Status Quo Begets Status Quo

I have been listening to the book Brave New Work by Aaron Dignon. Have you read it? I find it very interesting. 

When talk we (I) think about Process Behavior Charts (PBCs), it is usually in order to filter out the “noise” and highlight any “signals" in our metrics; to determine if we are still within the Natural Process Limits (NPLs). A PBC that stays within the NPLs indicates the system which the metric is monitoring is working as it was designed. Any data outside of the NPLs is one (of three) of the signals that indicates something has changed in the system, necessitating the need for closer scrutiny.  A PBC is referred to as the “Voice of the System” (VOS).

But the corollary to this is: 

If you are not happy with where the metric is charting, then in order to improve the chart, it means changing (improving) the system; the thinking and approach. 

As Dignon points out, if we want a 10-fold increase in production, we pretty much intuit that that will require major changes in our thinking and approach; the system. But, if we are only looking for a 10% improvement, somehow, we think that that can be achieved by "status quo " thinking. He calls this the "status quo bias." Any change in the metric requires a change in the system; the thinking and approach.

Even the modest 10% change will require different thinking and approach. Status quo thinking will only lead to status quo results. So, when the Practice Manager or area director (or even the C-suite) issues a new goal or benchmark for the new year or next operating period, then our response should be, "Great!! What are you all going to change within your thinking and approach (the system) to result in any chance of hitting that new goal?” Because, without that change first, the new goal 'just ain't going to happen!' Commanding it to happen or incentivizing it to happen or threatening if it doesn't happen will not make so.

Status quo begets status quo!

Remember, operational systems are created by and are the responsibility of Management. Workers are at the mercy of systems! 

Come join Mark Graban and I at the 2020 AVMA Veterinary Leadership Conference in Chicago as we facilitate the audience participation workshop of W. Edward’s Deming’s “Red Bead Experiment” which was designed to illuminate these concepts and more. 

A Different Kind Of Rounds: Lean Daily Management

As doctors and veterinary staff, we are well acquainted with the daily ritual of morning or change of shift medical rounds. This is the gathering of hospital staff and doctors to be updated on the current status of all of the patients in the hospital for treatment, and for the dissemination of new treatment orders by the doctors in charge. This is a form of standardized work. It gets everyone on the same page in a routine and timely manner.

Lean Daily Management (LDM) serves the same purpose, but for the operations and management side of the practice.



Each morning, leadership and management go to the gemba to meet with staff of a particular area of the practice to go over that area's board. What numbers are up (and why?) and what numbers are down (and why?). Or, better yet, do the Process Behavior Charts (PBC) of the data show any "signals" or is it all just "noise?" (see also Mark Graban's book "Measures of Success") What countermeasures should be tried? Any new kaizen ideas? What, if anything, can management do to support the staff? Any evidence that standardized work is not being followed?

Sidebar: One of the two Process Behavior Charts above is showing two signals. Can you identify which chart it is and what the signals are?

LDM helps support our progress through that big PDSA cycle called hoshin kanri or strategy deployment. Remember, part of the Act (/Adjust) phase of a successful PDSA cycle is to sustain the results (for now), write new standardized work, scale up if appropriate, and start teaching to the new standard. This brings a new current state, and the next target condition is identified, initiating a new PDSA cycle of improvement.

In the figure above, the wheel has been moved up the ramp (improvement) through A3 thinking and kaizen. But, there are forces in any system that want to undo that which has been accomplished. Some call it entropy; I think of it as organizational gravity. The function of standardized work is to counter those evil forces by stabilizing and sustaining the new current state.

The role of LDM is to sustain and stabilize ("nail down") standardized work as it is currently written. LDM functions as a "checks and balance" for standardized work, which acts as a wedge to help prevent organizational backsliding. LDM is the setting aside of time on a daily basis to monitor for this potential.

So, to recap, standardized work sustains the current state, and LDM sustains the current standardized work.

Lean Daily Management meetings should take 10 to 20 minutes per day. They are typically done in the mornings, however, they need to be a scheduled, daily priority for all involved. Choose the time that’s best for your practice and team.

