The McNamara Fallacy

…and why you should care about it.

Quantitative stats in isolation failed to uncover the true story in Vietnam.

It’s not often I get to indulge my passion for History and pass it off as work. However I stumbled across this post and wanted to share.

Who is McNamara?

The McNamara Fallacy is named after Robert McNamara. As U.S. Secretary of Defense from 1961 to 1968, McNamara was responsible for organizing American strategy in the Vietnam War.

Prior to his role in government, McNamara had learned (via the Corporate world) to put a priority on quantitative metrics. Following along with the professional culture of scientific measurement established under Frederick Taylor, McNamara decided that he could win the Vietnam War by quantifying it.

McNamara tracked the progress of the war by focusing on the ratio of enemy fatalities to American fatalities. As long as there were more enemy deaths than American deaths, McNamara concluded that the military was on the path to victory.

What McNamara didn’t keep track of was the narrative of the war, the meaning that it had both within the military forces of each side, but also in the civilian populations of the nations involved. Instead, he applied the business aphorism that you can’t manage what you can’t measure and treated his metrics as if they were in themselves the definition of success. McNamara insisted that if factors could not be quantified, they were not relevant to the management of the Vietnam War.

The consequences are well known. Despite achieving his metrics, McNamara lost the war.

The failings with this approach

By building a strategy solely around metrics which can be tracked, you run the risk of lacking context behind results. Where McNamara went wrong was by assuming the following:

• quantitative models of reality are always more accurate than other models;
• the quantitative measurements that can be made most easily must be the most relevant;
• factors other than those currently being used in quantitative metrics must either not exist or not have a significant influence on success.

This does not mean that you should throw out your metrics! Instead, it’s important to obtain other data-points (i.e. qualitative) to understand the story behind the numbers.

Avoiding the McNamara Fallacy in Operations environments

The McNamara Fallacy isn’t just a problem for military strategists, it is a common pitfall for Operations Leaders and Continuous Improvement programs throughout Corporate America.

Often, and due to the complexity of most modern corporations and the systems used, we tend to focus on the most easily obtainable metrics — those that can be pulled easily from workflow, CRM, financial and HR systems. We lose sight of the story behind the results. Our vision becomes myopic and the relationship between cause and effect becomes blurred.

It’s important to remember that data-points outside of quantitative metrics exist. For instance, qualitative feedback from frontline staff can be invaluable when combined with quantitative data.

What gets missed with an insatiable focus on outcomes and analytics is the story behind the results. What are the actions that led to the desired outcomes?

Those who are concerned about falling into the trap of the McNamara Fallacy shouldn’t abandon quantitative measurements and metrics. Quantification is a valuable analytic tool, when it’s applied properly.

A prime example of this is the traditional approach to staff engagement. Most large organizations will deploy a yearly engagement survey across their workforce. The results are aggregated and shared back to the staff via an email, team meeting or a town hall. Then what?

70% of staff engagement variance is directly linked to their direct manager. Yet this outcome is often ignored when it comes to annual engagement surveys.

More often, justification behind lack-luster engagement results is written-off due to external factors (‘the team has been working so hard’, ‘I think I know who scored that and they are a bad egg’, ‘the team is frustrated with the recent system migration project’). And yet, it has been proven that that 70% of the variance in staff engagement is driven by their line manager!

Very rarely do we encounter organizations that actively address this variance through dedicated mentoring and leadership training for their managers. Instead, it’s easier to focus on the wrong factors and excuse away performance without truly understanding the drivers behind the outcome.

By broadening analytical techniques to incorporate qualitative data-points, a more complete picture of not only outcomes but how they were derived is unveiled. We start to understand the story and the linkages between action and outcome. We can learn and adjust going forward.