Good input - the foundation of good strategy (part 5) How can you assure good data?

In general, the overall approach is to avoid the problems previously discussed.

Missing information - If the data doesn’t exist, we may be forced into presumption. Proper presumption technique will be addressed later in this article. If the information exists but is missing because we have no way to get at it, we must first consider if and how we could create a way to get at the information. For example, can we create a cost accounting system? Second, we must consider the cost (time and money) of creating a way to get at the information and carefully weigh that cost against the considered value of the information. This should be a group decision. If we determine to proceed, this may involve an extensive project. In the interim, we are forced into presumption. Of course if we determine not to proceed we are forced into presumption.

Excessive cost of information - As in the previous situation, we must carefully weigh the cost against the information value. Our defense against error here lies in requiring more than one person to agree to any decision not to acquire information due to high cost. Any time we determine not to pay the cost, we are forced into presumption.

Not knowing how to obtain the information - There are two alternatives. You can develop in-house expertise or you can obtain that expertise from outside professionals. You should do both. Every company ought to have some degree of proficiency in gathering information about customers, competitors, etc. Indeed most companies need greater proficiency than they currently have. There are a number of seminars in the field of information gathering. Among others, Michigan State University, the University of Pennsylvania, Washington Researchers and the American Management Association have such programs. For outside professional assistance check out FIND/SVP (212) 645-4500. They provide quick, inexpensive answers to difficult questions. They have hundreds of research consultants world-wide, and several of our clients have used them to good advantage. Whenever the need for outside assistance arises, we again face the cost versus value of information issue. And if the cost is too great, we are forced into presumption.

Not understanding what information was required – This is a communication error. Both the communicator and communicatee bear some responsibility for accurate communication, but (since the communicatee may erringly think he or she understands) the ultimate responsibility lies with the communicator. The communicator must double check where there is the slightest doubt as to understanding. Specifically, the process leader must double check the homework assignees’ understanding of each item on the following worksheets where there is sometimes misunderstanding; MARKET SEGMENT ANALYSIS (1.1-), COMPETITIVE EVALUATIONS (1.2-), ASSUMPTIONS FOR MARKET SEGMENT (2.1-), TIME WORKSHEET (9.1) and PERSONAL ANNUAL SCHEDULES (9.2). The final line of defense against this problem is to have the prepared material completed early enough so that the process leader can review it in time to have any errors corrected prior to the next session.

Simply failing to do the work - First, there should always be a minimum of four to six weeks between planning sessions - more if there are unusual factors such as intervening holidays, vacations, other scheduled events or particularly heavy workloads. Second, if any party is going to be unable to complete the assignment, they are obligated to make this known early enough so that someone else can pick up the ball. Third, the assignments should be completed early enough so that no last minute emergency could possibly interfere. Fourth, it should be given to the process leader for review a minimum of ten days prior to the next session. Fifth, the consequences are severe enough so that simply failing to do the required work is absolutely unacceptable. Make sure the whole team understands this when making the assignments.

Misperception - There are several things you can do to improve perception. First, be aware whenever you are dealing with perceptions rather than “hard data”. For example, we talk about PERCEIVED OPPORTUNITIES rather than just OPPORTUNITIES. Second, since single individuals are more susceptible to misperception than groups of individuals, involve more than one person whenever you are dealing with perceptions. For example, we use the whole planning team for the PERCEIVED OPPORTUNITIES exercise. This is also why we have the entire planning team review every single bit of homework. Third, a good process leader will probe and challenge perceptions. (“All right, prove it to me.”) Finally, be aware that even with diligent precautions against misperception - it can still happen.

Self-deception - This is perhaps the most difficult of all our input data problems. Self-deception is very closely related to misperception. The same defenses apply, i.e. involve more than one person, have the entire planning team review every single bit of homework and have a good process leader who will readily challenge subjectivity.

Deception from others - With customers, suppliers, colleagues, subordinates, superiors and advisors, unless and until you have total and absolute confidence in their truthfulness under all circumstances (and this is a very rare individual), you should maintain a healthy skepticism whenever they are giving you information that works to their advantage. This is not to suggest cynicism - just healthy skepticism. Healthy skepticism recognizes that people will frequently put a “spin” on information or not reveal information when it is in their best interest (we call this putting one’s best face forward). It also recognizes that some people will lie to us. Outright cynicism on the other hand is reserved for competitors and politicians. With them you should not take anything they say at face value unless you can independently confirm it.

Assumption error - First, assure a good understanding and agreement concerning the specific current situation before formulating the assumption. Second, be sure to give thoughtful, reasoned consideration to your assumptions, including; 1) the root causal factors for any significant uncertainty, 2) potential radical discontinuities (i.e. things that have not happened before) and 3) alternative assumptions or ranges.

