Dashboards as Products: Considerations to Improve Dashboard Adoption and Benefits
Alexander Mendoza, IT Senior Director for Data, Analytics and Planning Systems for Chobani
Alexander Mendoza, IT Senior Director for Data, Analytics and Planning Systems for Chobani
If we think of each dashboard as a consumer product as opposed to just a technical deliverable, then the following would be some of the considerations we can take from the marketing practice to increase the adoption and benefits of every dashboard.
• Target Users – there needs to be a good understanding of who the target users are (or at least an understanding of user segments) and what would these users need from the product. Being able to create a persona of each of the segments, their expected experience, benefits, etc. early on can mean better user experience and less redesigns. This can differ by industry or even how organizations are structured and thus a careful study of users is always good practice. Some of the typical user segments we see, and their focus, are the following:
- Executives– Enterprise KPIs presented in a concise dashboard, preferably served on tablets/phones in a “click and go” format which can be one summary dashboard or publications sent via email.
- Department Level Management - Department level metrics presented in a more granular level than what the executives can see and allows for quick, localized decision making and perhaps one to two drilldown paths.
- Business Analysts–Department level data with the ability to do their own dashboards based on governed data that they can then share with other members of their department.
- Data Scientists- Detailed or even potentially raw data to create analytics model on. In some cases, they can be the same as business analysts but in most cases, these user segments bring a different set of skill sets and capabilities to the company.
If users and their needs are well understood, then they can probably even be served with dashboards coming from one data model which would minimize the proliferation of similar dashboards and optimize the amount of data/information to be shown per dashboard.
• Investment – In general marketing, this usually means how much a customer is willing to pay/invest to get the benefits of a product. This is like asking the question of what is the value of the data visualization from the dashboard users’ perspective. Does it cost them less time and effort to get to the same insights they used to get? Do the insights generated by the data visualization allow them to get incremental benefits because of, say, faster decision making? Will it eventually cost the company less since an alternative, possibly more expensive solution, can be retired? Does the enterprise benefit as a whole because of standardization across business function – making the cost-benefit compelling enough overall?
• Place – There needs to be a deliberate approach on where the product should be made available, and this can translate to how the data visualization will be best consumed by the target users. There may be a user segment who can best consume the information via a mobile device like a smartphone of tablet while there may be a customer segment that can best consume the information via a computer or even say via a TV screen mounted on a wall.
• Adoption Strategy/Change Management – “Build it and they will come” does not typically happen in our experience with dashboard development. The goal should not be whether a dashboard made it to production or not but rather did it fulfill its objective. This can encompass continuous and ever evolving end user trainings, lunch and learns promotions in corporate town halls, office hours, etc.
One of the things we see nowadays is that the more precise a dashboard is with regards to its purpose and target audience, the better the adoption and return is to the company
If one deliberately approaches each dashboard as a product to be “sold” to end users as opposed to a “let’s build it and hope they will come” approach then there is more opportunity to improve adoption early on which translates to better returns to the company as well.
About the author:
Alexander Mendoza is currently the IT Senior Director for data, analytics and planning systems for Chobani, a food-focused wellness company. In this role, Alex is responsible for the successful implementation of Business Intelligence, Analytics and Data Governance practices in the company.
As the maker of America’s No. 1-selling Greek Yogurt brand, Chobani has since expanded its portfolio to include oat milks, ready-to-drink coffees, probiotic drinks, and dairy- and plant-based creamers and data and analytics is a key driver for this growth.
Alex has more than 20 years of experience in data and analytics, mainly in the CPG industry, helping organizations drive competitive advantage through effective data and analytics practices.
Alex earned his Master of Science degree in Analytics from Georgia Institute of Technology, his MBA from the Kelley School of Business, Indiana University, and his Bachelor’s in Science degree in Mechanical Engineering from the University of the Philippines.
