Survey Says: Data Science Investment Can Pay Off Big Time
Companies that make use of data science are living the high life, reporting more revenue growth, company growth, bottom-line profits, and market-leading performance.
A new study from Forrester Research -- cosponsored by Data Science, a provider of a data science platform-as-a-service (PaaS) cloud offering -- concludes that companies using "insight-driven practices" that incorporate the results of data science research and development are twice as likely to be market leaders in their specific industries. Forrester dubs these firms "Insights Leaders." It calls their counterparts -- companies that aren't able to make effective use of data science R&D -- "Insights Laggards."
"In our survey, 99 percent of respondents indicated that data science is an important discipline for their firm to develop, and 74 percent believe data science is among the most important disciplines supporting the rising demand for insights," Forrester says in the report, "Data Science Platforms Help Companies Turn Data into Business Value."
"Insights Leaders already have an edge here as well -- most have a data science road map and have identified use cases for big data across the organization, compared with less than 30 percent of other firms."
Leaders Living the High Life
It's good to be an Insights Leader. For example, 80 percent of Insights Leaders reported revenue growth exceeding five percent. Nearly half (44 percent) say their company's growth is exceeding shareholders' expectations. The same percentage say their bottom-line profits also exceed expectations.
Nearly two-thirds (64 percent) say they lead their respective markets with "a higher share than any competitor across all products/services [they] offer." Insights Leaders also tend to be better performers across their organizations: 67 percent of department-level respondents say their respective departments are exceeding their goals for contributing value to the business.
Forrester's survey is based on an online sample of 208 "decision makers" in a range of data science or data engineering roles. It used a maturity framework (a questionnaire with a weighted scale) to identify Leaders, Laggards, and the largest proportion of the normal distribution, "The Pack."
Forrester's research found that Leaders tend to have much larger budgets for advanced analytics -- about two times as large, on average -- as Laggards. The average Leader spends $2.2 million annually on developing data science and other advanced analytics capabilities; the average Laggard, $1.1 million. Average-performing companies spend about $1.47 million.
Leaders Are Smaller, More Nimble
The Forrester/Data Science survey discovered something else, too: Insights Leaders tend, by and large, to be small companies. Slightly more than half (53 percent) of data science leaders have fewer than 5,000 employees, the survey found.
On the other hand, larger companies are more likely to lag behind: according to Forrester, only one-third of companies with 5,000 to 10,000 employees are Insights Leaders. The largest firms are the worst performers: just 13 percent of companies with 10,000 or more employees are Insights Leaders by Forrester's definition.
The Platform's the Thing
The survey was sponsored by Los Angeles-based Data Science Inc., a start-up that markets a PaaS data-science-in-the-cloud offering. Unsurprisingly, Forrester finds that most companies tend to use integrated data science platforms rather than a motley assortment of tools and technologies. It identifies the lack of integration between and among analytics technologies as a critical challenge.
According to Forrester, an overwhelming majority -- 88 percent -- of Insights Leaders say they plan to pursue a "platform approach" to building out their data science stacks. Among all firms, comparatively few (26 percent) currently use a single data science platform. This percentage is much higher (38 percent) among Insights Leaders.
"Respondents reported using more than half of the analytics tools we asked about ... from basic BI tools and relational databases to predictive analytics, streaming analytics, and NoSQL databases. Many also have plans to implement even more tools in the next year," the report indicates.
"However, 46 percent lack an integrated platform for using these tools harmoniously. The top technology and data challenges we found reflect this lack of an integrated approach."
The Forrester survey concludes by urging companies to adopt a platform-based approach to data science and advanced analytics: "Insights Leaders recognize their competitive advantage often comes from the speed at which they can quickly optimize insight applications. Platforms unify the tools data scientists need to develop and deploy these [applications]," the report explains.
"Thinking about your data science tools as a connected platform and taking steps toward integrating and unifying them is a strong step in the right direction for any firm."