In part 1 of our visual performance management (VPM) series, we offered observations on the factors that businesses are getting right, or wrong, in VPM; part 2 unpacked the principles of VPM design that bring clarity and cohesion of information to diverse teams.
In our third post, we’ll unpack the mechanics of setting up a VPM model for your team or business, including the pros and cons of custom-built VPM software development.
Building your VPM: Knowing your blueprint
In the excitement to capture the value VPM offers, it’s tempting to look for the “one thing” that promises to deliver the entire solution, from initial concept through to implementation and impact tracking. But if there ever was a field where the old tailor’s axiom, “measure twice, cut once” is apt, it’s VPM.
That means taking a few crucial steps before looking at specific product investments: looking at design principles, logistics, and where the information engines will ultimately sit.
Design principles
Remember the one-three-ten rule from our first post? A quick refresher: take one second to know whether you’re winning or losing, three seconds to identify what you’re winning or losing at, and ten to determine your course of action. This idea is especially important in building a performance management visualization that gives the viewer the clearest story of the organization’s performance in the shortest time. Furthermore, creating an insight-driven VPM experience requires a deep understanding of the company’s data, its stakeholder needs, and users’ goals, structured according to best-in-class design principles and execution.
The design principles that must be settled before digital VPM product investment include:
- Tailored. Who is going to use this digital VPM tool: the C suite? Field operators? What will their purpose be?
- Intuitive. Which insights are most important to deliver, and how easy to understand are they?
- Interactive. How interactive should your visualization be? Will it follow the right information hierarchy (showing high-level metrics first and enabling drill-downs into specific values)?
- Accessible. Have you accommodated different accessibility needs, like color blindness or low-vision users? The Web Content Accessibility Guidelines published by the World Wide Web Consortium provide a good starting point.
Logistics
The logistics that need to be explored before digital VPM product investment include:
- Data type and accuracy. What types of data are available: quantitative, qualitative, spatial? What is the data governance model to ensure timeliness and accuracy?
- Data access and refresh Frequency. How often are the data refreshed? How often will target users access the VPM dashboards? The answer affects the timelines to be presented and the frequency of data refresh.
- Data format. How clean are your data? How much reorganization would be required to match the data with the target software? Where will the data be hosted? What is the platform integration path?
- The team. Do you have the right agile team for this development? This could include a product owner, scrum master, designers, software developers, solution architects, data scientists, data engineers, and subject matter experts who can join problem solving and provide insights and feedback on regular basis.
Location of information engines
With principles and logistics settled, take further time to be deliberate about where the information engines will sit, whether inside or outside of any software solution.
- Find out which calculations and transformations you will need.
- Map the end-to-end process and, where possible, simulate through spreadsheets or data visualization tools.
- Identify all inputs to go into a visualization—charts, maps, etc.—and ensure you can compute simple formulas outside of the VPM software to minimize lag.
Remember, joining data can happen either inside or outside visualization software. While it’s a common function in VPM solutions it can encode an error in ways that are less obvious to trace.
Finally, let’s look at reasons for and against going bespoke on a VPM system. While the market offers several out-of-box VPM solutions, each organization has unique—or seemingly unique—needs. The siren song of a bespoke VPM system can be a powerful call to business leaders. But should you heed it?
When customized solutions count
A bespoke or custom-built data visualization may be of value when:
- You need a complex visualization for complex operations, such as a department with multiple functions where performance management is already fairly mature—perhaps an existing dashboard cannot be expanded to provide the insights needed for all functions or use cases (Exhibit 1).
- You need more flexibility in creating bespoke user and stakeholder experiences, which can make your data more useful to diverse teams.
- There is clear ROI, you are confident—and, ideally, have data to support your confidence—that in your specific context and operations, a high level of detail and customizability will be worth the investment (Exhibit 2).
Exhibit 1
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McKinsey_Website_Accessibility@mckinsey.comExhibit 2
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at:
McKinsey_Website_Accessibility@mckinsey.comWhen standardized solutions suffice
However, there are several risk and cost factors to consider before embarking on the custom route. Custom-built digital VPM is more expensive, both in development and use. Usually, it will require a large, multidisciplinary effort in the design and development of the tool (in both front- and back-end engineering). And it will need a team to own and maintain the tool after implementation—a factor that imposes its own costs, yet is easy to overlook until the bill comes due.
The design process itself can provide another important clue as to whether customization is likely to be worthwhile. If technology as simple as a pen and paper can’t create a vision for the outcome needed, then custom-built VPM may provide no advantage. Instead, your solution might be to revisit our earlier steps to get clarity on the true one-three-ten.
What’s the lesson? In most cases, that custom-built VPM solutions are justified only when off-the-shelf software demonstrably cannot create the outcome needed.
Getting started
We end where we began—focusing on clarity and simplicity.
Always remember that good performance visualization will tell the story of your business’ performance at a glance. If the blueprint process outlined above is yielding too much complexity, return to the one-three-ten principle. If your VPM design principles are clear and fit this rule, then it is likely that software (either custom-built or off-the-shelf) may help with the synthesis, delivery, and usability of your VPM model.
But if you are looking at software to solve your design principles first, you could be on a path to disappointment.
Measure twice. Cut once.