Biased scorecard for the best way to success
Ripping up the balanced scorecard
That is correct, The Biased Scorecard for the best way to success, not the popular balanced scorecard (BSC) created by Norton and Kaplan. It is about time we shared some hard truths about the BSC and put forward some steps that will provide your business with a corporate performance management system that succeeds every time. In this article I am going to rip up the balanced scorecard and patch it back up better than new.
When the BSC fails
Business growth or leadership change is the most frequent drivers for implementing the popular measurement system called the balanced scorecard. The very name implies that each head and business area will have an equal say and influence on the business. This incorrect impression is also applied do to the standard symmetry and equal sized boxes when the model is explained or shared.
On top of the model context, the implementation process is often the first time a business had undergone such a deep dive into its operations. The outputs and findings typically become the largest hurdles and stop the BSC implementation short, or contribute to its gradual death through lack of follow up and action.
The key danger areas include:
· Poor data quality and therefore incorrect statistics and conclusions generated
· Lack of trust and credibility through discover or protectionism from silo behavior
· Misunderstanding of the model with managers insisting all KPI’s are equal
· Too many objectives clouding significance and importance
When have you recognized some of the above danger areas?
Cognitive bias in strategic planning
One key reason why there are significant benefits and advantages in gaining help from advisors and consultants to help your business surrounds the subject of cognitive bias. The design of a robust and sustainable BSC system can be helped through the use of external experienced and insightful contributors. This is an example where and when JAMSO helps business leaders and companies define the optimal performance management system without any undue cognitive bias in the design.
Middle management normally have higher emotional intelligence with the workforce than displayed with the C suite leadership, however they can also carry the highest incorrect perception and irrational personal judgment.
Examples that impact best metric choice decisions include:
· A metric is not followed due to the fact that all stakeholders in a task think they are doing a great solid job and the task has not been deemed significant enough.
· The marketing department highlights only the positive results and any significant lower performing results are proclaimed as a success in “branding”.
· A specific customer experience metric is designed to generate a specific outcome and not reveal the full view.
· The board of directors agrees mutually they saw the coming of an event that happened several years ago but blame other factors for their lack of action at the time.
Do you recognize any of the above bullet points or something similar?
The reality of industry analysis is about probability and statistics
A leading business scorecard and KPI suite will thrive on the back of solid industry analysis. This analysis is quickly out of date, can become expensive and the results and conclusions drawn from it, as varied and limited as according to the time, care, quality and scope of the analysis itself. The basis of governmental or industry association standard statistics will impact skew the perspective of the writer of the report and also private supplied “independent” and or academic research will also skew the outcomes with as varied an impact as that of the original scope.
The key objective with the above information is to seek through analysis the most relevant and accurate data sets that apply to your business, region when aligned to your business vision and mission. This structural context then form the basis of your analysis and conclusions which provide the base of your critical success factors, KPI’s when linked to the strategy of the business.
The art, yes I did say art, of good analysis understands the facts, scope, limitations, statistics and probability of significant events. This can be sought through extended analysis in similar industries or identification in trends and shifts in technological change or regulation direction.
Good analysis is not always possible, so it may be more appropriate to create a limited scope and take longer to define the key factors that will become important elements of your measurement system.
What was the quality of research and analysis to form your key metrics?
The real world of business development and metrics
The clear majority of small/medium sized companies (SME) do not have the budget and resources to conduct annual research due to their need for continual cash-flow and grow demands with short time windows. These SME’s are often seen as more agile and faster moving in the markets and yet slowly fall behind the changing demands of the markets and then become replaced by another company that started later but identified the correct trends for the next wave of industry development.
Therefore we mostly see a high financial skew and bias in metrics towards business development in SME’s as opposed to a broader and subjective range of metrics within larger organizations.
To help correct this pattern I put this article together to address metrics by declaring what I call the Biased Scorecard.
The Biased Scorecard solution using statistical significance
My Biased Scorecard solution is to provide the respect to the balanced scorecard theory and rebrand it with a dose of reality. We can see in the above sections how resources, scope and cognitive bias plus internal or external circumstances impact greatly the factors for a successful business wide performance management measurement system.
· Not all elements of the balanced scorecard should/can be made equal
· The speed of change in technology across many industries mean that more customer experience and innovation metrics are the new critical success factors
· Start out with a system that is known to be biased and adjust and change overtime or be prepared to clear out many key staff members and deal with the motivation impacts that occur.
· The scope of your analysis should highlight the significant signals and trends, qualitative and quantitative data should be compared to identify the most important elements.
Example: The rise of big data across the internet should be considered by every business and therefore provided special performance metrics within the innovation section of activity.
Data, trends and projects are often made from statistical values that are simply statistics. If the actual data itself is accurate then outliers of data can provide significant signal or new directions and opportunities to be explored. Also we see the nature of humans that make decisions are equally as open for error. Very few of the errors or frustrations seen with KPI decisions and metrics systems can be boiled down to a single element. It is frequently the convergence of several elements that creates systems that may be less effective than others.
Your business can generate significant value and advantages gained through ensuring quality analysis and independent help is attained when creating business wide measurement systems. This outside help will be able to identify the traps found within cognitive bias especially.
Actions and reflections for the reader:
1. How do you measure your own activities and provide feedback to your corporate measurement system?
2. What will happen if you challenge and engage deeper with the measurement system, decisions and design?
3. When was the last time analysis was conducted and checks made for cognitive bias across management?
4. Please share this article with anyone or any business that you feel can benefit.
JAMSO helps people and business raise their performance and results.