Define, Measure, Analyze, Improve, Control

Whether we are aware of it or not, we employ these five steps all the time.  In order to solve a problem we first have to understand it (“Define” and “Measure”), then we have to choose a solution (“Analyze” and “Improve”) and to make sure the solution sticks, we have to put some “Controls” in place.   Lean Six Sigma shortens these five steps to form the acronym DMAIC and organizes projects into five phases called Define, Measure, Analyze, Improve and Control.   Each phase deserves careful attention.   Faults in any of them will create problems down the road, either by solving the “wrong” problem, by implementing the “wrong” solution or by creating an atmosphere where the habits that created the problem can re-emerge.   Whether we have to manage a project or try to solve a less complex problem, DMAIC is a good place to start.

Lean Six Sigma Provides Tools and Techniques to Ensure Success

Good business decisions require relevant information and the ability to get it. Elsewhere in this blog I have discussed some of the finer points of relevant information.  Let me focus here on “… the ability to get it” because that often depends on the skills, knowledge and motivation of the humans who provide the information.

Throughout our certification course we spent considerable time sharing real life stories and discussing what it takes to build team consensus, to make team decisions and to prioritize solutions.  Lean Six Sigma provides a toolbox of methodologies from which the adept practitioner can choose the ones that fit the team dynamics and the problem at hand.  The mechanics of these tools are easily learned – the human element can be more difficult to manage.

It takes human judgment and input from people to determine which factors are relevant, to discover where the problems are and to identify which solutions are feasible and should be pursued.  Motivations such as job protection, maintaining a good reputation, demonstrating leadership and controlling one’s destiny are powerful factors that affect not only team dynamics but also what information people are willing to share.   Lean Six Sigma calls itself a “data driven” methodology, but that doesn’t mean it ignores human input.  When used appropriately and with skill, Lean Six Sigma tools help to transcend these human factors by approaching the problem from many different angles and by placing the emphasis on processes and problem solving rather than blaming people.

Lean Six Sigma Is Data Driven

Data and statistical analysis play a central role in Lean Six Sigma and go far beyond the measurement of technical specifications.   Our “gut” will often point us in a good direction, but to get funding and to understand whether and where we are making progress, we need some numbers.  That reliance on “numbers” is explicitly built into the Lean Six Sigma process by requiring us to “Define” our problem, to “Measure” the current state and then to “Analyze” it to determine the best solution.   Hypothesis testing, Chi Square tests, ANOVA, regression analysis, t-tests and a host of other statistical tools used in Lean Six Sigma also work away from the factory floor: they enable us to understand patient motivation, provider opinions, sales rep performance and driving forces in the market place – to name just a few.

Subject Matter Expertise Still Matters

Being able to use Lean Six Sigma jargon like “Cause & Effect Matrix”, “Design of Experiment” or “Value Stream Mapping” doesn’t mean much unless we provide the necessary context.  Usually this means dropping the jargon and applying relevant subject matter expertise.   A “Cause and Effect Matrix” may provide the foundation for translating business priorities into a bonus plan – complete with performance goals and payout curve.  Concepts from “Design of Experiment” apply to “Survey Design” in Marketing Research as well as to “Conjoint Analysis” when we are trying to understand the impact of various market forces.   Creating a “Value Stream Map” may help with restructuring departments and job descriptions to support growth for a provider of healthcare or other services.  It’s not the tool that matters, it’s how we use it.

The Take-Away

Whenever conversations with friends and colleagues turned from abstract to more details about Lean Six Sigma, I started to hear comments like “oh, you’re doing a mini-MBA” or “that’s what I learned as part of my PMP certification” or “hey, this is an idea I can use.”   The discussion above illustrates how these comments came about.  When choosing among consultants, shouldn’t we give priority to someone who has demonstrated their ability to solve problems effectively and efficiently?  I am banking on it, and together with some new insights from class, I now have more than a “piece of paper” to demonstrate that ability to anyone who needs to know

Data analysis tools have advanced to the point where seemingly anyone with basic computer skills can develop meaningful insights.  As with any tool, however, operator skill determines the ultimate outcome.  Anyone can create graphs with trend lines, but knowing how to graph data properly requires skill.

For example, the graphic below appeared in a recent blog post about the impact of Health Care Reform on President Obama’s popularity.  While the trend lines look impressive, this graph misleads the reader.

Four scatter graphs contrasting public opinion about Obama with public opinion about Health Care Reform

It is true that statisticians use scatter plots to show the relationship between two variables, but in this case a third variable plays an overriding role.  This third variable is Time.  Public opinions shift over time, depending on the headlines and the proposed changes in legislation.  A scatter plot cannot take this into consideration. A timeline chart such as the one below proves to be more informative: it shows trends over time and provides possible explanations for shifts in public opinion.

Annotated timeline chart showing public opinion over time

Think about the many graphics we consume on a daily basis, whether in business meetings or in the media. What do we really know about the skill and motivation of the author behind the graphic?  If a graphic supports an opinion we already hold, we may never question it – even if our opinion deserves questioning!

Herein lies the Catch-22: during times of change we have even less time than usual to deal with the intricacies of data analysis.  Yet, precisely at those times do we need to question our assumptions, adapt to new realities and update our opinions.  One way of solving this dilemma: delegate data analysis to people with the appropriate experience and skills.

• What information the organization needs
• Who needs to see what information
• How to prioritize information deliverables
• How often we need to update information

The third step to a successful BI future requires that we

• Set Goals
• Find out what skills we need
• Determine who needs to do what

Of course we also need a budget and organizational support, but for today, we will focus just on Goals, Skills and People.

