Hold people accountable for their decisions only

Imagine this scenario. You’ve been given a sales target by your boss. You have three direct reports. You tell each one where you’d like them to focus and set appropriate targets. All three leaders exceed their targets but your department misses its overall target. What rating do you give them on their performance review – fails to meet expectations, meets expectations, or exceeds expectations? This scenario came up during a recent discussion with a leadership group. Half of the group felt that the direct reports didn’t deserve anything above “meets” because the department failed to meet its goals. The other half felt that the direct reports deserved an “exceeds” rating since they exceeded the targets given to them and that the supervisor deserved a “does not meet” since he or she chose the wrong areas in which to focus. I tend to side with the second group. Departments don’t miss goals, people do. In this case the leader was accountable for the overall department’s goal His or her team was accountable for their assigned piece. Rolling the three direct reports into the department’s success creates an unfair and unrealistic level of accountability. You can’t hold people accountable for your decisions or the decisions of others. You should only hold them accountable for their own decisions and actions. I see this problem outside of the business world in the field of education. Teachers often have little input into the focus, curriculum, or policies of their school, yet are held accountable for the quality of learning in their classroom. Teachers should be accountable for their students’ achievement, but they should also be allowed to make the decisions as to how to best foster that achievement. The same is true of leaders and business decisions and results. It's not fair to tell someone to do something and then penalize them because it wasn't the right thing to do. A second area of misalignment in decision making and accountability often comes between corporate and business-facing functions of a company. This misalignment is a bit more tricky due to the often competing goals of the two parts of the business. Leaders in corporate departments need to look out for the welfare of the organization as a whole. Leaders in a specific business unit, while remembering they are part of a larger entity, are usually held accountable for their specific area's results. Therein lies the problem. For example, consider a procurement director who creates a preferred vendor program (in order to reduce costs). Such a director might successfully lobby to require all leaders in the organization to only use vendors in the program. If preferred vendor usage increases and vendors costs decrease, the procurement director is rightfully rewarded. However, what if the new vendor program excludes a vendor (or set of vendors) who are uniquely qualified to help one of the business units and that unit's performance slips? Does the procurement director, whose program excluded these critical vendors get held accountable? No, he or she is rewarded. The business unit's leader is penalized because he or she is accountable for the performance of the unit. Corporate policy is important, but it's unfair to hold someone accountable for actions that were dictated by someone who is accountable to a different set of goals and expectations. The last misalignment between decision making and accountability comes with data. Often departments that gather, process, and report data are not the departments that actually use the data. Standard reports while easier and more efficient for the reporting group aren’t always more effective for the leader who is trying to make a decision. Yet that second group of leaders are held accountable for the quality of decisions made using the standard reports. I’m often surprised at how hard it is for a front-line leader to get the data that he or she needs to run the business. Someone in a data department is making the decision about what data that leader “needs”, what data the leader can use, and the format in which that leader will receive it. There are important legal, ethical, and social reasons to safeguard certain data in an organization. However, when that safeguarding is so aggressive that it squelches any meaningful use of the data, the value of having the data in the first places ceases to exist. If you find yourself in the position of telling someone else what information, people, or resources he or she needs or what actions or investments he or she should be making, stop and step back. Ask yourself whether you will be held accountable if this leader’s performance slips in response to your requirement. If the answer is “yes”, continue on, you have every right to be involved. If the answer is “no”, reconsider your requests or actions. Is there a way to get your need met while enabling the other leader to make the actual decisions for which he or she will be held accountable? All leaders need to take time to assess the alignment between decisions and accountability. In an ideal world, people at all levels would only be held accountable for their decisions and actions. In a practical world, that can’t always happen. But, as leaders we can be more deliberate about whether we hold people accountable for executing our decisions and how far we step into other people’s business when we tell them what they need, when they need it, and what they have to do with it. Brad Kolar is the President of Kolar Associates, a leadership consulting and workforce productivity consulting firm.

Do you have number sense?

In the “Good Cop, Bad Dog” episode of Modern Family, Gloria Pritchett (Sofia Vergara) brings home an aspiring but somewhat naïve entrepreneur named Guillermo (Lin-Manuel Miranda).  She wants her husband Jay (Ed O’Neill), a successful executive, to give Guillermo some business advice.  Their conversation begins like this:

Guillermo:  Are you aware that last year Americans spent $40 billion on dog training?

Jay: Well, that’s not true

Guillermo:  I was surprised as you are

Jay:  No you were surprised because it’s not true

Guillermo: What is this multi-billion dollar industry missing?

Jay Pritchett:  Multi-billion dollars

Guillermo: I have devised a revolutionary way to communicate . . .

Jay has number sense.  He isn’t an expert in dog training nor is that his business.  Yet, he has a broad enough understanding of business to know that Guillermo’s claims don’t make sense.

Recently, on ABC’s World News, Dianne Sawyer stated, “as of tonight, it [The Occupy Wall Street Movement] has spread to more than 250 American cities, more than a thousand countries -- every continent but Antarctica.” (October 10, 2011)

Some people, upon hearing that statement were probably impressed by the movement’s growth and support.

Critics of Sawyer and the movement were quick to jump on her error.  Her statement reflected a number that is five times greater than the total number of countries in the entire world.

It’s unlikely that Diane Sawyer believes that there are that many countries.  She was probably rushed and possibly reading from a cue card.  But, someone gave her that number.  Unlike Jay Pritchett, that person didn’t apply simple number sense to determine whether the data seemed reasonable.  And Sawyer, for whatever reason, didn’t do a quick reality check on the fact she was reporting.

Number sense sits at the intersection of business acumen and critical thinking. 

