“In God We Trust, Everyone Else Bring Data”, read the sign outside the office of one of the Dell executives with whom I worked. His mantra was reasonable and compelling as data-driven decision-making is a sound business practice. Over the years, however, I have found that living by this creed can be at times productive and counter-productive. So how could data-driven decision-making be counter-productive? Simple: when you do not have the data.
In the "limited” or “bad data" environment, where we find ourselves from time to time, managers who live by the “we must have data!” motto are crippled by their inability to make decisions. Have you ever heard the statement, "We can't make that decision until we have all the data?" If you have the luxury of putting off or not making a decision, then wait. However, business needs or competitive pressures often require that we make a decision regardless.
What should you do in this situation? I recommend that you enlist the most knowledgeable team members about the decision and walk them through a structured process of soliciting, debating and synthesizing their judgments. You've made an investment in these team members for their knowledge and experience; it’s time to get a return on that investment! You will find in the absence of data, your knowledgeable team members inform your decisions far better than you think. Ultimately, as my current colleague reminds me, “Not Making a Decision is a Decision to do Nothing”.
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7 comments:
The online decision maker and this How
to Become a Creative Genius article at lifehack.org might give you some ideas for better decision making.
I like the How to Become a Creative Genius article; thanks. I wish all decisions were as easy to make as the online decision maker makes them.
In such circumstances, I have seen three general approaches: the manager makes a (snap) decision; the experts consult and make the decision (through some synthesis); the organization collects the data and makes a data-based decision.
I have found that the best way to select between these options is to use decision analysis: what is the cost of delaying the deliverables (to make a data-based decision) vs. the potential cost of rework if a bad decision is made right now? The cost of rework is generally the probability of making an incorrect decision times the cost of delay associated with collecting the data. Additional costs may include loss of brand image and added delay between the decision and the start of data collection.
Preparing for such decisions well in advance is crucial to obtaining fast answers.
Thank you for your comment Tom. I concur with the three general approaches that you describe and like your recommendation for deciding between these options. Do you find that your organization or client organizations readily use decision analysis to determine which decision approach to use?
I find that getting my colleagues to use decision analysis has been an uphill battle. They are unfamiliar with the tools, and management focus is too often on making snap decisions or soliciting a snap decision from resident experts. Even in cases where synthesis is desired, the timing is usually such that developing a correct synthesis from the experts is impossible; the step where one defines ones objectives is frequently skipped.
The key, as I indicated, is preparing for such decisions in advance. Laying the groundwork by identifying goals and developing simple economic models of projects early enables fast yet accurate decision-making later on. Unfortunately, people too often respond only to the current crisis. To overcome this cultural bias, we have been working on upper levels of management to take a more evidence-based approach (using Six Sigma to lay the groundwork for this) and advocating among the lower levels of management to adopt decision analysis techniques.
I too have found that managers are more comfortable talking about the alternatives than their objectives. Defining the objectives, we believe, is the most important step in the process.
I like your approach for helping your organization understand the cost of delaying the deliverables vs. the potential cost of rework of a bad decision. I would love to see an example of this analysis.
We've found that building on small wins has been a successful way to attract management attention and commitment to using decision analysis. We like to find important, but not bet the business decisions, where we know we can reach a successful outcome inside of 1-2 days (spread over a number of days is ok).
Finally, I tend to downplay the fact that we are using "decision analysis". I focus more on the collaborative decision making process and that we are helping to make the typical BOGGSAT meetings more productive by bringing a structured approach to capturing and using management judgment and intuition.
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