The Challenge: Bringing Data Analytics Out of its Silo
We now have amazing technology that can bring data together, in real-time or right-time, to understand what customers want, and predict what they will likely want in the near future. However, the challenge is that these capabilities are still being stuck into new kinds of silos.
“A robust, successful data and analytics function encompasses more than a stack of technologies, or a few people isolated on one floor of the building,” Carl Carande, Paul Lipinski and Traci Gusher, all with KPMG, observed in a Harvard Business Review article.
Data and analytics, they urge, “should be the pulse of the organization, incorporated into all key decisions across sales, marketing, supply chain, customer experience, and other core functions.”
Still, there doesn’t seem to be as much progress as hoped in this regard. In a survey of 448 executives, only two percent of executives say their data analytics investments have achieved a “broad, positive impact.” Obviously, there seems to be a lot of work ahead of us, and much of it will involve working even more closely with the business to identify and guide data analytics investments.
The survey, published by the Economist Intelligence Unit in partnership with marketing firm ZS, points to a fact that is holding back the progression of analytics: there is still a long way to go in learning the how to effectively capitalize on data analytics. The challenge, as expressed by the EIU and ZS team, is that data analytics – as a function and as a system – remain contained within their own silos, very infrequently touching the mainstream pieces of the business. Executives in the survey report an inability to embed data analytics more deeply into their businesses. “The biggest challenges in the analytics value chain are those at the front and back ends – areas where senior analytics executives interact most with the rest of the business.” In addition, 47% cite challenges with solution design and change management, which also point to difficulties in introducing data-driven thinking into their organizations.
“Some organizations have data and analytics capabilities spread across functions, or rely on a few data scientists to provide insights,” Carande and his co-authors observe. “Some are too reliant on technology tool kits and rigid architectures, and not enough on creating the right environment to effectively leverage people with the right expertise to drive data and analytics projects forward. These sorts of models usually are not capable of achieving truly transformative data and analytics.”
Bringing data analytics out of its silo and into the mainstream business requires a number of measures:
Understand the business
In the EIU-ZS survey, 73% of executives agree that domain expertise – or understanding the business and the environment in which it operates – is critical to data analytics initiatives. Those charged with delivering successful data analytics need to “first acquire a good understanding of the core businesses of their company, its value chain and strategy,” the study’s authors state. “From there, they can truly become more involved in data-related issues, ensuring that the right data management, structures and capabilities are in place to enable proper data capture and experimentation.”
Encourage greater interaction between data and line-of-business teams
Today’s technology is very effective at potentially breaking down silos and generating insightful data analytics. However, the organization must be ready and aligned to achieve this. What this boils down to is a continued lack of interaction between data professionals and the rest of the business. In some cases, all it may take is to encourage more interaction between these parts of the business, even informally. I recall one chief data officer I recently spoke with described how he sponsored informal weekend getaways between data analysts and line of business employees.
Make data analytics a strategic priority
“Start by developing a strategy across the entire enterprise that includes a clear understanding of what you hope to accomplish and how success will be measured,” Carande and his co-authors advise. “Successful data and analytics starts at the top. Make sure leadership teams are fully immersed in defining and setting expectations across the entire organization.”
Keep data analytics teams front and center
“It’s important to understand that data and analytics teams are not data warehouses that perform back-office functions,” say Carande and his coauthors. “Your data and analytics function should be a key contributor to the development and execution of the business strategy by supplying insights into key areas, such as employees and customers, unmet market opportunities, emerging trends in the external environment, and more.”
Focus on data integration and aggregation
The EIU-ZS survey also found cloud is the dominant route taken to support data analytics. Nine in 10 respondents report they have implemented a big data-based infrastructure or are planning to do so. The catch is that only eight percent have integrated this cloud platform with their analytics systems. Data integration and aggregation is another challenge that needs to be addressed more thoroughly. In the survey, only 44% rated their organizations as adept at bringing data to the places it is needed. Even the “leading” companies were only marginally better, with 51% reporting successful data aggregation and integration.