In the case of Sawyer’s comment, you don’t have to be a geography expert to realize something is wrong with her number.  Some simple logic would cast suspicion. 

·         Sawyer's statement excluded Antarctica leaving just six continents to house one thousand countries. 

·         The remaining six continents would each need to have around 166 countries on average. 

·         Even if you don't know much about the other continents, you probably know that your continent has far fewer than 166 countries.  Therefore, the remaining five would have to average MORE than 166 countries each to make up for yours. 

·         Without knowing specifics, you probably also have some ballpark guesses about other continents either those closest to you or those really big ones with relatively few countries such as North America and Australia.

·         That leaves an even higher requirement for the few remaining continents that you know little about.

It quickly becomes clear that one thousand is an outrageous number.  That thought process was probably even more elaborate than most people would need.

That’s an application of number sense.  It’s not about knowing detailed numbers.  It’s about having a few general numbers/facts on hand and the ability to use them to reason through a problem.

Successful leaders have good number sense.  They can tell if the size of a projected market for their product seems reasonable.  They can quickly think through the bottom line impact of small changes in their business model. 

As a leader, part of your business acumen development should focus on number sense.  By getting familiar with some basic facts and using those facts to vet the claims that you hear you’ll be able quickly to discern good data from data that isn’t credible.

Here are some facts that would probably create a good foundation for your number sense:

General

What is the population of your country? 

What is the population of the countries in which you do business?  About what percent are adults versus children?

What is the population of the world (currently approx. 6.97 billion people)

What is the GDP of your country?

How many households are in your country?

How many people are in your country’s workforce?

Business

What is the size of your company’s customer base?

What is the size of your industry’s customer base?

How many of each of your products are sold in a given year?

How many employees do you have in your company?

What are your company’s annual revenues?

Do you need to look up all the details to know if a fact or figure seems reasonable, especially one that might not be specific to your job, role, or business?  If so, it might be time to brush up on your number sense.

Brad Kolar is the President of Kolar Associates, a leadership consulting and workforce productivity consulting firm.  He can be reached at brad.kolar@kolarassociates.com.

When is enough, enough?

How much analysis is enough?  You can always find more data, more questions, and more procedures that can be applied to data.  It can be daunting.  It can also lead to “analysis paralysis,” which seems to be the main concern of the leaders with whom I work.

Five simple criteria will help you assess the thoroughness of your analysis.  These aren’t rocket science but they will help create some diligence and structure to your analysis.

You’ve probably done a thorough analysis if:

·         You’ve answered your question

·         You’ve used multiple, disparate, and distinct sources

·         The data are consistent –there is low variability

·         The result makes sense and can be explained easily

·         You’ve found the exception (there always is one)

You’ve answered your question

This might seem obvious.  But it’s probably the biggest mistake on the list.  Too often, we jump into the data without clearly defining (or without defining at all) the question we are trying to answer.  We just start reading the reports, left to right, top to bottom. 

Before you jump into the data, figure out what question you are trying to answer.  Then figure out the criteria (or sub-questions) that will help you answer that question.  Now, go answer those questions.  When you are done, you’re done.

But how do you ensure that you haven’t missed an important sub-question?  The answer is easy – talk to people before jumping into the data.  Find out if they agree with the model that you’ve laid out (question and sub-questions).  Ask if there are other questions that you need to answer. 

More importantly, ask the person to whom you will be presenting the data.  That will help you avoid doing unnecessary analysis and will help ensure that you don’t repeatedly go back to the drawing board answering additional questions. It also improves your chances of gaining buy-in on your findings since you already know what that person is looking for.

You’ve used multiple, disparate, and distinct sources

The two most important words here are disparate and distinct.  Using sources that share the same beliefs or agenda isn’t much better than using just one source.  For example, using only environmental organizations as sources of data on global warming might not give you a fully credible view.  Mix your sources.  Often opposing groups use similar data for their analysis.  What’s different is their interpretation of that data.  If two opposing parties use the same data, it is probably pretty credible.  If their data is different, keep searching until you find some common facts upon which both agree.  If you can’t, try to find some additional sources that might be more objective in the first place.  A current example of this is our national debt.  Most politicians seem to agree on the size of the debt.  That number is pretty safe.  There is huge disagreement on how much the debt will be reduced by various proposed initiatives. Therefore, that data is probably more suspect.  The Congressional Budget Office was established to provide an impartial quantification of budgetary information.  On the issue of savings, they are probably a better source than the spokesperson for either political party.

The data are consistent

I monitor my credit score on a monthly basis.  The three agencies never match.  But, they are consistent.  All three paint the same picture of me for creditors.  If they varied widely, that would be a problem.  Keep looking at the data until it begins to converge.  It doesn’t have to match, but if the data is telling three different stories, you need to get some clarity.

The result makes sense and can be explained easily

If you have to take a lot of exotic twists and turns to build your argument, be suspicious.  One of the many reasons cited for the financial crises of the past several years is that financial instruments and analyses became too complicated to understand.  Clarity and simplicity are both results of clear thinking and analysis.  Keep working until your argument is clear, concise, and easily understood.

You’ve found the exception

If all of your data fully supports your conclusion, you might be suffering from “confirmation bias”.  Confirmation bias is the result of only seeking information and data that support your view.  Even the best solutions don’t work every time.  If you’ve looked hard enough to find the exceptions, you’ve probably done a thorough analysis. 

There is always more data and more questions.  However, if you’ve been diligent in your analysis, you can be confident that your conclusions will hold up.  They might not always be right, and there might be something that you missed, but you and your analysis will still be credible.

Brad Kolar is the President of Kolar Associates, a leadership consulting and workforce productivity consulting firm.  He can be reached at brad.kolar@kolarassociates.com.