How come there often seems to be no direct connection between the things we choose to measure and the goals we are hoping to achieve? Here are a few examples:

• If a company management’s goal is a sustainable long-term growth, why do they measure their decisions based on IRR (Internal Rate of Return)? The metric is useful for measuring a transaction, but it can likely lead to an ultimate distraction of an enterprise vitality if applied to strategic decision making.

• If a Customer Service organization’s goal is Customer Satisfaction, why do we measure performance of the employees based on how quickly they complete a call with a customer? Driving down the cost of customer interaction is a meaningful operational metric, but there is no profitability if customers abandon your operation.

• If an ultimate goal for Product Marketing is demand generation, wouldn’t it be critical to measure why customers buy your product? “The customer rarely buys what the company thinks it is selling him,” as Peter Drucker said.

According to Clayton Christensen, a professor in Harvard Business School and brilliant scholar of Innovation, the root of this problem is the quality of education offered in our business schools. He makes a great point illustrating how wrong choice of key metrics leads to deconstruction of enterprises and entire industries. Clayton is famous for his efforts to re-focus marketing “a job customers hire products to do” as opposed to product’s specs.

As consumers, we all know that our experience with “products” depends on many factors that are not connected to or even correlated with its specifications, functions and features. Quite often customers are more influenced by how easy it is to deal with the supplier or how reliably a product performs, or how simply and consistently it delivers the outcome we require. Yet when we try to measure customer satisfaction, we ask them to score their opinions about characteristics of the product itself. I do appreciate the elegant simplicity of NPS (Net Promoter Score) methodology and its well-documented correlation with profitability, but what specific action can it suggest to a product manager whose product earns a low score?

Steve Blank, Silicon Valley entrepreneurial marketing genius and the author of The Four Steps to the Epiphany book, seconds Christensen’s opinion about the quality of our business schools and is working on the development of an alternative curriculum that is focused on customer development as opposed to financial engineering. Blank is preaching the importance of customer involvement into a product development that appears to be a no-brainer to me, but apparently is a relatively challenging concept to most marketing professionals according to Kristin Zhivago.

The choice of measurements we make has a dramatic influence on the probability of a startup success, according to Eric Ries—a creator of the Lean Startup movement—who has very interesting thoughts on creativity and innovation. Eric thinks that we prefer to use “vanity” metrics that make us feel good instead of helping us to make quality decisions.

So it appears that according to the experts, institutional indoctrination and lack of intellectual honesty are two major reasons for the gap between organizational goals and performance measurements that negatively affect our probability to succeed in business.

I would like to suggest that our compensation system methodology is the third leg of this proverbial stool. Since a majority of the workforce is not compensated for producing results aligned with a long term goals of organizations they work for, we instead end up measuring what is easy to measure and makes us look good.

I was talking to one of my customers about her experience trying to introduce the use of metrics into the business processes she is managing. Janet is in the gourmet food marketing business and was hoping to use analytics for discovering the patterns of shoppers’ consumption of her products by the time of day, as well as an impact of promotional events on the sales results. The food business, in her words, is a very fragmented environment and even the simplest business process tends to involve a number of companies to perform.

Clear understanding and measurement of the metrics, which Janet is interested in, would bring substantial financial benefits to all of the participants in this process, and yet they passively resist any attempt of implementation. Her frustration level was rising as Janet was describing the excuses she was getting from her customers and partners. They were not saying no to her proposal and even promised to make some information available, but ultimately no progress was ever made. Let’s make it clear that a cost is not a factor, as Janet’s company offered to underwrite the implementation.

“So why do ‘go-get-them’ people usually become so passive-aggressive when the analytics are involved?” Janet asked me. This question made me look back on my experiences, and it occurred to me that they invariably are similar to Janet’s. For over decades of my business career, I was charged with development and implementation of KPI’s many times in large and small companies engaged in different industries, but the outcome is always the same – passive resistance.

There are a few business processes that universally accept and practice metrics. The most common example are Sales and Call Center processes, but anyone who has managed sales forecasting will tell you that the efforts required to drive it are very substantial.

Recent explosion in web analytics technology brought to us a myriad of products that capture, measure and present dashboards of transactional data that may correlate to specific business process performance, but are very far removed from actionable KPI metrics that most of us need to manage business. Even marginal improvement in measuring performance of advertising investment disrupted the entire industry and created new multi-billion dollar players like Google. Imagine what could be done if we could measure actual impact of a given decision on the bottom line results. However, that would not be likely to happen anytime soon because of fundamental characteristics of human behavior – we will go to extraordinary lengths to avoid personal accountability.

The numbers can shine a light on our performance and quality of our decisions that can be too bright and harsh. Our organizational structures and compensation systems are too binary, with a few exceptions, to compensate for actual performance. Too commonly we get and keep our jobs not for delivering exceptional results, but for “fitting in” and showing up on time, for being efficient and working long hours, but not necessarily effective in producing the “right” results.

The key to successful, productive adoption of analytics into organizational fabric is careful selection of only those metrics that measure elements of a process that can be proactively managed by the parties involved to their performance benefit. The fewer relevant, actionable KPI metrics that help to take meaningful actions is much better than dashboards full of charts and numbers you have no control over. Relevancy beats ease of generation and drives user adoption.

My hero, Peter Drucker, is often quoted to say (I paraphrase here) “What you cannot measure, cannot be managed” and this idea inspired many analytic initiatives by large companies as well as by budding startups, like this one. There are hundreds of companies that monitor, listen and analyze every aspect of web traffic, impact of media messages, both digital and analog, and just about anything else under the sun. There is surely no shortage of technology and tools, and current interest from businesses and consumers is quite high, but…there is still not enough conclusive evidence that measuring and managing to the specific parameter can produce measurable result. It often is still a challenge to interpret measurements into predictive models, that produce or support specific actions or decisions. Perhaps it is just my personal, limited experience and I look forward to be proven wrong  in your comments, but for now I would like to propose a few potential reasons for these disappointing experiences.

Is it possible that we often measure wrong things? Many people would argue that NPS (Net Promoter Score) is a meaningless thing to measure and the Social Media influence, measured by Klout and others, does not translate into any specific action. We often measure what is easy to measure, listen to what is easy to hear, without a difficult effort of understanding and interpreting into an action that can produce measurable improvement. Many people find it easy to identify metrics that measure the worth of their work:

salespeople have sales targets, production managers track whether inventory is delivered on time and under budget, but for most of us it is very difficult to associate and measure our direct contribution to the desired outcome.

Perhaps the most actionable metrics are derivative – a combination of a signal, statistics, interpretation and analysis. Measurement of atmospheric temperature and pressure, compared with historic observations and combined with predictive algorithms, do produce relatively reliable weather forecasts. Perhaps measuring multiple aspects of customer experience, compare them with competitive alternatives and combining it with  predictive algorithms, can produce more accurate sales forecast.

Is it possible that we have unreasonable expectations? We often expect direct causation while operating in an open system environment. Business environment is not a scientific experiment and unpredictability of market conditions cannot be isolated to prove validity of specific measurement methodologies.  We only can improve odds, but we often expect certainty. Uncertainty is the reason for any important measurement effort. Measurement improves confidence in a quality of the decision is supports, but it cannot guarantee an outcome, after all according to Warren Buffet “It is better to be approximately right than to precisely wrong.”