James Taylor, CEO, Decision Management Solutions
A Beautiful, Cloudy Forecast
Research by James Taylor, CEO of Decision Management Solutions, shows business potential in cloud-based predictive analytics.
Both “predictive analytics” and “cloud” are hot topics in business today. But what is the potential for predictive analytics in the cloud? Research by Decision Management Solutions and a recent survey of more than 200 professionals hosted by SmartData Collective shows that cloud-based predictive analytics is poised for rapid growth.
Separately, predictive analytics and cloud solutions are changing the way organizations do business. Together, they open up a wealth of opportunities. The use of predictive analytics in the cloud to improve focus on customers is particularly powerful. As early adopters look to build a sustained competitive advantage, organizations should have a plan to rapidly adopt this new approach to avoid being left behind.
Many survey respondents (43%) have already seen an impact from successful predictive analytic implementations. For an approach that has only recently become a mainstream topic in organizations, this is an impressive showing. Perhaps even more impressive is that 11% of respondents say this impact has been transformative.
According to the survey, the top two areas for cloud-based predictive analytics were marketing/customer acquisition and customer retention. Other areas that scored well included the broader category of customer management, sales and cross-sell/up-sell. Fraud detection scored high for projects currently implemented. It is clear that the sweet spots for predictive analytics in the cloud are effective acquisition, management and retention of customers. Cloud-based options are also very appealing for geographically dispersed staff to work on customer-facing processes.
While there is a clear optimism about these solutions, some issues remain. Data security and privacy were the top concerns in the survey, with 65% listing them as very important. Regulatory issues, bandwidth for moving to the cloud and increased complexity were also identified as concerns. Each can be mitigated:
- Privacy and security. Keep personally identifiable data out of modeling and leverage private clouds when necessary.
- Regulatory issues. Work with vendors experienced in your industry.
- Moving data to the cloud. Move data to the cloud directly rather than aggregating first and then moving to the cloud.
- Complexity. Work with experienced vendors and leverage more public cloud infrastructure.
Early Adopters Benefit
However, when a new technology is adopted, organizations must choose between being leaders or laggards. With cloud-based predictive analytic solutions, this balance seems to come down firmly on the side of being an early adopter. The gap between companies that implement these solutions now and their competitors is likely to widen as early adopters realize more positive results, have fewer objections and more aggressively adopt the technologies.
The basic value proposition of predictive analytics in the cloud is clear: Organizations can make predictive analytics more scalable, more pervasive and easier to deploy. For many of the challenges organizations face in their journey to becoming analytic organizations, cloud-based solutions have much to offer.