All extraneous interruptions should be put on hold for the entirety of the time. During the meeting, a staff member from the department or area of the practice, such as the Hospital Care team, quickly reviews the metrics, status of any countermeasures, new problems that have come up, any cross training efforts, new and ongoing kaizen, etc. with management. The staff member that leads the meeting should rotate from amongst the entire team, so that everyone gets the opportunity to lead the conversation and learn.

As is the Lean perspective, management takes on a teaching and mentoring capacity; asking questions to stimulate A3 thinking, encouraging all efforts and practicing servant leadership.

So, Lean Daily Management accomplishes several things:

1. Gets management to the places where work occurs (go to gemba)
2.  Facilitates conversation and consensus building with staff

3.  Demonstrates management's commitment to the staff

4.  Monitors the metrics that support the True North statement and KPIs

5.  Allows time to encourage and appreciate kaizen efforts

6.  Sustains and audits standardized work
7.  Creates increased engagement of the workers

8.  Show respect for workers

Thanks for stopping by. Comments, questions, and suggestions always welcome.

Also, to answer the sidebar questions, the bottom PBC is showing a signal that needs to be investigated. The first signal is the data point above the upper process limit.The second signal is three or four of the last four data being closer to one of the process limit lines than the average. In the case above, the last five data points are closer to the lower process limit line than the average. In fact, it appears that we may be trending around an entirely new, lower average, which indicates that the whole system has changed somehow. Both of these conditions should have been recognized earlier than now, if they weren't. The next step is root cause analysis and formation of countermeasures, i.e. PDSA problem solving.

Lean Veterinary Strategy Deployment (Hoshin kanri)

Hoshin kanri is a Japanese word for strategy deployment. It literally translates to mean “compass management.” It is the process of introducing and aligning the organization’s True North vision down through managers to the frontline staff. It consists of a series of PDSA cycles complete with consensus building (nemawashi) and playing “catchball” along the way.

The first PDSA cycle is undertaken among leadership. It is here that the concept of True North is defined along with the four to six (typically) high-level focus areas and their metrics. 

When looked at as a whole, these few focus areas should completely define your practice. In other words, monitoring the metrics of the focus areas should give you a high-level indication of how the practice is functioning. If these metrics are improving, then the practice should be improving, also. The lower level metrics will compliment these metrics by highlighting the more detailed processes.

This a true PDSA cycle in that all of the stages (Plan, Do, Study, Adjust) are completed and what is eventually chosen is not written in stone. It is an attempt at alignment; high-level standardized work. It is an experiment. If the True North statement turns out to be inadequate in some respect, then leadership simply adjusts and starts a new cycle. A3 reports can follow the process in order to keep stakeholders up to speed.

The second cycle is between leadership (Owners, C-suite, etc.) and supervisors (lead receptionist, lead surgery techs, lead hospital tech, lead groomer, lead boarding tech, etc.). Again, consensus building is of prime interest. This is not the typical management philosophy of “command and control.” It is a typical Lean “bottom-up” endeavor with "catchball" input from leaders. Leadership introduces True North focus areas to the supervisors and, then, mentors and coaches them in order to help them to decide what True North would look like at their level.

and what processes they'll need to monitor in order to help ensure the top focus are metrics are positive. Again, this may be subject to adjustment after a period of experimentation. A3 reports are kept current.

The third cycle is between the lead staff and the frontline workers. It proceeds similarly to the cycle just described.

So, what we now have is is an overall alignment of the practice from leadership through lead techs down to frontline staff. How that looks and what metrics are monitored will vary based on the the different areas of the practice. 

For example, we might have a True North focus area of "Processes Improvement." This applies to everyone. However, at the lead and frontline level, the metrics are different between, for instance, receptionists or exam techs or surgery techs, etc. Their metrics will be determined by what that focus area means to them from their perspectives. 

If all of this is successful, then everyone, from leadership to frontline staff, should have a hold on the same rope, on the same end, pulling in the same direction and at the same time...and winning!








