What’s really in the glass?

When making any business decision–from rebranding to evaluating a new market opportunity–it is easy to view the glass as half full. The challenge is to understand what is really in the glass. Even with the best intentions it can be difficult to step back and evaluate the situation with an objective eye.

It doesn’t take long for energy and enthusiasm to build behind a new campaign or product idea. Generally by the time an organization decides to evaluate a decision it has already committed to the new direction. For months a team has been working on the new idea or direction and they have confidence in the plans. As a result when conducting a due diligence review it is easier to see the signs and data that support the decision and difficult to see the ones that do not.

Organizations and individuals alike also fall victim to the what-you-see-is-all-there is syndrome which is why many forecasts and predictions fail. The most notable of these are failures like Pearl Harbor which was overlooked because no one at the time could conceive of an attack on the United States. Nate Silver outlines similar prediction errors in his book The Signal and the Noise: Why so many predictions fail, but some don’t. Stanley Greenberg’s exhibit at the MIT Museum provides another amusing example of model failure. One of his photos features the Pierre Auger Cosmic Ray Observatory in the Pampas region of Argentina. Isolated and flat, the region seemed the perfect place to place the arrays. But the installations kept failing and the engineers had no explanation. They eventually discovered that herds of migratory cattle were rubbing themselves up against the installations to scrape off their dry hides. None of the engineers had considered this possibility when outlining the things that could go wrong.

These tendencies are human nature and require effort and discipline to overcome even for the most seasoned and objective teams. Conducting primary research can be a useful step in broadening your view of the situation. By definition, research takes an outside-in view of the world and provides insights into your customers and prospects. However, internally conducted research can fall victim to the same biases. When designed by an internal team the team’s view of the world informs what is included in the research, and what is not. This may place undue weight on some areas and miss others. When evaluating the results, the data that reinforce the internal team’s beliefs may get more attention and credence than data that conflict with what they believe – most people are looking for data that support what they already think.

Using an outside research firm can help mitigate these issues. Here’s why.

• The outside research firm has no bias one way or another and can approach the research design and data with an open, objective view.
• When designing the research, outside firms are more likely to explore a wider range of issues and give as much attention to the barriers or limitations as the indications that the decision is the right one.
• Research firms serve a wide range of clients and sectors, equipping them with a wide view into various market dynamics. A good researcher can identify where and how the learnings from one sector or situation are applicable to another. This keeps the research from overlooking aspects that should be included in the research. This often includes asking the obvious questions.
• Research firms are staffed by humans who have their own blind spots and biases. But they are different than yours and the combination of the world views will give you a broader picture than either can alone.

If you are disciplined in managing your biases and blind spots you don’t need an external assistance to ensure you objectively evaluate your market assessments and predictions. However, third parties can be helpful as it is human nature to underestimate your biases and to not see your blind spots – they are blind spots after all. The third party doesn’t have to be an outside consultant or research firm. Peers from other business units and product lines can bring an open mind to your evaluation.

Daniel Kahneman’s book Thinking Fast, and Slow provides some practical advice for overcoming our inherent biases and reliance on intuition and snap judgments. Examples include asking yourself questions such as:

• How much do I like this idea? Is that changing the way I am looking at the data?
• How have other similar ideas panned out? Why do I expect ours to be different?
• Are we answering the simple questions, instead of addressing the complex ones?

Regardless of the approach you take the guiding principle is to make the time and effort to ensure you are taking as wide an objective view of the situation as possible.