Setting Appropriate Goals

Much of the discussion around goal setting deals with managing and motivating people to strive for a common goal.  It includes such well known concepts as

Peter Drucker’s MBO (“Management by Objectives”) or

SWOT Analysis based on the work by Albert Humphrey or

“The 7 Habits of Highly Effective People” by Steven Covey or

BHAG (“Big Hairy Audacious Goal”) by James Collins and Jerry Porras.

For our purposes today let us focus on the acronym S.M.A.R.T.  It’s easy to remember and useful for developing the kinds of delivery goals that a BI Manager needs to set and implement.  Depending on the author, the letters S.M.A.R.T. stand for slightly different words.  One such set of words is:

S: Specific

M: Measurable

A: Achievable

R: Relevant

T: Time bound.

A very nice one page summary about setting S.M.A.R.T. goals can be found here.

A hypothetical goal could be: “In six months we will need to deliver sales goals and compensation measures for 50 sales reps, 5 managers and a VP of Sales.”  Let’s see how S.M.A.R.T. it is:

Specific: deliver sales goals and compensation measures for 50 reps, 5 managers and a VP of Sales

Measurable: at the end we either can deliver something or we cannot

Achievable: we know that sales goals and compensation measures are required – failing to develop them simply is not an option.  We also know that achieving goals usually depends on finding the right balance between cost, quality and time. Finding that balance is the key to making this goal achievable.

Relevant: a company does not survive long without sales goals and compensation measures

Time Bound: in six months

It appears that we really do have a S.M.A.R.T. goal on our hands.

Identifying the Right Skills

Today’s business analysis software makes it much easier to perform data analysis and performance tracking without requiring programming skills.  But software alone does not provide everything we need.  Appropriate data has to be collected, processed and made available in a timely manner.  To stick with our hypothetical example of providing sales goals, here is an example list of several skills we will need:

• Understanding of the market place and business goals
• Knowledge about what types of data are needed
• Knowledge about how the data is collected and processed
• Understanding the shortcomings of the data and how to address them
• Ability to make the necessary data available and accessible
• Ability to distribute information in appropriate formats
• Analytical skills to develop meaningful measures, metrics and conclusions

In our hypothetical example we may already have someone on our team who knows all the necessary data sources.  Maybe this person already knows which information from hospitals, doctor offices, contracting and claims systems, SFA systems and a myriad of other sources has to be combined to develop meaningful goals.  Maybe this person already knows how to develop compensation formulas that appropriately reflect business goals using data that is actually available.  Maybe this person also has the skills to process and analyze data and to make it available to everyone who needs it.

In reality it is much more likely that a team of internal and external resources needs to work together to provide the necessary information and insights.

Finding the Right People

The actual list of skills depends on the individual situation, of course.  Sometimes it is useful to develop and maintain the necessary skill sets within an organization, at other times it makes sense to hire specialists.  Budgets, time requirements, available skill sets and long term vision for the organization will help determine the appropriate mix of in-house talent and external resources.

As a whole, the team not only needs technical skills (as outlined above), but also management and communication skills.  To effectively work together, team members need to

• Be able to identify critical issues and communicate them appropriately
• Understand each other’s requirements
• Know their respective roles in the project
• Possess project and time management skills
• Possess people and team building skills

Ideally, our team combines representation from the business side as well as the information side.   For example, developing sales goals requires

• input from all levels of the sales organization
• input from product management and other strategic stake holders
• input from HR and other relevant support functions
• buy-in from upper management
• the ability of the information team (BI, IT, vendors, etc.) to deliver
  • appropriate, accurate and timely data
  • systems to make data available
  • analysis and actionable insights

Managing Growth: Reprise

We began this series of blog posts with the question of how to manage BI growth.  We started with ways to prioritize deliverables, continued with ways to streamline what the BI team needs to deliver and ended with an exploration of the skills and people necessary to deliver what is needed (the article you are reading now).

Managing BI growth requires constant attention since this process never really ends.  For each deliverable we are asked to provide, it is therefore necessary to develop criteria that allow us to determine when it needs to either stop or evolve.  We need to balance available head count and the need for professional development and advancement of individual team members with the information delivery needs of the organization.   We need to keep track of technical developments and the services provided by various data vendors.

As BI managers we periodically need to step away from the daily fires in order to plan ahead.  The steps outlined in this series provide a starting point for doing so.

Many consultants will be happy to do the work – but picking the right one out the bunch requires some planning and foresight.  The journalist’s “What-When-Which-Where-How” approach to story reporting is a good place to start:

1. What needs to get done?
   1. Is critical information lacking?
   2. Is there too much data, but too little useful information?
   3. Does conflicting data have to be reconciled?
   4. Does the business need a new way of looking at things?
2. When does it need to get done?
   1. One time only
   2. Periodically (daily, weekly, monthly, etc.)
3. Which skills or types of experience are required?
   1. Business analytics
   2. Industry experience
   3. Data skills
   4. IT skills
   5. Beginner vs. Expert skills
4. Where should the consultant be located?
   1. Are face to face meetings required?
   2. Can the work be done remotely?
   3. Is access to company data/IT resources required?
5. How should the work be done?
   1. How much team interaction is needed?
   2. Who should manage the project?
   3. Can work results be transmitted electronically?
   4. What types of presentations and reports are required?

Each situation has its own idiosyncrasies, of course, and this list can be modified and expanded as needed.

Relationships Rule!

Earlier we said that this list is only a starting point because the secret ingredient to success is the relationship between consultant and client.  If client and consultant cannot get along, the project sits on shaky ground – no matter how proficient, competent and talented everyone is.

The bottom line:

the Right Expertise + the Right Relationship = Success.