Mark Graban's 4 Hypotheses of Strategy Deployment

Mark has described strategy deployment as a series of four hypotheses in a series of two blog posts - here and here:

 1.  If we focus our improvement efforts and close performance gaps in our four or five True North areas, we will therefore perform well as an organization, this year and into the future.

For example, if we choose Client education, Staff development, Community involvement, Fiscal responsibility and Hospital improvement as our five True North focus areas, then we posit that if we are successful in these areas, the practice as a whole will be successful. In other words, these five areas are the best five areas to monitor in order for the overall practice to be successful. 
Remember, this is your True North statement with your focus areas for your practice with your staff and clients. 

Is this the right True North? We don't know.  But, we will start with these and experiment. If it is determined these are not the best five, we can adjust them and try again. Just like treating our patients. If one diagnosis or treatment is not working, then we “back up" and try again

What are the four or five focus areas that make up your True North and that, if successful, will results in a high probability that the hospital/clinic will be successful overall.

   2.   If we can improve and close our performance gaps in these key performance indicators, we will satisfy our need for improvement in our key focus areas, and therefore will be successful as an organization, overall.

What are the metrics (two or three per focus area) that will show that our focus areas are heading in the right direction (which, in turn, indicates that the whole practice is headed in the right direction).

Are these the right metrics? We don't know, but we'll try them for a while and then evaluate our decision. If they are the right metrics, why? If they aren’t, why not? It is important to deeply understand both of these scenarios in order to learn.

Are these metrics still relevant to your organization and staff?

3. If we actually execute and complete these top X initiatives,  projects, events and A3s, then we will make the greatest strides toward closing the key focus areas (Hypothesis  2) and therefore we'll be more successful in our strategy.

Not everything can be a high priority. It is easy to get sidetracked and pulled off task. You have already prioritized in the last hypothesis. Stay focused. Close the performance gaps in these focus areas in order to get the greatest gains, then you can start over with other focus areas. Err on the side of too few initiatives (so you can actually get something accomplished), rather than too many (and none of them get done or done right). With experience and reflection, you will get more accurate in choosing the number of areas you can tackle without the whole team becoming overburdened. 

4. We actually have the organizational capacity to complete these top X priorities in a year or a given timeframe (and with the right quality).

Do we have the capacity in terms of personnel, resources and capital to actually accomplish these priorities in a timely fashion? If not, then either we obtain them or deselect this priority in favor of another one that can be accomplished at this time.

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Management By Means

There are several reasons why some organizations have had difficulty obtaining the kind of results with Lean that Toyota has. One of the main reasons could be that they confuse the use of Lean "tools" with the incorporation of  the complete Lean philosophy and mindset deep into their DNA.

Take, for example, the difference between Management By Means (MBM) and Management By Results (MBR), also known as Management By Objective (MBO).

With MBR/MBO, management sets the goals (usually financial) for the metrics. The objective of the organization is to reach the goal, without much attention to the processes or methods involved. Leaders might say things like, "I don't care how you get the results, just get it done, no matter what." Pay incentives or threats of dismissal often can, at different times, be part of the conversations and scenarios. 

Look at the Process Behavior Chart below, which shows only the last data point (for a metric where higher is better). 

This is typical top-down management, which is common in the West. Workers do whatever they feel necessary in order to arrive at the goal by the deadline set by the forces that be. The method or means of getting there is a distant second concern. The focus is the end result.

One of the problems with this approach, as seen below, is that the systems and processes, if they were exposed, may be riddled with errors, defects and/or fraud (ala Wells Fargo). There is a lot of variation which implies the systems and processes are not as tight as they could be. In addition, notice there is a recurring pattern to the data-- three weeks of down data followed a an up data. This very well could indicate that, for three week every month, the employees not hitting there number until the week before monthly reports come out. If the reports only show the ending point for the current month, leadership is happy (and leaves the staff alone!) 

MBR is similar to trying drive by looking in the rearview mirror. 

