We spoke with Mark Graban, and we discussed the importance of managing your metrics in your field of work. These metrics could be within the healthcare field, or they could be for a business. Either way, they are essential, but what’s even more important is how you manage and examine them.
Mark Graban is an author, podcaster, and leader in helping business and healthcare leaders be more successful.
Mark Graban’s Biography
- Mark Graban is the author of the award-winning book Lean Hospitals: Improving Quality, Patient Safety, and Employee Engagement.
- Mark is also co-author, with Joe Swartz, of Healthcare Kaizen: Engaging Front-Line Staff in Sustainable Continuous Improvements and The Executive Guide to Healthcare Kaizen.
- His most recent book is Measures of Success: React Less, Lead Better, Improve More. He is also the creator and editor of the anthology book Practicing Lean.
- He serves as a consultant to organizations through his company, Constancy, Inc, and through the firm Value Capture.
- He is also a Senior Advisor to the technology company KaiNexus. He has focused on healthcare improvement since 2005, after starting his career in the industry at General Motors, Dell, and Honeywell.
- Mark is the host of podcasts including “Lean Blog Interviews,” “My Favorite Mistake,” and “Habitual Excellence, Presented by Value Capture.”
- Mark has a B.S. in Industrial Engineering from Northwestern University and an M.S. in Mechanical Engineering, through three and an M.B.A. from the Massachusetts Institute of Technology’s Leaders for Global Operations Program.
Mark Graban’s Social Media and Other Outlets
- LinkedIn – https://www.linkedin.com/in/mgraban/
- Mark’s Website – https://www.markgraban.com/
- Mark’s Podcast -Mark hosts 3 podcasts.I would like to emphasize this one. – http://myfavoritemistakepodcast.com/
- Twitter: @markgraban
In This Episode, You’ll Learn…
- What gets measured gets managed. What does that mean? We manage a process. We might use the word “lead” when it comes to people. Our leverage points are the things we can do as leaders to achieve better results.
- Having too many metrics is a common problem. Overreacting is also a problem. For instance, for any of us, there are several key health metrics. It might be weight, diet, lifestyle, or other critical metrics specific to a person’s health and situation for some people.
- So, the key is finding the correct number of metrics and then finding the right category of metrics to focus on. Of course, you should measure, but you need to measure the right things. For instance, 5 Categories of Key Metrics For a Business are Safety, Quality, On-Time Delivery of Product, Staff Morale, and Cost. These are likely the metrics businesses should look at the most.
- You also need to know how often to measure. Some of this is learned through experience. Does something seem too cold or too hot? Is it too frequent or not frequent enough? Each person is different, and each business is different. For instance, some people think you should weigh yourself daily. Others say weekly, so you don’t react to the fluctuations. Then, some say you can train yourself not to overreact. It’s a matter of not reacting to the “noise,” which is your small fluctuations, but reacting to the signal, which is the bigger picture, such as a 5-10 pound change.
- Process behavior charts can help show the metrics and look at the bigger picture. They help you examine the bigger picture as to when measuring weight changes. For example, you can monitor if your weight is going up overall or down. And then, you can determine what changes to make, if any.
- A “signal” is mathematical, statistical proof that the metrics are no longer just staying around one area. You define lower and upper limits, and the signal is a single data point that’s either above the upper limit and or below the lower limit. If you see at least eight metrics occur like this, then you have a signal. This number is an average that applies to almost anything.
- Most businesses are just floating around an average. Of course, there are some exceptions, but seeing these metrics float with an average often means stability.
- The process behavior charts have helped businesses identify problems with business and examine data over time. With this data, companies have used it to identify the factors that were making the company “stuck.” Essentially, this data helped them identify the problem and help get them “unstuck.”
- Mark challenges business owners to use his process behavior charts. For example, don’t compare one month of data to the previous month or any recent activity. Instead, look at the bigger picture. For example, look at where the business was last year or a few months before.
- It’s hard for people to break old habits, though. This problem often leaves people personally stuck. So, a more personal approach may be more helpful.
- React less. Lead better.
- Are you measuring too frequently or not frequently enough?
- Don’t react to the noise, but do react to the signal.
