What did you expect?
Benchmarking & Decisions – for better or worse
I recognize that benchmarking is not a new concept. In business, we have learned to appreciate the value of benchmarking at the “macro level” through our deliberate attempts to establish a relative measure of performance, improvement, and even for competitor analysis. Advertisers often use benchmarking as an integral component of their marketing strategy.
The discussion that follows will focus on the significance of benchmarking at the “micro level” – the application of benchmarking in our everyday decision processes. In this context, “micro benchmarking” is a skill that we all possess and often take for granted – it is second nature to us. I would even go so far as to suggest that some decisions are autonomous.
With this in mind, I intend to take a slightly different, although general, approach to introduce the concept of “micro benchmarking”. I also contend that “micro benchmarking” can be used to introduce a new level of accountability to your organization.
Human Resources – The Art of Deception
Interviews and Border Crossing
Micro benchmarking can literally occur “in the moment.” The interview process is one example where “micro benchmarking” frequently occurs. I recently read an article titled, “Reading people: Signs border guards look for to spot deception“, and made particular note of the following advice to border crossing agents (emphasis added):
Find out about the person and establish their base-line behavior by asking about their commute in, their travel interests, etc. Note their body language during this stage as it is their norm against which all ensuing body language will be compared.
The interview process, whether for a job or crossing the border, represents one example where major (even life changing) decisions are made on the basis of very limited information. As suggested in the article, one of the criteria is “relative change in behavior” from the norm established at the first greeting. Although the person conducting a job interview may have more than just “body language” to work with, one of the objectives of the interview is to discern the truth – facts from fiction.
Obviously, the decision to permit entry into the country, or to hire someone, may have dire consequences, not only for the applicant, but also for you, your company, and even the country. Our ability to benchmark at the micro level may be one of the more significant discriminating factors whereby our decisions are formulated.
Decisions – For Better or Worse:
Every decision we make in our lives is accompanied by some form of benchmarking. While this statement may seem to be an over-generalization, let’s consider how decisions are actually made. It is a common practice to “weigh our options” before making the final decision. I suggest that every decision we make is rooted against some form of benchmarking exercise. The decision process itself considers available inputs and potential outcomes (consequences):
- Better – Worse
- Pro’s – Con’s
- Advantages – Disadvantages
- Life – Death
- Success – Failure
- Safe – Risk
Decisions are usually intended to yield the best of all possible outcomes and, as suggested by the very short list above, they are based on “relative advantage” or “consequential” thinking processes. At the heart of each of these decisions is a base line reference or “benchmark” whereby a good or presumably “correct” decision can be made.
We have been conditioned to believe (religion / teachings) and think (parents / education / social media / music) certain thoughts. These “belief systems” or perceived “truths” serve as filters, in essence forming the base line or “benchmark” by which our thoughts, and hence our decisions, are processed. Every word we read or hear is filtered against these “micro level” benchmarks.
I recognize that many other influences and factors exist but, suffice it to say, they are still based on a relative benchmark. Unpopular decisions are just one example where social influences are heavily considered and weighed. How many times have we heard, “The best decisions are not always popular ones.” Politicians are known to make the tough and not so popular decisions early on in their term and rely on a waning public memory as the next election approaches – time heals all wounds but the scars remain.
Decisions – Measuring Outcomes
As alluded to in the last paragraph, our decision process may be biased as we consider the potential “reactions” or responses that may result. Politics is rife with “poll” data that somehow sway the decisions that are made. In a similar manner, substantially fewer issues of value are resolved in an election year for fear of a negative voter response.
In essence there are two primary outcomes to every decision, Reactions and Results. The results of a decision are self-explanatory but may be classified as summarized below.
