Mental models


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Mental models

  1. 1. Metrics, Measures And Mental ModelsBusiness success can have a lot more to do with the way firms manage theirmental models than with information or technology. But in using theaccumulated experiences of a firm in decision-making, traps can lurk at everystep.Despite all the euphoria around information technology, companies committed tothe use of IT have been failing. Corporations are discovering that acquiringinformation technology is necessary for business survival, but not sufficient toensure success. In their 20 years of research on how corporations use informationfor decision-making, Richard Foster and Sarah Kaplan of global consulting majorMcKinsey, and authors of the recently-published Creative Destruction, have learntthe importance of mental models. These form the framework for all the metricsand measures behind the decision-making process. They show that businesssuccess has a lot more to do with the way companies manage their mental modelsthan with information or IT per se.Governing Metrics and Measures"Mental models" are the accumulated experiences of an enterprise. Theseexperiences are shared company-wide through meetings and orientationprogrammes. These lead not only to the creation of collective wisdom and manyshared beliefs within the company, but also to a comprehensive set of metrics andmeasures to monitor performance. Thus, mental models are the "core concepts of acompany, its beliefs and assumptions, the guidelines for interpreting language andsignals, and the stories repeated within the corporate walls". When well crafted,mental models allow managements to anticipate the future and solve problems. Butonce constructed, mental models also become self-reinforcing, self-sustaining andself-limiting. And as mental models lie dormant below the layer of awareness, theydo not get re-examined at all. As a result, when the external world changes, themetrics and measures of the enterprise go out of synchronisation with the marketrealities. They keep reporting a very palatable "Alls OK-except this tiny bit"feedback, ensuring the right shade of authenticity! This goes on until the firm findsitself in deep trouble one day.Corporations end up often measuring what they wish to measure rather thanwhat they need to measure.A Blindness of Vision Consider John Sculleys experience when he left Pepsi to join Apple Computers.From Apple co-founder Steve Jobs, he inherited a team of whiz-kids who shared astrong vision of transforming the entire world with the Macintosh computer.In his first presentation, Sculley explained to the kids at Apple that market sharewas the most critical measure of performance. He talked about Pepsis ongoingcola war with Coke, and the way Pepsi closely monitors its market share againstCokes, on a day-to-day basis. Jobs whiz-kids did not seem impressed. "What doyou mean by market share when the entire market is being created by us?" theyasked a stunned Sculley.
  2. 2. Mental Models and Corporate BehaviourAll corporations derive their information system from their corporate wisdom, asynonym for mental models. The amount, type, quality, form and preparation ofdata are all determined and controlled by the managements mental model.Consequently, when a mental model is in harmony with the market scenario, theright things (those that show the companys strengths and weaknesses in themarket) get measured. When the same mental model goes out of sync with marketreality, its metrics and measures would not reveal what the company really needsto know.A corporation that sold all it could produce might, therefore, have measured itsprofitability through yield per machine. But even after market conditions havechanged and its products are stuck as finished goods or as work in progress(effectively, work not in progress!) it might continue to use yield per machine as aprofitability measure-at a considerable cost. In a market where competition issevere and working capital is scarce, a better measure might be yield per rupee ofworking capital deployed. Companies who believe they are profitable and that thesales margin is the only thing they need to carefully control often choose aflexible costing methodology that allocates overheads in such a way as to show asuitable sales margin they believe they are achieving!Corporations often measure what they wish to measure rather than what they needto measure. And in measuring what they wish to, the flexibility required to showthe desired result is often built into the system, of course within reasonableflexibility limits. That is why quality gurus advocated the use of information-based management to ensure that mental models and consequently metrics andmeasures do get re-examined periodically through factual data/information.Information-based ManagementOne purchase manager believed that quality of supplies from vendors was poorbecause the finance department did not pay them on time. An objective datacollection by an external consultant revealed that many vendors who were paid ontime did not supply good quality material, whereas many vendors struggling to getpayment were indeed supplying good quality material consistently. When pointedout, the purchase managers instant reaction was: "Dont worry, I will find out howthis mistake has occurred and get you the right data proving my point."Non-moving stock is a key measure for inventory control. If there is an item ofinventory without a single issue taking place in the last say, six months, it getsflagged as a non-moving item.A large manufacturing company saw its non-moving inventory, approaching Rs 30crore in March, dropping to Rs 12 crore in April. The general manager (materials),responsible for inventory control, had picked up a few A class items and issuedjust one item each from those, thereby getting rid of a huge value of stock outsidethe exception list at the year-end. He had done no wrong technically and hisreporting was as per the metrics of performance laid down. If this manipulationwas not observed at higher levels that was because decision makers at all levels
  3. 3. seek data that confirm existing mental models rather than data that contradicts suchmodels.Ladder of InferencePeter Senge made a major contribution by propagating the idea of a ladder ofinference. According to this model, we selectively observe data, add meaning to it,apply our assumptions, and come to conclusions, which are in time reinforced asbeliefs. Actions often stem directly from these beliefs; the danger is that metricsand measurements continue to pick up and project only data and information thatappear consistent with the beliefs held. This is how measurement systems becomeself-sustaining and self-limiting.In a reputed company selling auto spares, the efficiency of the sales counterassistants was measured in terms of how quickly the invoice was made out to thecustomers. The company had a reputation for customer service and also believedthat they had an excellent system of ordering and keeping stocks to match marketrequirements. A process improvement consultant asked the sales counteremployees how many potential buyers came into the store, checked on theavailability and walked out without buying anything. "Very few," said the counterclerks, "perhaps one or two out of a hundred. Our computer system recommendsitems based on precise market requirements to be kept in stock."The consultants study revealed that as many as four out of 10 customers whoentered the store left without buying. But the counter clerks, who strongly believedthey had the right stock, simply did not notice so many people leaving withoutbuying! Also, since their efficiency was measured in terms of invoicing time, theirmind registered only those customers who bought goods.Revalidating Mental ModelsEnterprises need to realise the close connection between mental models and theirmeasurement systems and information technology applications. If the metrics andmeasures are to be contextually relevant, the mental models will have to beperiodically reviewed and renewed.This is not a trivial task, considering that mental models are tacit and lie dormantbelow the layer of awareness. But the imperative of ensuring this has never been sostrongly felt as now, when the life span of organizations is getting drasticallyreduced every day.