One of the positive effects of the Covid 19 Pandemic has been the digital transformation being speeded up by many companies. Along with this, the Business Intelligence too has naturally gained speed and many BI dashboards are being implemented.
Today, in my blog I will be analyzing the analytics and BI dashboards from the perspective of aiding decision making, especially during progress review meetings.
I want to compliment the numerous analytics and dashboards available, which primarily depict numerical data graphically, of different types. Using these graphs, it is possible to better understand the reality for planning improvement measures. These analytics can also be used to validate the hypothesis during the iterative planning process.
However, once the planning phase is over, we should be using the analytics for reviewing and achieving consistency in performance. The content of such analytics is different from the one widely available today, primarily for planning and for testing the hypothesis during the iterations. I have put together two examples of such analytics, which I will explain in detail.
After having defined the Key Performance Indicator, it is necessary to establish the monitoring, steering, and reviewing clockspeed – each being faster than the other. The targets for all the clockspeed timeframes must be defined. It is very much necessary to plan for the next clockspeed timeframe and to forecast for one thereafter. In my experience, consistent performance is achieved when the forecast is greater than the plan and the plan greater than the target to address the unforeseen surprises. The next step is to capture/collate the data for computing the key performance indicator and generating the analytics dashboard. Additionally, OTU: On-time Updating is equally a must for ready access by all the team members, therefore I have added the OTU status at the top. Optionally, OTR on-time review can also be included. Finally, it is very useful, if a simple signal is used to indicate the criticality.
The Actual is based on the current data, while the Latest Estimate is predicted based on extrapolation considering the type of data and the seasonality and the correlations. The benchmark can either be picked from the past best performance or entered separately from the benchmarking data. The next extremely important aspect is to manage the Y-Axis scale in relation to the various Clockspeeds so that the analytics dashboard can be perceived almost instantaneously.
I believe these basic criteria must be met for any analytics dashboard.
- Ease of comprehensibility with standard templates.
- Speed of comprehension in seconds and not minutes.
- Data collection/collation timeframes correspond to Clockspeed.
- Focus areas for deep diving are obvious without any explanation.
- Development over time is presented to capture trends.
- Benchmark, Target, Forecast, Plan and Latest Estimate are included.
- On-time updating and, optionally, on-time reviewing is visualized.
- Usage of a simple signal or smiley to indicate the criticality.
- Checkpoint for regular on-time updating is included.
You must be wondering; how much additional effort will be needed to create and maintain such analytics dashboards. The ERP, MRP and PLM systems are already implemented in many companies. Apart from this, multiple workflow automation applications, especially using checklists and mobile forms is also a common feature today. Even the planning of actions and scheduling of tasks are digital today. Of course, the data from all these standalone systems must be captured, validated, plausibility checked and presented as dashboards, all done automatically with today’s computing power. With the ML and AI solutions the forecasting and predicting is also possible today. With all this I want to confirm that the ongoing effort for creating such analytics dashboards is literally Ø. However, some initial investment may have to be done for linking all this massive data, for meaningfully compiling and smartly visualizing, for assisting team and not individual decision making. The team effectiveness improves exponentially, as experienced by me, with the dashboards like the two samples I have used.
The reason is simple – instead of spending most of the time in meetings for everyone getting to know the current situation, most of the time can be spent in discussing the solutions for securing the buy-in, while naturally changing the mindset and culture for agility.
I am sharing my first experience, from almost 20 years back, on the impact of comprehensive analytics, all manually constructed though! I spoke to my team of about 150 people every month in all the three shifts using these analytics, as the mindset and culture transformed for delivering significantly better results. With today’s technology, we can achieve an even better impact in lesser time.
The analytics dashboards are essential to improve the flow in the Seven Business Chakras, I had introduced a a couple of weeks back. Unlike a single intelligent mind striving for improving the flow of energy in the seven chakras or energy centers in our body, multiple diverse intelligent minds need to jointly strive for improving the flow of business wisdom in these Seven Business Chakras.
I will end my blog with a quote by Albert Einstein:
“The Measure of Intelligence is The Ability to Change”
How intelligent are your analytics to drive change, so much needed for agility?
2 thoughts on “Analysis of Analytics”
The belief and the discipline to follow in anything we do are very important. Such tools or aids can then help realize our goals.
very well done analysis and also shared the entire information very neatly.