In the race towards insights, trust at every stage of the analytics value chain is foundational to unlocking the value of data, as well as the technologies that enable analytics. In our January 2018 research of over 200 analytics decision-makers, those defined as “leaders” commonly exhibit trust in their actions, from data collection to data-driven decision-making. In exploring how and why trust plays a role in analytics leadership, we’re publishing this series to dig into several of the critical factors necessary to building the trust needed for analytics leadership, including organizational design and IT-business alignment.
As shown in our research, insights-driven cultures are foundational to analytics leadership. Achieving leadership requires new modes of thinking and believing, deeply embedded in an organization’s makeup. In the third installment of our series, we apply the principles of cultural change to understand what business functions can do to become intrinsically data-driven.
Changing the Narrative
In some organizations, executives take a very data-oriented view of their work. Recent Forrester research indicates that 81 percent of business owners and C-level executives can access the data they need to obtain insights in a timely manner, but only 63 percent of individual workers say the same. While executives may not be responsible for day-to-day decisions related to analytics, the narrative they are responsible for shaping and promulgating needs to become part of the organizational culture.
If they haven’t done so already, top leaders in an organization must incorporate insights as a key enabler of the aspirational vision the organization sets for itself. But in 2018, this is the start and not the end of designing a well-rounded vision. Using data to enhance and personalize products, define and capture new markets, and make real-time business decisions is now table stakes.
Leaders must communicate with urgency to make it clear that data-driven insights are not just a direction for the future, but critical to competitive advantage today.
A company’s values are written to articulate present priorities and guide future action – and the use of analytical insights for decision making must become part of the value set. This starts with embedding analytics in stated values, leadership expectations, and other vehicles used to build culture intentionally. Alignment to these core values provides a sustained mandate for ongoing and discrete change initiatives to be seen not as an option but a requirement.
In practice, embedding values involve not just speaking but setting examples, even (and especially) where it hurts. Do you press for quantitative justifications behind significant decisions, even when it means additional time and effort? Do you refuse to settle for fragmented data sources and require a shift to apples-to-apples metrics, even in the face of entrenched opposition? Senior leaders must prioritize long-run accountability for embedding the values and sow the seeds that allow people at all levels to embed the values in “unexpected places” including everyday language and behaviors.
Talking the Talk and Walking the Walk: Being the Change
The talk: Language
Intentionally developing and using key terms and points of emphasis is one way language connects concrete efforts to vision and values, and helps clarify otherwise fuzzy ideas. A compelling example is how Nobel prize winner Daniel Kahneman harnesses the power of language to enable cultural change by providing examples of how key ideas can be translated into water-cooler gossip in every chapter of his book, Thinking, Fast and Slow. Aspiring change agents for analytics can borrow from his approach and research on the psychology of bias, causality, and statistical thinking.
Language in the form of data storytelling should be used by analytics practitioners to engage and win audiences as part of a data-driven cultural transformation. This is two-fold: not only does storytelling better convey the outcomes of the problem at hand, but it also engages the audience to start shifting their thinking about analytics in general. Artfully exposing carefully selected and tractable elements of an analysis along with the final outcomes is crucial to building trust in analytics that may otherwise be opaque, and if done well will drive divergent thinking about what may be possible rather than converging on answers before one has really had a chance to explore the questions.
The walk: Behaviors
Behavioral change is often seen as the desired outcome, but modeling behaviors – ways of working and thinking that demonstrate the value of analytics – is also important for driving acceptance and true cultural change. If there are barriers to collaboration, analytics organizations should strategically target “give-to-get” opportunities with desired business leaders (and potential champions for the cause) to model behaviors that go beyond ticket-taking report building and begin a virtuous cycle of collaboration.
Trusted ways of working quickly open avenues for changing ways of thinking, i.e., frameworks and ways of approaching questions and decisions. Open conversations about what is really needed and what is possible can lead to decisions and solutions based on a detailed understanding of the business, the information needed on a daily basis, and the levers available to manage the business.
Meeting in the Middle
One pitfall in any cultural transformation is to focus on change at the top and at the bottom while the middle is overlooked. To really take hold, changes in language and behaviors must be fostered through reinforcement and through the systems that enable or discourage them.
“Soft” forms of recognition should be deliberately attuned to reinforcing behaviors and language that reflects the value of data and analytics. The role of data in the company’s vision and values must be communicated regularly and across channels, and when desired behaviors are observed at the front lines, they should be quickly called out, praised, and rewarded. This is especially important in the face of failed attempts to collaborate or seemingly insurmountable obstacles that threaten to undermine the entire effort.
At the same time, “hard” recognition is also required. This means giving analytics a seat at the table – each table – to better understand business priorities and help shape attitudes and support decisions with information. This also means putting serious effort into designing performance measures and rewards that reflect the value of data in the company’s daily operations.
Organizational systems and tools demonstrate the value of analytics when they are enabled to both capture data and to leverage analytics for improvement. Process and technology roadmaps should all be oriented toward becoming analytics-driven, and even model-driven in the long run. Systems and tools need to mature alongside the cultural change, lest they hamper change efforts and provide cover for status quo behaviors.
Systems also support the gradual workforce transformation in ways of working and thinking. Learning and development plays a key role in building data literacy across the organization. Recruitment and retention strategies must similarly contribute to building a solid analytical foundation regardless of role or business function.
Cultural change isn’t easy, but it’s fundamentally important. While our research shows that only 44 percent of organizations have been successful in establishing insights-driven cultures, there’s a measurable return for the organizations that achieve it. Forrester reports that insights-driven firms are growing at an average of more than 30 percent annually – and eight times faster than GDP. Faced with the sometimes-overwhelming breadth of obstacles to cultural change, analytics functions need to focus on the key building blocks of instilling greater trust in analytics: namely, the experiences that analytics delivers.
For a complete picture of the landscape of trust in analytics, take a look at the other pieces in our series: