Leading with Data Competencies – Business Acumen

Is a pre-tax profit margin of 7% good?  Be careful before you answer.  It’s not as obvious as it might seem.  The answer is - it depends. 

For WalMart, whose 2011 first-quarter pre-tax profit margin was 5.5%[1], 7% would be welcomed news.  However, for Nordstrom, whose first-quarter 2011 pre-tax profit margin was 10.5%[2], 7% would be a disappointment.  Numbers and data have no meaning without context.

Given that Nordstrom’s profit margin is nearly double that of WalMart, who’s making more money? 

It’s not even close. WalMart comes out on top.  Does that surprise you?  If it does, you may be confusing profit and profit margin.  The first is an absolute number, the second is a relative number.  Walmart makes less profit on every dollar of sales.  However, their sales were almost fifty times greater than Nordstrom.  As a result, WalMart’s first quarter profits were almost one and a half time greater than Nordstrom’s sales.

Does this mean that one company is better than the other?  Not at all.  Each company has its own model, value proposition, and way of doing business.  Without understanding what those are, it’s impossible to make effective decisions and take actions on data.

This is the essence of Business Acumen.  Having business acumen means understanding the content and context of business in general, and of your business in particular.

Business Acumen is a hot topic.  Increasingly, I see it appearing on more leadership and general skills competency models.  However, while there is strong consensus that it is needed, there seems to be less consensus about what it looks like. In some leadership models, Business Acumen simply means knowing what’s currently going on inside and outside of the business.  In other models, it is a more formal, MBA-like foundation in the art and science of business.  To be effective at leading with data, leaders need a broad understanding of business.  I divide this into three categories:

·         General business understanding

·         Understanding your industry

·         Understanding your company

Within each of these categories, leaders need content knowledge (what things are and how they work) and context knowledge (what is currently happening in this area).  Content is relatively static.  It can be learned once (and might need an occasional tune-up).  Context, on the other hand, is dynamic and requires on-going attention.

This holistic model of business acumen most effectively positions leaders to make sense of, interpret, and act upon data.

The remainder of this essay outlines key considerations for each area of this business acumen model.

General business understanding

Many leaders are running parts of a business not because they know a lot about business but rather because they know a lot about their particular process or function.  That’s a good starting point, but it’s not enough to make good data-driven business decisions. 

A content-based understanding of business understanding the mechanics of how business work:

·         What are the parts of a business?

·         How do businesses make money?

·         What are the general processes and functions of a business and what do they do?

·         How are businesses organized (corporations, partnerships, co-ops/mutual companies) and what are the implications of those structures on the way the company is run?

·          How do businesses keep track of and use money (basic accounting and finance)?

·         What are the standard business reports? (e.g., income statement, balance sheet, etc.) How do they work? What information do they provide? What decisions and actions do each type of report support? 

Contextual business understanding involves knowing how businesses are changing, new techniques for running businesses, and the macro-economic, social, technical, and political dynamics that influence the way businesses operate.

Once a leader understands how businesses work in general, he or she is ready to think about how those principles apply within their industry.

Understanding the industry

A content-based understanding of an industry involves knowing how the industry, as a whole, functions:

·         What are the different ways that companies in this industry go to market (e.g., high volume, low margin or low volume, high margin)?

·         Does the industry tend to have a lot of collaboration or competition among its members?  Is the industry heavily regulated?

·         Does the industry focus on business-to-business or business-to-consumer (or both)? 

·         How do companies in this industry make money? 

·         What are the different types of value propositions that companies in this industry bring to the market? 

·         Which functions and processes tend to be strategic/market facing and which tend to be support functions? 

·         What are the best practices for the various functions and processes associated with this industry?

A contextual understanding of the industry involves knowing what is currently happening among the players in the industry.

·         Who are the key players in the industry?

·         What innovations or “game changers” are emerging?

·         What new trends exist in supplier or customer behavior?

·         What key plays are different companies making?

·         How will pending or new legislation affect the industry?

·         Is the industry in a growth, mature, or declining state?

·         What innovations or practices from other industries can be adapted to this industry?

Maintaining contextual knowledge of the industry requires staying abreast of what is happening outside of the organization.  It requires attending conferences, keeping up with the news, and exploring other industries.  In many cases, the payoff won’t be immediate or directly applicable to the leader’s day-to-day role.  As a result, many leaders make contextual knowledge of their industry a lower priority.

Each business within an industry operates in a unique way.  That’s why the final and possibly most important type of business acumen is knowledge of your own company.

Understanding the company

Companies have their own specific value proposition, business model, and ways of doing business.  Some emphasize quality and service while others might emphasize price and availability.  Some might outsource most of their functions while others might do everything in-house.

Understanding how your company works is critical for leading with data.  Too often, leaders fall into the trap of pulling a “page” out of a successful company’s “playbook”.  Robert I. Sutton and Jeffrey Pfeffer describe this problem in their book, Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-based Management

“The problem lies with the way that benchmarking is usually practiced: it is far too “casual.” The logic behind what works at top performers, why it works, and what will work elsewhere is barely unraveled, resulting in mindless imitation.

…a pair of fundamental problems render casual benchmarking ineffective. The first is that people copy the most visible, obvious, and frequently least important practices…. The second problem is that companies often have different strategies, different competitive environments, and different business models—all of which make what they need to do to be successful different from what others are doing. Something that helps one organization can damage another. This is true particularly for companies that borrow practices from other industries, but often is true for organizations even within the same industry.” (page. 7)

There are four different perspectives that a good leader has with regard to his or her company.

Functional

·         What are the key functions in the organization? 

·         What is the role of the function?

·         For what outcomes is the function responsible?

Process

·         How do information (data) and physical materials move through the organization? 

·         How does the company determine what products and services to provide? 

·         How does it get people interested in those products and services?

·         How does it create and deliver those products and services? 

·         How does it manage, track, and control all of those processes and services?

Financial

·         How does money move through the organization? 

·         How is a customer’s dollar translated into profit/loss or shareholder value?

·         What are the company’s greatest expenses?

Economic

·         How does the company fit into the broader economy? 

·         With what other industries does it interface? 

·         Who are its direct and indirect competitors? 

·         How do different market forces impact it?

A contextual understanding of the company involves knowing what is happening inside and outside of the company across those four content-based dimensions.

·         What are the current goals, challenges, and initiatives? 

·         What types of threats exist from the outside? 

Contextual understanding requires a leader to keep up to date with information that might not directly relate to his or her job but is essential to the company’s success.  Often this information is treated as “nice to know” and cast aside while the leader focuses on the day-to-day minutia of his or her department.

In order to lead with data, a leader must first understand the “story” of his or her business, the industry in which the company operates, and the external economic, political, and social forces that are influencing the way businesses run.  Without that understanding, the leader has little to add to the numbers on the page.

Brad Kolar is the President of Kolar Associates, a leadership consulting and workforce productivity consulting firm and is the co-author of The Brain Advantage: Become a More Effective Business Leader Using the Latest Brain Research.  He can be reached at brad.kolar@kolarassociates.com.

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[1] Forbes.com, http://finapps.forbes.com/finapps/jsp/finance/compinfo/Ratios.jsp?tkr=jwn

[2] Forbes.com, http://finapps.forbes.com/finapps/jsp/finance/compinfo/Ratios.jsp?tkr=jwn

Leading with data competencies – Leadership Courage

For time and the world do not stand still. Change is the law of life. And those who look only to the past or the present are certain to miss the future.

John F. Kennedy

Be willing to make decisions. That's the most important quality in a good leader.

General George S. Patton

Looking ahead and making decisions. Those are among the most important things that good leaders do. But, both are risky. Both require that you lay your experience, perspective, and judgment on the line. And your experience, perspective, and judgment might be wrong. That’s scary. That’s why Leadership Courage is an essential element of Leading with Data.

The past and present are safe
Too often leaders focus on using data to report current events rather than resolve future issues. It’s easy to talk about the present. There is very little personal risk. But past and present data don’t generally provide insight. Sure, they provide information. But information isn’t enough to create change. Change requires interpretation and speculation. Gökce Sargut and Rita Gunther McGrath make this point in their September, 2011 Harvard Business Review article, “Learning to Live with Complexity” when talking about the use of “lagging” (backward facing) data and “leading” (forward looking) data:

If the bulk of your information is in the lagging bucket, that’s a warning sign. Basing decisions mainly on lagging indicators is essentially betting that the future will be like the past. At least some of your information should be in the leading bucket. This information will be fuzzy and subjective by definition: The future hasn’t happened yet. But without it, you’re apt to be blindsided by change.

It’s ok to speculate
For some reason, speculation has gotten a bad rap. That’s probably because the term has become interchangeable with “guessing”. Speculation is not guessing. It’s not random or irresponsible. It is what separates good leaders from the rest of us.

