills and operational clarity are big barrier for organizations wanting to make use of data sciences, and half of respondents aren’t even actively implementing data sciences in their sales organization, he said. Ultimately, organizations are either really sophisticated or a have a long way to go. “Few are in the intermediate stage,” he said. “It’s a real struggle from getting from being behind to being in the middle of the pack.”

Right now, the state of data sciences is one where an attempt is being made to marry the advanced techniques of the academic work with the pragmatism of business, said Wensley. “We haven’t done that all that well.” There needs to better collaboration between the two, he said, with business schools being a viable vehicle. “Leaders see that this a hype area. What is going to move them is adequate evidence is that it will apply to their organizations.”



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