Читать книгу AI-Enabled Analytics for Business - Lawrence S. Maisel - Страница 15

Research typically pegs the ROI on analytics at a minimum of 10X. For example, according to Boston-based NUCLEUS Research, the 2014 survey on Analytics ROI revealed that the average return “has increased to $13.01 for every Analytics dollar invested.”⁵ An excerpt from a November 2011 Research Note from NUCLEUS Research highlights the visibility that analytics provides:⁶

Software buyers may think that vendors overhype visibility as a benefit of analytics, but Nucleus found that, in fact, the highest-ROI analytics deployments made data more available to decision makers and enabled them to find ways to increase revenues or reduce costs. Nucleus found analytics enabled improved visibility in three areas:

 Revenues. The more managers knew about what customers where (sic) buying and why, the better able they were to accelerate sales cycles, cross sell, and maximize pricing.

 Gross margin. By serving up highly granular data on costs of goods sold, analytics applications helped decision makers identify the highest margin products so that they could push the right products and increase gross profit.

 Expenses. The more managers … learned [from] analytics … the better able they were to reduce or eliminate expenditures that were unnecessary or generated low returns.

As seen in Figure 1.3, the report “The Analytics Advantage, We're just getting started,” from Deloitte, reflects key findings from the Deloitte Analytics Advantage Survey, including “Nearly half of all respondents (49 percent) assert that the greatest benefit of using analytics is that it is a key factor in better decision-making capabilities.” Further, when asked “Does analytics improve competitive positioning?” some 55% of respondents indicated that analytics Fairly to Significantly improved positioning.⁷

Figure 1.3 Deloitte analytics for decision-making.

With executives agreeing on the value of analytics for decisions and competitive capability, we note that business performance betterment projects must be measurable, and AI is no exception. To this end, we believe that all analytics projects should start with a proof-of-concept or pilot to ensure that the quantification of benefits are measured, material, and achievable.

For example, at a data science conference, many speakers crowed about their projects with AI and analytics. But what was notably absent in most of the presentations was a slide on ROI. In one session, a member of the audience specifically asked about ROI. In a proud fashion, the presenting data scientist said the project saved enough money to hire another data scientist! Self-perpetuation is not ROI, and this example highlights the need to benchmark AI's contribution to business performance.