I recently worked with a leader who wouldn’t make any statements that he couldn’t conclusively prove with data. This limited him to only talking about things that already happened.  For example, this leader had a rock-solid case that the company’s sales force was ineffective and was inconsistent in their application of the sales processes (which most people probably already knew). His leadership didn’t need more data on the problem. They needed a solution. And, no matter how much data you have, recommendations are always speculative. Because this leader refused to speculate, his meetings and conversations never moved the organization forward. He had a well-documented root-cause analysis, but it didn’t provide a solution. Ironically, his assumption that sales would improve if they addressed the process inconsistency was speculation. He only had data that the problem existed. He had no proof that fixing it would change anything. Staying in the present doesn’t prevent speculation. It only delays it. At some point, you need a solution. All solutions and future actions, even if grounded in data, are speculative. Being scared to speculate means being unable to move forward.

Good leaders move beyond discussion of current events. They interpret those events. They combine them with their experience and project what might happen (or what should happen) in the future.

If you aren’t talking about the future, your organization will repeat its past.

Making decisions
The second critical aspect of leadership courage is making decisions. There are two decisions that leaders should be making on a regular basis:

1. Assessments of the current situation
2. Required actions

Surprisingly, many leaders shy away from both. How often do you hear leaders present their current results by simply stating whether they are hitting or missing their targets? That’s safe. Everyone is looking at the same data. There isn’t much risk in saying aloud what everyone else is reading.

Instead of simply stating that the department missed some of its targets (which everyone could see on their own) an individual with leadership courage might say:

Even though we saw a slight dip in performance, we are still in good shape and will end the year strong.

or

Our performance is down but it is primarily due to our leadership team in the Southern region. We are going to bring in some new leaders to turn things around. At this point, we don’t believe that we need to make changes outside of that region.

While these statements appear simple, they provide two things that a rehash of the data doesn’t: 1) an opinion of the implications of the data and 2) a proposed action.

Assessments and actions drive business forward. But they require courage. As soon as you move away from the data and start interpreting it, you might be wrong. You might disagree with your boss. Or, you might ruffle some feathers. Leaders who worry about such things will often just opt to pass along the facts. Are you willing to take a stand? Do you talk in terms of assessment and action or data and facts? If you are sticking to the facts, you may be playing it safe. You also may be stalling progress.

Of course, just with speculation, assessment and actions must be based on data and not desire or hopes. Leadership Courage isn’t about manipulating or ignoring data to make a point. Leadership Courage is about being confident in the conclusions you’ve drawn and the process you used to draw those conclusions. In fact, individuals with the most leadership courage put all of the data on the table, even those that contradict their opinion.

Leading with data requires the courage to take a stand, develop a point of view, and recommend actions. None of those is certain and all are risky. Leaders who step up to the challenge and take the risks will be the ones who help drive their business forward.

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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.

Leading with Data Competencies – Critical Thinking

These days, you probably spend a lot of time looking at and thinking about data. However, due to the vast amount of data that you encounter, you may not be thinking about that data critically.  This might put you in a reactive mode, making knee-jerk or even misguided decisions.

Many of the leaders with whom I work struggle to think critically about their data.  They either dismiss it outright (e.g., “Our data is never credible anyway”) or accept it at a surface level and try to make decisions from discrete, incomplete facts.  But, it’s not entirely their fault.

Our brains aren’t optimized to work with data.  In fact, our mind often gets in the way.

A famous example of this is the “Invisible Gorilla” experiment by Dan Simons and Chris Chabris (If you haven’t experienced this experiment, click on the link and play the video). The experiment shows how we can miss information that is right in front of us. At the other end of the spectrum, Roger Shephard created an illusion, “Turning the Tables”.  In this illusion, you actually see something that isn’t there – a difference in the size of two equally sized parallelograms. 

These two examples counter the common myth that the main barrier to good decision making is having the right data in front of you.  Good data is important.  But often the data is there, it's just being misinterpreted.

Instead, a good leader must have the ability to think critically about what he or she is seeing.  Critical thinking isn’t the same as analytical thinking or problem solving.  It’s easy to fall into the trap of doing either without thinking critically.

Critical thinking is thinking about what and how you are thinking.  It’s a type of reasoning through which a person challenges his or her own understanding, beliefs, attitudes, and interpretations as well as those of others. What makes critical thinking difficult is that it requires acknowledging an element of uncertainty to our judgments.  The result is continual scrutiny of a topic by questioning its validity.  This doesn’t mean that you should fall into “analysis paralysis”.  But it does mean that you should look beyond the first reasonable answer to find the most legitimate answer.