- If you see at least eight metrics occur on a large amount of data, it’s a signal.
Links & Resources Mentioned…
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Mike O'Neill: Welcome back to the Get Unstuck & On Target Podcast. I'm Mike O'Neill with Bench Builders and we're business coaches who love to help leaders get unstuck and sleep better. In this podcast, we're talking with thought leaders to uncover tips to help you break down the barriers that may be keeping you or your business stuck.
Mike O'Neill: Joining me today is Mark Graban. Mark consults through his firm Constancy and through the firm Value Capture. He's also a senior advisor to the technology company KaiNexus. Mark started his career at General Motors, Dell and Honeywell. And since 2005 has focused primarily on healthcare improvements. Welcome Mark.
Mark Graban: Mike hi. Thank you for having me here.
Mike O'Neill: I am in kind of rare company, because Mark is not only also a podcast host. He hosts several podcasts. Those include the Lean Blog Interviews and Habitual Excellence. And it's his newest podcast. It's called My Favorite Mistake that I highly recommend. Mark has also authored and co-authored several books. But it's his most recent book it's called Measure of Success. React less lead, better, improve more. And it's this book that we're going to spend most of our time today exploring. So Mark, why don't we just jump right in?
Mark Graban: Okay.
Mike O'Neill: We've all heard this adage. What gets measured gets managed, but you pose in your book, a fundamental question in the opening. And that is what gets measured, gets managed. But as a leader, have you ever learned to manage a metric? Great question. Elaborate, please.
Mark Graban: Well, thanks for bringing that up. And I think there's a couple elements to it. What gets measured gets managed. What does gets managed me like that could be defined many different ways. And we can explore that here. Maybe today, there are ways of reacting or managing that just create busy work, chaos, confusion, dysfunction. And then there's maybe an element of the quote, what gets measured gets managed. As, as you were saying, we, we, we could say we manage a process. We manage a business, we manage a system. We might use the word lead when it comes to people, we're leading people. And then that metric, I would say, it's, it's an end result of our business, the systems, the processes, the people, the leadership, we, we very often can't directly.
It's not like turning a knob on, it's a dated reference to think back to when radios had knobs, but you know, the, the direct lever is not the metric. What we are leveraged points in the organization are things we can do as leaders. That then improve that business, that lead to better results and the book Measures of Success, explorers, you know, some, I think better alternatives for how we react or sometimes don't react. You know, the subtitle, like you said, is react less, lead, better, improve more. It's not never react, but we can maybe learn. Through the methods in the book, you know, when, when are the times that we should react to the most recent data point, because it's some sort of outlier that's worth understanding and explaining. And then there's times when we should actually kind of chill out a bit and take a step back and not be so reactive about that most recent data point.
Mike O'Neill: Mark, I know you work in multiple industries. Healthcare is one area that you are known for, but you work in other industries as you step back and just look at this notion of measuring. Do you find some industries put more emphasis on measurement than others?
Mark Graban: There's I think a little bit more of a culture of measurement in manufacturing. Healthcare of course has measures. There's, you know, sometimes step back and ask, well, you know, are we measuring what's easy to measure or are we measuring what's important to measure. But I've seen, you know, as I've worked in different industries the first years, 10 years of my career in manufacturing, 15 years in healthcare, probably a total of 12 years involved either full-time or part-time in startup software companies, all those companies have measures. And I think there's fairly consistent human behavior and how executives or leaders or managers, are reacting to their metrics. So that's why I wrote the book Measures of Success, not as a healthcare management book, as I've done previously, this one is really more of a management book and it brings, it brings in examples from manufacturing, healthcare, software companies. I mean, we can find examples in the news of data and metrics. And headlines that might be misleading because that headline is just reporting the difference between the last two data points. Well, we, we do that at work. And so sometimes examples like that from the news or from, data in our communities about, crime rates or things like that, we can learn those lessons in a way that helps us bring, the approaches into the workplace. So again, you know, we can react less and we can lead to better that actually frees up time. And equips us to improve more, which is really, I think that's, that's the point.