Workers have no control over systems. They are at the mercy of systems, good or bad. It is management or leadership that is responsible for the system in place. As such, if results are not predicted to be good, then the only pragmatic way they can affect the result, and not be disciplined, is to "fudge" the system somehow. 

In a bad system, no amount of motivational rhetoric, monetary prizes or threats is going to change the system. The system gets changed by the "uppity ups" changing the system. An object in motion tends to stay in motion in the same direction unless some external force is applied to the system. That isn't part of the job description (or domain) of workers.

MBR is managing the results

By contrast, MBM is focused on the processes and systems ("the means") that lead to the results ("the ends"). The metrics of MBM monitor the systems involved. The idea is that if all of the processes are stable and positive, then the results are a foregone conclusion. It is much more of a bottom-up style of management since the staff is much more involved in choosing the metrics and monitoring the day to day functioning of the organization. The journey is as important as the destination.

In the graphic above, we really don't need to see the final result (below) to have a reliable expectation that it will be where it needs to be. In addition, we know that our systems and processes are probably functioning properly and free of waste. While there is some variation, they appear to be under control. 

(Notice that three out of the last four data points are closer to the upper limit,  which indicates that the system has changed for the better; improved. If we do know why this has occurred, we need to investigate in order to understand how to continue this trend.)

MBM is managing the processes; the operations

This is the management style of Toyota and promoted by Lean. People often say, "The right process brings the right results." We care about results... but you manage a process, not the results.

Lean is all about objective systems thinking!

I will continue with the next idea in this theme in my next blog "The Practice Scoreboard."

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Process Behavior Charts: A Better Way to Evaluate Your KPIs

Have you ever learned something new and thought, ”Gosh! If I had had only known this years ago, my life would have been so much easier!”? We all have, I suspect. What I'm writing about in this post falls into that category.

I remember owning my practice. I dutifully kept stats on everything I could think of:

• Gross income, 
• number of new clients, 
• average invoice total, 
• number of dentals or spays or neuters, etc. 

I would even plot them on charts and tape them to wall of my office like a war room, constantly watching the numbers and bouncing emotionally between feelings of “we made it through another period in good shape” and “oh sh*t, we’re down, and this must be the beginning of the end.”

The same sort of thing happened when I worked for a corporate practice. Every week, the practice manager (PM) and I were on a conference call with our area managers to discuss “the numbers” -- our KPIs (key performance indicators) -- whether we were achieving our benchmarks, by comparing them to last month, last quarter or last year, and why or, more importantly, why not. Same emotional rollercoaster.

Now, for the stuff I wish I’d known back then. I recently read a book called Understanding Variation: The Key to Managing Chaos 2nd Ed., by Donald J. Wheeler, at the recommendation of my co-blogger Mark Graban. It is a fun little book about some statistics (there is that ‘S’ word) and creating Process Behavior Charts (PBC).

You know that in any process or system there is going to be some amount of variation from period to period. When this is plotted on a chart, it shows up as “ups” and “downs.” Most of this is normal, it is just “noise.” But, sometimes it can mean something significant -- a “signal.” So, how do you tell the difference? By turning your data into PBCs. This way of plotting your data will “filter” out the noise and highlight any “signals.”

I encourage you to read the book as there is more than I can briefly blog about, but, having said that, let me share some points before we get into the charts.

1. Tables with lists of numbers are difficult to understand. There is no context, and the data is difficult to visualize in this format.
2. Line graphs, over a longer period of time, are easier to understand and put the data in some form of continuity and context with prior periods.
3. Comparing two data points, such as the current period data with the same data last month or last year, doesn't offer any context. Who says the data from last period was normal? Maybe, it was a really bad period due to extraneous influences, e.g. inflation or a natural disaster that occurred at that time.
4. Averages tend to be pretty much in the middle of a range of data. Comparing to averages tends to create “binary output.” You are either above average (“good”), or you are below average (“bad”).
5. The setting of arbitrary goals, such as a 10% increase over last period, becomes more objective and rational. It is well and good to set the goal, but if the system cannot produce to that degree, it is simply a futile “wish.” No manner of cajoling, incentivizing or threatening employees is going to help. If the goal is outside the limits, then the system is going to have to be changed from what it is right now, and employees have no control over the systems under which they operate. That is management’s domain.
6. PBCs are the voice of the system. They show how the system is functioning, and the extents to which the system can function, as it is now designed and operating. One can also assume that, without any change, the system will continue into the future as it is currently; it is predictable. If it is not where it should be, then the system has to be changed somehow. It also shows when a data is outside the limits of the system and, therefore, is a signal that something unusual has happened, and it needs to be investigated.

