Phase Two: Inventing
In the Inventing Phase, new ideas and potential solutions are generated based on the research and pain points that were identified in the Discovering Phase.
Pain Point 2: Lack of Leading Indicators: The data presented within the Balanced Scorecard did not accurately provide trends in data or leading indicators.
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Tim Rayburn mentioned how he is able to identify insights due to his 25 years of experience.
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“...Looking at the BSC, Insights would be like Tribal Knowledge.” - David O’Hara
“We thought X would change and result in Y, but it didn’t…” - David O’Hara
Insights/Research: How Might We identify leading indicators and use them as insights for the Balanced Scorecard?
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Thematic Networks Activity: I used Mural.co to create an activity that would help the team identify and visualize the connections between each of the sections of the Balanced Scorecard. The plan was to link each metric to another if we saw a relationship or a correlation in data between them. Link to Activity
Challenges: Halfway through the activity, we realized that even if we were to link all the metrics together and establish relationships, we would be choosing these relationships based on minimal experience in the company’s operations and would still need to verify all these relationships with executives. Therefore, we did not finish the activity and moved onto to the next method.
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Spearman’s Rank Correlation: The Spearman’s Rank Correlation is a formula that helps to find the level of correlation between multiple metrics. I used this formula on the individual metrics within the Balanced Scorecard to find what metrics were correlated. I originally focused on trying to see if any metrics within the Culture section had an influence over the metrics in the Operations section.
This is a small overview of the vast number of correlations I ran on Excel.
…and so many more…
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The table below represents a relationship that was found using the Spearman’s Rank Correlations. This tells us that the number of salaried employees is directly related with the # of events that are being attended each period by 76%.
Solution 1.0: Using Spearman’s Rank Correlations to Find Leading Indicators on the BSC and Prompting them as Insights through the use of VBA Macros.
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After we identified the relationships between metrics with the use of the Spearman’s Rank Correlations, we then found a pre-written macro online and implemented the relationships into the code. We also programmed the macro to determine when a specific metric would fall below their target. In simple terms, if a certain metric were to fall below its target, the macro would recognize this issue and find the effect on the correlated metric with the use of the formula from the Spearman’s Rank. One recognized the macro would copy and paste this data onto the main dashboard to prompt this insight to executives.
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For example, if the number of salaried employees were to drop, the number of events attended would also drop.
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This storyboard showcases the process:
Who, What, Why:
Improving’s upper-level management can use the prompted insights to take initiative on leading indicators defined within the Scorecard.
Results:
My team and I agreed that using the Spearman’s Rank Correlation was the best way to identify leading indicators within the BSC within our time frame. In a perfect world, if we had more time with this project, we would make sure to verify all the relationships we found with Improving’s executives BEFORE we implemented them into the VBA macros.
Quick Overview
Yellow Hat: The overall process of prompting an insight to the dashboard is functional.
Black Hat: Due to time constraints, the relationships identified are not verified.
Green Hat: We could schedule a meeting with executives at Improving to see if they already have data regarding any relationships they have seen.