Mike O'Neill: You know, Mark, you introduced something that I'd, hadn't thought about and that is, are we measuring the things that matter most or are we measuring those things that are easiest to measure? And I was, my head was spinning, as you were saying, that of examples by which I know that I've worked in organizations, they were measuring everything. But in reality, the question is what matters most, are there some general rule of thumbs we'll to start with that before we get into some other aspects, but general rule of thumb, when you were working with an organization, how do you help them identify those metrics that do matter?
Mark Graban: Yeah, yeah, you're right. This, this is a common problem. Too many metrics. And, you know, we, we, we hear the acronym, KPIs.
Mike O'Neill: Yes.
Mark Graban: That the K stands for key.
Mike O'Neill: Yes.
Mark Graban: What are the key performance indicators? Sometimes we have a kajillion performance indicators and that becomes overwhelming. Like I, I, I interviewed. The other day for, for my lean podcast, a woman who works in the British national health service and she teaches, this, the same methodology that I learned. We both learned it basically from the same statisticians. And she would say, you know, a hospital board might have a couple hundred metrics that they're looking at. And then when you have the dynamic of kind of, you know, over to tending, to overreact, to all of them, if you have 200 metrics, maybe half of them are better than they were last month. And half of them are worse than they were last month. Or some of those metrics are color coded red or green. And we react to that, which may be isn't the right basis for it. So, so back to your question, though, I try to draw parallels, to help. I've, I've done a lot of work with hospital laboratories and I think it's fair to say there are hundreds, maybe it's actually measured four digits, hundreds. There are hundreds of different laboratory tests and measures related to your blood and your body and things that you, that that could be measured. When it really comes down to gauging health or quality of life, which I would argue is really kind of the end result output of all these measures, we're all unique, right? So I, my family, there's predisposition to type two diabetes. So for me, there are certain measures that are really important to look at.
And if one of those measures, is, has blipped in the wrong direction, that's the time to react. When it comes to diet, lifestyle, exercise, what have you. And then there are some people for whom that measure doesn't matter. But I think for any of us, there are, I don't know what the exact number would be. A handful of key health measures. That number on the scale might be one of them. That number on the scale might also be misleading, you know, in different ways. So I think there are lessons from organizations like don't fixate too much on one number. You've got to keep that number in context. With the overall goals of the business or, or your own health and, you know, you, you raised yeah. You know, I appreciate your reason that question of asking, like, what are the key metrics we need to look at to gauge the health of the business? There might be some things we look at daily, or even hourly. There might be some things we look at weekly or monthly or quarterly. So I think in addition to the question of what do we measure and why there's another question around what's the right frequency for looking at those metrics and, you know, I learned framework back in manufacturing that I think applies well in other settings, if you were to pick five categories of key metrics for a business, well, let's start with safety.
Mike O'Neill: Yeah.
Mark Graban: Quality.
Mike O'Neill: Yep.
Mark Graban: Your, on-time delivery of product or in healthcare that might mean waiting time or access to care, staff, morale and cost or bottom line measures. And now the the mantra, the mindsets I was taught was that, you know, safety, quality delivery and morale, if you improve in those measures, that leads to lower cost. Which will lead then, I mean, quality would lead to growth and revenue and profit, but you know, there's this methodology I've learned whether we call it Lean Manufacturing or the Toyota Production System or Lean Healthcare, or the Lean Startup is that we view cost and profit as being the end result of doing everything else right. Which is different than a quote unquote cost cutting focus. So, I know you kind of touched on a lot of different thoughts there. So I think, you know, the key is finding the right number of metrics, finding the right category of metrics. And then are there one or two or key, you know, one or two or three key measures within that category of metric? That's, that's a framework that I've seen work really well. So not just one, not hundreds, but something that's maybe more like 12 to 20. Key measures.
Mike O'Neill: You use the word handful. And so we've gone from potentially thousands to a much more manageable number. But did you also said something that was kind of interesting, and that is if your challenge to us as leaders, leading organizations is yes measure, but measure the right things, but also stay focused on those things that matter. Most you're kind of raised a point. Individually and collectively. We have a limited capacity to what we can keep up with. And so if we were to reduce that number to the number, you just kind of mentioned, at least we increased the likelihood that we can pay attention to those, those fewer numbers. You know, you mentioned, about not only what you measure, but you also began talking about how often you measure it. You can measure it too frequently. You can measure it not often enough, it almost feels like kind of Goldilocks. You gotta find that right balance. How do you advise your clients on how should they go about finding that balance on frequency?
