Analytics in Competitive Intelligence: Stated vs. Derived Importance
If your company uses market information to make decisions, you are almost certain to be familiar with the ‘Of these items, how important was or which of these would you consider to be first, second, and third most important?’ These questions result in a measurement of stated importance, or those things that are easily identified and verbalized as important.
The Limitations of Stated Importance
While these data are easy to generate and generally seem reasonable at face value, there is evidence to show that decisions based solely on stated importance are subject to important limitations. Those areas of your company’s performance that are identified as most important often do not correlate well, if at all, with purchase decisions. Which means that your company can act on those performance areas identified as most important and yet, no measurable improvement can be made from those efforts. In most companies, that is defined as poor ROI or a waste of money.
For example, through your research, you may identify a performance area with a relatively low performance score and might initially trigger discussion regarding ways to improve the performance. However, you wouldn’t want to do much about it if it had a low correlation to overall increases in market share. For instance, let’s consider this principle in a win/loss setting. Suppose we had created an interview and included the measurement of professionalism of a salesforce against a prospect’s likelihood of choosing a vendor.
Whether the performance rating against the competition was positive or negative, it would be difficult for an executive to understand the impact that professionalism actually has on the company’s sales win ratio. It would be impossible to know how much a change in performance would affect that win ratio. If it turns out that the correlation to the sales win rate is high, the decision to put emphasis on increasing professionalism would be very easy and relatively risk-free. If the correlation were low, resources could be assigned to improve other parts of the sales process.
There is much evidence to indicate that responses on importance scales can be affected by other factors that distort the accuracy of the response, for example. the need to please social demands, cognitive dissonance, and generic importance, among others. In the entertainment industry, for example, television viewers using such scales will continually rate the value of news and information above sex or escapism. However, would anyone wish to predict, based upon these data, whether the ratings of the program The Big Bang Theory will be lower than those of The PBS Newshour?
Thus, there is a much deeper level of insight to be gained from deriving the information from the respondent’s answers rather than taking them at face value.
Stated vs. Derived Importance
The quadrant below shows how actual data from our win/loss studies has plotted on stated importance and derived importance:
Stated importance is plotted on the Y-axis; it represents the average importance rating given by respondents for each influencer’s characteristic or attribute.
Derived importance is plotted on the X-axis; it is obtained by assessing the company’s performance in each influencer and determining (through proprietary modeling techniques) the impact that each influencer had on the sales outcome. The higher the derived importance, the more impact that influencer has on the overall sales win ratio.
- Upper left quadrant: Declared important. This quadrant consists of items that are stated to be important, but which ultimately have little correlation to a respondent’s decision-making process.
- Upper right quadrant: Key influencers. This quadrant reflects attributes that the respondent both states as being important and which prove to be highly influential at a derived level.
- Lower right quadrant: Hidden opportunities. This quadrant consists of attributes that the respondent cannot readily identify at a stated level, but which do impact overall satisfaction at a derived level.
- Lower left quadrant: Limited impact. Attributes in this quadrant have both low stated importance and little influence on overall satisfaction.
Don’t Throw Out Stated Importance
Now, one caveat is in order here. Some performance areas may be ranked high in stated importance, but will be low in derived importance. This doesn’t mean that a company can cut back efforts in the areas of stated importance. They still have an effect on the sales process. When an attribute has a high stated importance, the data are saying that this is a performance area that can’t be neglected without adversely altering the win/loss ratio, but significant improvement may not provide actual gains in the win/loss ratio.
In the end, using the most sophisticated analytics tools to determine the key influencers will eventually provide the greatest strategic decision-making ability for your company. In many cases, this approach has improved company performance much more than gut feeling, reactive competitive intelligence programs, and stated importance measurements.
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