Inappropriate presumption - First, any time you presume, question the appropriateness of making a presumption in this particular instance. The only times it is appropriate to presume is if; 1) there is no data, 2) the data is presently unavailable or 3) the cost of data acquisition is inordinately high. Second, be sure to give thoughtful, reasoned consideration, including; 1) examination of all the available evidence bearing upon the matter and 2) alternative presumptions or ranges. Third, give each presumption a confidence rating. “I don’t know” is preferable to a wild guess. Remember, it is better to be knowingly ignorant than to have false knowledge.

(part 6 – optimizing cost/time vs. perfection will appear next week).

Good Input – the Foundation of Good Strategy (part 4) How faulty data arises

The four basic causes of faulty information are:
misperception
deception
inadequate consideration
inappropriate presumption

Misperception - Misperception is a cause of faulty information wherein we see what the situation really is, but we don’t recognize it for what it is. As an example, in watching football on TV you occasionally are sure you see something happen and then find out you are wrong when you watch the replay - misperception.

Deception - Another cause of faulty information is deception. Competitors often try to deceive one another in an attempt to mislead. Customers are sometimes deceptive in an attempt to negotiate a better deal. Suppliers are sometimes deceptive in an attempt to a) make themselves look better, b) make the competition look worse, c) get the order or d) negotiate a better deal. Many politicians are professional deceivers and congenital liars and have the worst public credibility of any group of people in this country. Colleagues, subordinates superiors and advisors may be deceptive in an attempt to a) make themselves look better, b) cover up a mistake, c) gain some particular advantage, or d) sabotage the company. Finally, we may even deceive ourselves in an attempt to avoid facing unpleasant facts. This falls under the category of “wishful thinking”. (We are usually unaware of our self-deceptions.)

Inadequate consideration - Another problem lies in the area of assumptions. When we are dealing with the future, there is very little that we can “know”. Even when it comes to death and taxes there are areas of uncertainty. Any prediction, estimate or hypothesis about what is going to happen is an “assumption”, and it should be obvious that it is uncertain. Good assumptions are grounded upon a clear understanding of the current situation and sound reasoning when considering possible alternative future outcomes. They require thoughtful consideration. Poor assumptions are usually “pulled out of thin air”.

Inappropriate presumption - To “presume”, on the other hand, is to accept something as factual without checking it out. Presumption is inherently risky. On occasion it is acceptable to presume, as when checking it out would be impossible or inordinately expensive and all reasonable evidence leads strongly to a certain conclusion. Presumption does not always lead to faulty information. However, most faulty information is the result of inappropriate presumption.

In summary, the four causes of faulty information are misperception, deception, inadequate consideration and inappropriate presumption. These may be first hand - as when you misperceive, self-deceive, inadequately consider or inappropriately presume. Or it may be second hand - as when someone else gives you faulty information either intentionally or inadvertently (e.g. he believes the information to be correct but it is faulty due to misperception, deception, inadequate consideration or presumption).
(part 5 – How Can You Assure Good Data will appear next week.)

Good Input – the foundation of good strategy (part 3)
How Missing data comes To Be Missing

The five basic causes of missing information are; 1) unavailability of information, 2) excessive cost of information, 3) not knowing how to obtain the information, 4) not understanding what information was required, or 5) simply failing to do the work.

Missing information - Information may be unavailable because it simply doesn’t exist. If so, this is just a fact of life we must live with. On the other hand, the data may exist but there may be no way to get at it. Let me give you a couple of examples. First, closely guarded information about a competitor exists but is not available to you. Another example would be a company that has no system for retrieving and using its cost data. The data exists but is not accessible until a system is put in place.

Excessive cost of information - Sometimes information is available - but at great expense of time and or money - for example, when a very expensive survey would be required. Unless the value of the information is greater than the cost of acquiring it, it would be unwise to do so. Such a decision requires an estimation of the acquisition cost and a reasonable prejudgment of the information value.

Not knowing how to obtain the information - Frequently the information is available but we don’t know how to get it. There is an absolutely staggering volume of information available in the world - if you know how to get it. At times we may seek information in the wrong places. Other times we may not even figure out any place to look.

Not understanding what information was required - On occasion, there may be misunderstanding as to what data is required. For example, when we ask for significant recent events on the MARKET SEGMENT ANALYSIS, we sometimes get information about significant recent internal company events. The respondent clearly misunderstood the question and gave the right answer to the wrong question - thereby not providing the information required.

Simply failing to do the work - Finally, on occasion, we may simply fail to do the required work. (Often accompanied by the lame excuse “I didn’t have time.”)

(part 4 – How Faulty Data Arises will appear next week.)