Mark Graban: I think some of it is through experience. So to build on the Goldielock analogy. Does something seem too cold or does something seem too hot. Is it just right? Is it too frequent? Is it not frequent enough? Right. So I'll, I'll think of an example with, with personal health. I do weigh myself every morning. Weighing myself multiple times during the day. Probably not very helpful because for one, your weight fluctuates during the day as you're eating and there's just normal kind of patterns and rhythms. So for me, measuring myself, weighing myself every morning is fine. And then there's that question. And this is where I've learned from some of these statistical methods that we could also call management methods, things I write about and share in Measures of Success. Not to overreact to every up and down in that number. So you might be in a period where I'm trying to lose weight. I might be in a period where I'm happy if my weight is just stable and again, like each person is different. My weight may fluctuate plus or minus a pound every day for different reasons.
Fred Rogers, Mr. Rogers, like in the movie about him with Tom Hanks, it's brought up that Fred Rogers supposedly always weighed 143 pounds every day. And maybe Fred Rogers was very disciplined and what he ate and he swam and he exercise and I don't think he drank alcohol. So I do, and I don't eat the same things every day. And I, I don't always make good choices. So my weight is, you know, for different reasons, my weight is going to fluctuate. So there are some experts when it comes to health and I'm not a health expert, but just trying to use the example. There are some health experts who say, you know what? You should only weigh yourself weekly so that you don't react to every, up and down on a day. So for some people that might work fine. But for me, you know, I, you, so again, you know, the idea is weigh yourself weekly. So you don't overreact to daily fluctuation. You can also learn and train yourself to not overreact to daily fluctuation. And that's where, you know, there's a method I was taught and I share in the book, called a process behavior chart. Which is applicable to business metrics. It helps you learn the difference between basically just that, that routine fluctuation that's not worth reacting to, or explaining or investigating. And then a time when you might have what some would call an outlier in the data, or, you know, statisticians might call that a signal we're distinguishing between signal and noise. Don't react to the noise, but do. React to the signal is, is one of the lessons that I think is transferable from that number on the scale or our business metrics.
Mike O'Neill: Yeah. In your book. My understanding is it's that reaction to the noise. They can really create problems. You describing your book. It's that reaction to noise that can cause waste.
Mark Graban: Wasted time, wasted, motion wasted emotion and energy. If people get upset about a number that's a little bit worse than it has been before, and then they get to happy the next day, like I've heard people in, healthcare describe that dynamic of re overreacting to every up and down and fluctuating metric as pizza or punish, because then the metric looks good. Like, Hey, let's throw a pizza party. And then the next month, the metric looks bad and managers kind of give a bit of a speech or pressure people or chastise them. And then guess what it fluctuates back to being a little bit better than average. And the manager might pat themselves on the back and say like, Oh, I lit a fire under them. Like when really maybe no such thing happened at all. People just kind of toughed out. They cross their arms and stared at the shoes and waited for the the chastising speech to end, and then they go back to work and the metrics just flush fluctuates back. Again, so that's, that's a really common dynamic in different industries. And so then when we overreact and what we ended up wasting time, we, we ended up with kind of a faulty cause and effect relationship between what's really happening and the metrics and, and that's where, you know, process behavior charts help us evaluate, improvement projects, like where w where we are trying to change the system, or if I was trying to lose weight. You know, at the beginning of the year, well, I've lost 12 pounds this year.