- Reactions – Noise (Social Aspects)
- supporters
- detractors
- resistors
- Results – performance, data, facts (Business Aspects)
- worse than expected (negative)
- as expected (neutral)
- better than expected (positive
If you are still with me, I suggest that at least two levels of accountability exist:
- The process used to arrive at the decision
- The results of the decision
In corporations, large and small, executives are often held to account for worse than expected (negative) performance, where results are the primary – and seemingly only – focus of discussion. I contend that positive results that exceed expectations should be subject to the same, if not higher, level of scrutiny.
Better and worse than expected results are both indicative of a lack of understanding or full comprehension of the process or system and as such present an opportunity for greater learning. Predicting outcomes or results is a fundamental requirement and best practice where accountability is an inherent characteristic of company culture.
Toyota is notorious for continually deferring to the most basic measurement model: Planned versus Actual. Although positive (better than expected) results are more readily accepted than negative (worse than expected) results, both impact the business:
- Better than expected:
- Other potential investments may have been deferred based on the planned return on investment.
- Financial statements are understated and affects other business aspects and transactions.
- Decision model / process does not fully describe / consider all aspects to formulate planned / predictable results
- Decision process to yield actual results cannot be duplicated unless lessons learned are pursued, understood, and the model is updated.
- Worse than expected:
- Poor / lower than expected return on investment
- Extended financial obligations
- Negative impact to cash flow / available cash
- Lower stakeholder confidence for future investments
- Decision model / process does not fully describe / consider all aspects to formulate planned / predictable results
- Decision process will be duplicated unless lessons learned are pursued, understood, and the model is updated.
The second level of accountability and perhaps the most important concerns the process or decision model used to arrive at the decision. In either case we want to discern between informed decisions, “educated guesses”, “wishful thinking”, or willful neglect. We can see that individual and system / process level accountabilities exist.
The ultimate objective is to understand “what we were thinking” so we can repeat our successes without repeating our mistakes. This seems to be a reasonable expectation and is a best practice for learning organizations.
Some companies are very quick to assign “blame” to individuals regardless of the reason for failure. These situations can become very volatile and once again are best exemplified in the realm of politics. There tends to be more leniency for individuals where policies or protocol has been followed. If the system is broken, it is difficult to hold individuals to account.
The Accountability Solution – Show Your Work!
So, who is accountable? Before you answer that, consider a person who used a decision model and the results were worse than the model predicted. From a system point of view the person followed standard company protocol. Now consider a person who did not use the model, knowing it was flawed, and the results were better than expected. Both “failures” have their root in the same fundamental decision model.
The accountabilities introduced here however are somewhat different. The person following protocol has a traceable failure path. In the latter case, the person introduced a new “untraceable” method – unless of course the person noted and advised of the flawed model before and not after the fact.
Toyota is one of the few companies I have worked with where documentation and attention to detail are paramount. As another example, standardized work is not intended to serve as a rigid set of instructions that can never be changed. To the contrary, changes are permissible, however, the current state is the benchmark by which future performance is measured and proven. The documentation serves as a tangible record to account for any changes made, for better or worse.
Throughout high school and college, we were always encouraged to “show our work”. Some courses offered partial marks for the method although the final answer may have been wrong. The opportunities for learning here however are greater than simply determining the student’s comprehension of the subject material. To the contrary, it also offers an opportunity for the teacher to understand why the student failed to comprehend the subject matter and to determine whether the method used to teach the material could be improved.
Showing the work also demonstrates where the process break down occurred. A wrong answer could have been due to a complete misunderstanding of the material or the result of a simple mis-entry on a calculator. Why and how we make our decisions is just as important to understanding our expectations.
In conclusion
While the latter situations may be more typical of a macro level benchmark, I suggest that similar checks and balances occur even at the micro level. As mentioned in the premise, some decisions may even be autonomous (snap decisions). Examples of these decisions are public statements that all too often require an apology after the fact. The sentiments for doing so usually include, “I’m sorry, I didn’t know what I was thinking.” I am always amazed to learn that we may even fail to keep ourselves informed of what we’re thinking sometimes.
Until Next Time – STAY lean!
Vergence Analytics
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