Leaders who just take data at face value often miss the important insight hidden deep within the context surrounding that piece of data.

What is your data telling you?

One organization’s customer service survey asked customers if they received a follow-up call after service was rendered.  The company had a target of 80% follow-ups.  The results from the survey looked like this:

Most of the leaders to whom I show this data come to two conclusions:

1)       The company, in general, should put more effort into making follow-up calls

2)       Departments G, D, C, and J, in particular, need to step up their follow-up call activity.

Sound reasonable?  It might be, but it also might be totally wrong.

A common critical thinking error is taking a metric’s name or a report’s column heading too literally.  Therefore, a good first critical question to ask is what specifically the data represent. 

In this case, you might think that answer is obvious – it’s the percentage of follow-up calls being made.  But that’s not quite correct.

Remember, these data come from responses on the customer satisfaction survey.  Therefore, they are a measure of the number of customers who reported receiving a follow-up call, not the number of calls placed.  Any calls made after the customer took the survey are not included.  Or, suppose that customers define a follow-up only as a call in which they actually spoke with someone. Voicemail messages would also be discounted. 

Telling managers to step up the number of calls might result in confused looks. Their staff might be following up 100% of the time.  However, they might just be leaving messages or making the calls after the surveys are completed.

Does it matter?

Suppose that the leader determines that his or her people are not adequately making follow-up calls. At that point, does it make sense to put more resources into improving the numbers?  After all, they aren’t hitting their target.  But, a critical look at the data might tell a different story. 

Before committing resources to increasing follow-up calls, it makes sense to challenge that assumption that in every area follow-up calls have a positive impact on the business (note: if this has already been proven, there is no need to re-create the wheel. However, often practices are adopted because they seem reasonable as opposed to having been proven effective).  Otherwise, you might be optimizing a metric that doesn’t matter. 

Generally it’s hard to find an insight with just one discrete fact.  Insights come from finding relationships and relationships require at least two pieces of data.  The customer satisfaction survey has a lot of data aside from the follow-up call question.  The leader also has access to data outside of the survey. So, why limit yourself to drawing conclusions from just one number?

The following table compares the rate of follow-up calls (as reported by the customer) and customer satisfaction.  The second column shows the percent of time that customers report receiving a follow-up call after service is rendered.  The third column shows the average level of customer satisfaction. (0 is worse, 100 is best).

What does this data tell you?  What would you do with it?

At face value, the data seem to be pretty clear – more follow-up calls leads to more satisfaction.  Or do they?

Confusing correlation and causality is another common and dangerous critical thinking mistake. This often happens because our brains are wired to find connections, even when they might not exist.  The leader who jumps to the conclusion that follow-up calls impact satisfaction and therefore advocates for more follow-up calls is falling into this trap. 

Instead, the leader needs to challenge that natural assumption of causality.  He or she can do this by asking two critical questions about the nature of the relationship:

a)        Do follow-up calls impact satisfaction, or

b)       Are follow-up calls just one of many things that high-performing departments do? 

A quick and simple test can answer the question.  Instead of just comparing the number of follow-ups to the level of satisfaction, the leader can compare satisfaction in those people who receive calls and those who do not.  If there is a difference, then there is causal relationship.  If there isn’t a difference, then it is just a simple correlation.  The following tables show these two different scenarios.  The second column in each table shows the average satisfaction level among those who did not report receiving calls.  The third column shows the average satisfaction level among those who did receive calls.  The final column shows the average overall satisfaction for the department.

Scenario 1: Causal Relationship

In this scenario, there is evidence that follow-up calls impact satisfaction.  Therefore, putting more resources into making follow-up calls is probably a good idea.  But, that might not always be the case.  The next scenario would provide the same high-level results (overall relationship between follow-up calls and satisfaction).  However, it tells a very different story.

Scenario 2: Simple Correlation

In this case, while there is a correlation between follow-up calls and satisfaction, there is no causal relationship.  Increasing follow-up calls would have little impact on the business (other than the negative impact of wasting resources that could be put on higher impact activities).  In fact, according to this data, increasing follow-up calls in departments C, F, and I could actually have a negative impact on the business (although slight).  A better response would be to monitor calls in those departments to find out why they might be making customers less satisfied. Note the use of the word “might”.  This is another opportunity to think critically and not jump to the conclusion that the calls are reason for the lower satisfaction.

You can do all of the thinking and testing described in this essay in a matter of minutes.  It doesn’t take long or require a lot of additional analysis to think about data more critically. It just takes discipline, practice, and a different mindset. 

