Design Thinking For Analytics Excellence
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Design Thinking for Analytics Excellence

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Data Professional, Dev Manager at CDK

Design Thinking is a human centered, iterative process increasingly used for digital transformation of products, services, teams and businesses. This article talks about using the tenets of Design Thinking to put the users at the center of an analytics project to ensure success.

Business Analytics combines data, technology, statistics and quantitative models to generate insights, make sense of the numbers and use them to make timely decisions. This remains a rapidly evolving field and in the past decade the tools and technologies supporting the ecosystem have improved by leaps and bounds.

Design Thinking for Analytics Excellence

However empirical evidence and industry research indicates high rate of failure in this space. Gartner says “80% of analytics insights don’t deliver tangible outcomes and 80% of AI projects remain alchemy, run by wizards”. Major reasons for such high failure rates include poor communication, lack of business-IT partnership and not taking the users into confidence. So harping on designing analytic solution with end users’ stated and unstated needs in mind doesn’t hurt.

Most of the practitioners agree that the notion of “If you build it, they will come” doesn’t work in analytics and project outcomes have to be about aligning with what the users desire. Analytics projects are often about introducing changes in the status quo. Be it a one-time ad hoc analysis, a decision support system, a predictive model, an operational report or a management dashboard; the primary motive behind these endeavors is to spot opportunities, expose the inefficiencies, track KPIs against a baseline and assign accountability.

Because analytics tries to introduce new ways of working and measuring progress, the final outputs of these projects can be unsettling and business users can try to resist the change. This is why analytics leaders and team members should show great empathy for the users and start putting themselves in their shoes. They need to envision how the end users would consume the product or service. It isn’t only about making the analytic product aesthetically pleasing or easy to navigate. It is about designing the user experience with focused enquiry and a people-first approach. This is where adopting the Design Thinking ethos can make all the difference.

Tim Brown, CEO of IDEO, defines Design Thinking as a “human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology and the requirements for business success”. IDEO proposes a 3I Framework (Inspiration, Ideation, Implementation) to infuse design thinking into the project.

Inspiration (Explore - Empathize - Understand): Process of truly discovering the problem or opportunity

  • Interview and observe the users
  • Understand who are we solving for, what is the problem and why does it needs to be solved.
  • Resist the urge to propose a solution at this stage
  • Create user personas and point-of-view statements
  • Come up with the criteria for evaluating proposed solution

Ideation (Research - Prototype - Collaborate): Process of generating, developing and testing various ideas

  • Synthesize what you have learned about the users
  • Hold brainstorming sessions. Defer judgement.
  • Diverge to Converge – Come up with more ideas and filter them later
  • Determine what to prototype

Implementation (Test – Build – Evaluate): Path that moves from project space to users’ lives

  • Make prototypes and validate
  • Turn the best ideas into a concrete action plan
  • Launch Solution
  • Keep getting feedback and iterating
  • Scale towards impact

Similar to other iterative frameworks like Lean and Agile, design thinking isn’t a linear process. We need to iterate through the steps till the end product meets the users’ needs.

It isn’t only the UI/UX professionals designing the analytics front-end who have to worry about design thinking. The framework has valuable lessons for all analytics professionals and there is always a scope to be better at listening to what the users are saying and most importantly what they aren’t saying. It is possible that they don’t really need a dashboard with 20 charts even though they are asking for it.

May be they prefer a machine learning model that is easily explainable than some esoteric one or maybe they don’t agree with how a KPI is defined because they think it unfair to their team.

It is only patient probing and empathizing that can unravel the problem or the opportunity. Building an analytic solution with the iterative Designing Thinking framework can increase the odds of success.