Insiders often find their opinions carry very little weight. Even data from competitors can seem superior.
In my former job at AT&T Bell Laboratories, I was an internal consultant to AT&T. When I left the company to consult on my own, I found that the same advice I had given as an insider was suddenly given much greater consideration. The only thing that had changed was that I no longer worked for the company. I sometimes joke that the only day in my career I got smarter was the day I left AT&T. But it is no joke. Organizations can fall into a trap when they ignore their own internal voices and decision-making capabilities and rely only on outside sources.
It is natural to assume that the inputs of internal sources (insiders) receive the greatest weight. After all, they’re closest to the decision maker and are known quantities, often with long-term relationships, shared experiences and common goals. But that is not always the case. One common situation involves consultants. Organizations make heavy use of consultants, and senior management often places great weight on their advice. When the consultant’s recommendations reinforce the opinions of insiders, the consultant can give senior management the confidence it needs to proceed forcefully with the insiders’ recommendations.
But when the consultants’ and insiders’ recommendations diverge, insiders frequently find that their opinions carry very little weight. And it is not just consultants who have this advantage. Even data derived from the competition can seem superior. Some years ago as AT&T struggled to get its costs down, the advice of seasoned internal veterans was discounted by senior leadership in favor of WorldCom Inc. figures who later proved fraudulent (Dick Martin, Tough Calls: AT&T and the Hard Lessons Learned From the Telecom War New York: Amacom, 2004).
Given this problem, how should decision makers proceed? First, they should recognize that, consciously or not, they may subject internal sources to tougher standards. They know that insiders can be biased and that their recommendations can lead to personal gain such as promotions, larger budgets or new responsibilities. Additionally, decision makers are well aware of their own internal data quality issues. So even if insiders aren’t perceived as biased, the numbers and the recommendations based on them can be perceived as inferior.
The mistake does not lie in taking these points into account.