Tell captivating big data stories with the help of storyboards
Image: iStock/Shing Lok Che
For movies, video work, and cartoons, a storyboard is the successive drawing of scenes or frames that work together to weave a plot. Storyboarding is also a natural fit for IT; it can be the vital link between reaching the desired result that end business users want from analytics, or missing the objective altogether.
Put analytics on storyboards
In its way, storyboarding is an old technique in IT. For years, system and application designers have used storyboarding to demonstrate functionality in technical design reviews. But storyboarding has been used sparingly in the end business, where it could be put to productive use by stepping end users through a business process visualization.
In the big data world, visualization is often thought of as different pictorial ways to represent data, but an alternate definition of visualization in the form of business process storyboarding can be just as productive.
When to build a storyboard
Do it as soon as an analytic idea is proposed that will change a business process. Why? Because the end user must buy into the change in how she does business.
How to create a storyboard
You build a storyboard the same way that you create a flowchart: chart out the business process flow that the analytics will prompt, and also how the analytics will fit within the process and what it will contribute. A walkthrough like this (before any work is done) helps the end user visualize the pros and cons of the analytics function in her work area before the project starts.
A real-life example
A city tram operator wants to find a way to improve the reliability of the tram system, decrease the cost of operations, and grow the appeal of the tram to customers who have other transportation options.
In the existing system, when part of the tram track fails, or when other parts on the tram cars and engines fail, maintenance crews are dispatched to repair or replace the parts. Between these occurrences, and on a regular basis, crews go out to inspect the track and cars as part of periodic maintenance field calls. These inspections are used to make repairs, pinpoint areas that will soon need repair, and do preventive maintenance. If a section of track or a part failed between visits, there would be an emergency personnel dispatch to the field.
A new analytics process was proposed that used remote sensors to monitor the health of tracks and trains throughout the system. The sensors would collect machine-generated data and report in to a central software console. If critical operating tolerances or measurements were exceeded, or if they approached levels of intolerance, the fully automated system would generate a message to the nearest field maintenance crew, instructing it on which part or area of track was about to fail.
In many cases, the net result was that periodic maintenance visits now included proactively replacing parts that the system reported would soon fail. In other cases, there were emergencies that crews had to immediately respond to. Overall, system reliability was likely to go up because there were fewer realtime failures, and customers were happier.
The value of using storyboards
This move to analytics sounds like a straightforward no brainer, but it probably isn’t. For starters, an injection of automated prediction analytics impacts the workflow of the field crews, who are probably wondering why a “proven” work process has to be changed. There are also business managers who are likely unhappy with the change, because it means they have to train workers on new systems and procedures.
This is where the value of the storyboard comes in for business analysts. Frame by frame, analysts can show the present and revised business processes alongside each other and illustrate business steps that will be revised, added, or eliminated in the new process. The business analyst can walk through the script with business users, address user concerns, make revisions, and arrive at a point where everyone concurs that it’s beneficial to make the change.
Conversely, if the benefits of changing are perceived as negligible or nonexistent, storyboarding is also the perfect way to pull the plug on a proposed analytics project.