According to a recent study by Ignites Research, less that 20% of asset managers’ analytics teams’ time is spent on analytics, and only 63% of firms can turn the resulting analyses into opportunities or wins. Compared to other industries, asset managers are behind the curve in using analytics for sales and marketing enablement, but similar issues have persisted in other, more analytically mature sales organizations. Sales teams and marketers at asset management companies use investment analytic teams to support their decision-making, so when the sales and marketing analytics they receive don’t deliver the value they expect from other analytics teams, they’re less likely to tolerate it.
Interestingly, the most challenging steps are at the beginning and end of the analytics value chain, according to a recent ZS study, rather than the middle stages of statistical or analytic execution, where the traditional focus has been on analytic process improvements. In the asset management industry, there are three common themes that cause these breakdowns:
- Poor problem definition or approach selection: Before applying any statistical techniques, many analysis efforts are dead on arrival because analysts frame the problem too narrowly or too broadly, or they select the wrong approach. For example, some analysts undergo complex analytics when a much simpler analysis would be sufficient, or they select the wrong type of complex analysis. It’s important to take steps—such as training, integration and setting aside time in each effort for scoping—to ensure that your analysts know their customers’ problems and needs.
- Endless data preparation cycle: Many teams find themselves in a never-ending cycle of data preparation. Investing in data prep tools and processes that meet most of the analysts’ data needs can greatly reduce the time spent on the other steps of the analytics value chain. Analytics teams should continuously search for ways to operationalize common data preparation tasks.
- Change management issues: Successful change management is necessary to gain the full impact of any initiative, and change prompted by analytics is no different. It’s no surprise that change management is one of the largest problems even for high-performing analytics-based organizations because it depends on seamless integration of analysts, marketing personnel and salespeople. It’s critical for analysts to understand not only the business, but also the psychological and emotional barriers to any change that they recommend, and how to overcome those obstacles.
Asset managers have an opportunity to build their analytics teams to address these broken portions of the analytics value chain. The first step is to identify that there is a problem—which is a step that many companies within asset management and other industries have yet to take.
After you’ve identified the problem, you can craft a solution, which should include tapping experts on your analytics team who know the business problems, developing systems to complete common data processing tasks and pushing your analytics team to navigate the change management problem.