The following data represents the number of new clients seen per month over the last 18 months.

18, 16, 14, 19, 15, 17, 16, 18, 15, 14, 19, 18, 15, 18, 18, 17, 19, 11

Total = 297  Average = 16.5

When just looking at a list of numbers, it is difficult to really appreciate what is going on with the data. In this form, one might easily miss the value of the last data point.

Converting the raw data into a graph is more visually helpful.

You can see that this running graph (or X-chart) is easier to understand and gives better context to the table of numbers.

This appears to be a rather stable system (or process) until, possibly we get to the 18th and last data point. Is this part of the normal “noise” or do we need to investigatte? It is lower than any prior period we have recorded. I can tell you that, for me, this would have been good for at least a week of sleepless nights and two stupid, stress related arguments with my wife!

Continuing with the chart methodology, we next determine the Moving Range (mR), between each two successive data points. This distance is always a positive number, regardless of whether the first number is larger or smaller than the first. For example, the distance between -3 and 2 is 5, or the distance between 8 and 4 (or 4 and 8) is 4.

By comparing the first data to the second, the second data to the third, the third data to fourth, etc., we get the following table:

2, 2, 5, 4, 2, 1, 2, 3,1, 5, 1, 3, 3, 0, 1, 2, 8

Total = 45  Average MR = 2.53

Graphically:

To see if the variation in the X chart is all routine or if there's something exceptional going on in that last data, we then complete the X-chart by calculating and drawing the average, an Upper Control Limit (UCL) and a Lower Control Limit(LCL).  These are calculated as follows:

          Avgx= Totalx/#x

          UCL= Avgx+(2.66×AvgmR)  = 16.5+(2.66×2.53) = 23.54

        LCL= Avgx-(2.66×AvgmR)  = 16.5-(2.66×2.53) = 9.46

Note: The 2.66 is a conversion factor that approximates three standard deviations (but we don't calculate a standard deviation in this methodology).

Updating the X-chart:

To complete the mR chart we need to calculate the Upper Range Limit, as follows:

         Upper Range Limit = AvgmR×3.27  = 2.53×3.27 = 8.66

  
Note: The Lower Range Limit is always zero, since the variances can never be a negative number.

Updating the mR chart:

Together, these two graphs make up an XmR chart or Process Behavior Chart.

Looking at the XmR charts, we can see that the last data point is still within our calculated limits. This indicates that the data is just “noise.” It is just part of the normal variation for this system or process, as it is currently designed.

That said, if we're uphappy with the average level of performance, we could try to improve the system in a systematic way. There's nothing worth investigating in terms of a reactive question like "what went wrong that month?"

The first hint of a "signal" would be any single data point above the upper limit or below the lower limit.

Wheeler’s book gives much more information about the meaning of the charts and some other types of “signals” to be aware of such as: 3 out of 3 or 3 out of 4 data points being closer to one of the limits,

or

a run of eight or more consecutive data points being on one side or the other of the central line are interpreted as being a “signal.”

Mark Graban is currently writing a book on this material. It should be completed by June, but you can buy the first three chapters now through his use of the "Lean Publishing" approach. All of Mark’s books are “Top Class.”

Heads up! I will be the guest on a webinar hosted by Mark Graban and KaiNexus on May 7th at 12:00 noon Central time. We will be discussing the new emergence of Lean management in veterinary medicine.  Use this link. Hope you will join us!

Update 4/4/18: Watch Mark Graban talk about this material here.

Thanks for reading. Tell your friends and colleagues and, as always, comments welcomed.