While assumptions are a worthwhile tool to use within the right context, they can be a double-edged sword ... they can just as easily lead you astray.
Case in point: the results of your research are not at all what you expect ... and perhaps not what you want to believe. Even though you've been diligent in your planning, you're certain that the data must be wrong. Your first reaction is to question your assumptions about the design of your program.
STOP RIGHT THERE! While it's important to check those assumptions, be aware that your bias toward the results you expected might be clouding your judgement. What you might need to question, instead, are your assumptions in analyzing the data. If you expect one thing and find another, it may just be that you've uncovered something important.
One of our clients encountered this bias when they designed a new product for a specific market. When they started to offer it for sale, they got very little traction with it. "Back to the drawing board," they thought. But wait ... this was a team of seasoned experts who put this together. How could they have missed the mark so drastically?
In truth, they didn't miss the mark at all; the product was great! What they missed, initially, was that the value they thought they were bringing to the table was quite different from what the market actually valued in their product. So, what the data was telling them was not that their product design was poor, but rather that they simply needed to position it differently. Once they realized this and corrected their approach to positioning the value of their product, it was so well recieved that it changed the face of their business completely, and it took them to a new level of success both financially and in terms of national recognition within their industry.
Had they gone with their initial assumption that their product design was flawed, they may well have abandoned the new product, and in so doing, they would have thrown the baby out with the bathwater. But they didn't do that. Instead, they questioned their assumptions concerning their intended market (which is what the data was really telling them), and this insight allowed them to launch their business into the stratosphere.
So, getting back to how this impacts your situation, ask yourself what assumptions you're making that are biased by your expectations. What insights might the data (feedback from clients, prospects, staff, suppliers, etc.) actually be trying to reveal to you? Don't let faulty assumptions mislead you. Be diligent in trying to uncover the real messages that your market is sending you.
Yours in Success, Differently.