You are probably already asking questions when looking at your data. Critical thinking just changes some of those questions.  It also requires an understanding of your business and your metrics.  If you find yourself trying to make decisions off of your high level reports, take a step back.  Learn to ask critical questions to ensure that you understand what the data is telling you. Ask enough questions so that you don’t see things that aren’t there or miss things that are.

Having good data is important.  But understanding that data and being able to question it and find insights is more important.

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.

Developing leaders who “lead” with data

This  entry is the first in a series of four on developing leaders who lead with data.

Organizations are scrambling to improve their people’s ability to use data to lead their business better. But many are focusing on the wrong thing. The problem is that they often focus on the data part rather than the leading part. Roger Martin, Dean of the University of Toronto Rotman School of Management, summarized the problem in his March, 2011 HBR column, "Don’t get blinded by the numbers”:

“Over the past couple of decades this management-by-numbers game has gained currency. The huge amount of data captured by IT and the growing sophistication of econometric modeling encouraged nearly everyone to believe that a firm’s success was driven by the quantity of its data and the ability to model them…More and more we’re coming to see that strategy is as much about interpreting as it is about analyzing. This kind of approach requires completely new abilities. The successful strategists of the future will have a holistic, empathetic understanding of customers and be able to convert somewhat murky insights into a creative business models...”

Course in Six Sigma and business statistics provide an important foundation. But they aren’t enough. It’s not just about the numbers. Leaders need more.

People who lead with data have three key skills or attributes: Critical Thinking, Leadership Courage, and Business Acumen. Placing your bets in these three areas will increase your organization’s success at using data to drive decisions and actions.

Critical Thinking
Leaders often tell me that if they could just get a hold of the right data, they’d be able to make the right decisions. Data and facts make leaders credible; they don’t necessarily make their insights valuable. Too many leaders look at a number and attempt to jump into action. The problem is that the insight generally isn’t sitting within a number on a page. The insight requires, to use Roger Martin’s term, some interpretation.

Current neuroscience research has found that our unconscious minds often squish, squash, re-arrange, and re-configure data many times before we actually become aware of it. “Seeing is believing” just isn’t true. More often than not, “Believing is seeing”. Your experiences, thoughts, expectations, and memories often have a greater influence on how you view the data than data has on your thoughts and experiences.

Given these issues, a good leader must have the ability to think critically about what he or she is seeing. Is it really what it seems to be? Is it somehow being distorted? Is there more to the story than meets the eye? Leaders who just take data at face value often miss important insights. Those insights tend to be hidden deep within the context surrounding that piece of data.


Leadership Courage
I once worked on a project to help a client assess their readiness to serve a new market demographic. The data couldn’t be clearer. They were not even close. Yet, no one was willing to put that statement in their final report. They were too concerned that they might be wrong, look bad, or “rock the boat”. So, they passed the data along in a neat little package to their executives. The executives then had to wade through the data to come to the conclusion that everyone else already knew but wouldn’t say.

These leaders weren’t unique. Few leaders are willing to go out on a limb and state their interpretation of the data. There is just too much risk. It’s always easier and safer to pass along facts. It’s also less efficient.

Companies that drive decisions and actions, talk about decisions and actions (not data). They don’t keep passing off the responsibility to make those decisions or recommend those actions.

Business Acumen
There are many reasons that leaders don’t draw conclusions or build a story around their data. However, lack of a thorough understanding of the business is one of greatest contributors.

Many organizations still promote people to leadership positions because of functional or technical ability, not understanding of the business. Often these leaders continue to view their world through the myopic lens of the function or role from which they came. They can report KPIs and process metrics but often don’t fully grasp how those numbers impact the overall goals of the business. The result is that they speak in numbers rather than insights, decisions, or actions.

It’s simply not possible to draw conclusions or insights from data if you don’t deeply understand the business to which that data apply. How can a leader ask questions about correlation and causality, if he or she doesn’t understand the dynamics of the business?

Business acumen comes in three parts: understanding how businesses work in general, understanding your company, and understanding your industry. All three can be further broken into content and context understanding. Content is facts about how something works. Context is what is currently happening relative to those facts.

A good leader is able to add content knowledge and contextual knowledge to data. This enables him or her to tell a compelling story about what is happening in the business and what to do about it.

Leading with data isn’t about numbers

People who “lead” with data don’t actually let data play a leading role in their conversations. Instead, they lead with insights, decisions and actions that are supported by data. If your development programs aren’t building Critical Thinking, Leadership Courage, and Business Acumen, don’t be surprised if all you get are numbers.

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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.