And, I was trying to make it through some changes to my system, mostly diet, a little bit with exercise. I was already exercising. I want to see that metric that weight not just fluctuating around an average. I want to see it start becoming an outlier in a good downward direction. And, and so the, you know, these process behavior charts give us a very visual method. And then with a little bit of math, we can calculate what you think of as some guard rails or, you know, we, we, we call these limits in the chart to help us tell if that metric is just fluctuating within those limits. I've got a stable, predictable health or a stable, predictable weight, or a stable, predictable profit number for a business. But then in the case of weight, if I can get that number to be below that lower limit, I can say, Oh, okay. The math sort of proves out and I see it visually. It's no longer just fluctuating. I'm making good progress. And then I might have a bit of a step function down where now my weight is fluctuating around a slightly lower average. Until I get a little bit more, more, more motivation to make additional change, being more consistent in some of these changes to, to keep shifting, that metric downward in the right direction. The charts, these process behavior charts can help me, again, distinguish between signal and noise. Especially if I'm trying to gauge cause and effect, with an improvement project in my business or a change I've made to my diet.
Mike O'Neill: So let's pursue that for a moment. If process behavioral charts done right. Will allow you to differentiate noise from signals. We've talked about noise, but what do you, when you use the word signal, what does that mean to you and how you advise your clients?
Mark Graban: Yeah, so a signal is sort of, you know, mathematical statistical proof that this data point or data points are no longer just randomly fluctuating around a stable average. So, as I mentioned, we have these. Guardrails above and below. So we can think of a process behavior chart. And for the audio listeners, the podcast listeners have to try to imagine that you've got some sort of run chart or line chart that shows your metric over time. Like you might draw in Excel and then you calculate an average for your baseline time period. And you've got horizontal line in the middle of your metric, and then you calculate what are called the lower and upper limits. That are kind of symmetrical around that average. So to your question, Mike, if there's a single data point, either above the upper limit or below the lower limit, that's the signal.
Mike O'Neill: I see.
Mark Graban: That's a point that's worth stopping and asking what changed, what happened if it's a change in the positive direction, you'd hope you understand why. So you can learn from that. If somebody was experimenting with a new method for doing their work, you want to understand that and maybe make that the new standard method. If you have a data point that's worse than the lower limit. Like so many, it's a metric that we want to be higher. We would likewise react. So back to your question earlier, if we've narrowed it down from 200 metrics to 12 key performance indicators, there might be one or two. I mean, it's depends on the dynamics, but there might be one or two out of those 12 that are showing a statistical signal. We want to focus our effort and attention and energy on those charts and the metrics that are showing a signal. Th the other second key signal that you would see is eight or more consecutive data points that are all either above average or below average, that that's, that's a strong statistical signal that it's no longer fluctuating around an average. And again, that's worth understanding or reacting to, or learning from.
Mike O'Neill: You mentioned the word that the number eight, is that correct? So you have found that number eight, holds true in a variety of settings. If you see it occurring eight times, then that's, that is a signal that you respond to.
Mark Graban: Yeah. And that's the, that's the guideline that I've learned from PhD statisticians of which I am not. You know, and, and, and it's a minor point and there's quibbling, there are some who would say seven consecutive. There are some who would say eight. There are some that would say the math proves out nine is the right number. Because, you know, with this statistical analysis where we're trying to trade off, there's the risk of overreacting and there's the risk of not reacting soon enough. But, but eight is, I mean, I think, you know, I think that's, that's a good, useful number. And we can see that we, again, we can see that visually on our, our metrics are on a process behavior charts. It should jump out and say, okay, that's no longer what, what I've seen is most business metrics really are just fluctuating around an average, unless we're in a high growth startup business where a revenue might be fluctuating around a linear you know diagonal line on the chart, that's kind of a special case.
But a lot of business metrics when it comes to safety metrics, quality and customer satisfaction metrics, how many patients, had their surgery start on time, like metrics like that tend to fluctuate around an average because the systems and the processes are also pretty stable, right? So we wouldn't expect to see huge fluctuations in the metric. But that's why we use the charts again, to distinguish between signal and noise and to help kind of filter and focus what we respond to as leaders.
Mike O'Neill: I know we spent quite a bit of time on data and how data appears both graphically and otherwise. But sometimes when you look at data, one can kind of conclude my gosh, I can't, we can't, we're all trying to get it off this. We are almost stuck if you would.
Mark Graban: Right.
Mike O'Neill: May I ask, can you reflect on maybe an example by which, and working with a client, the realization was we're stuck, and if that took place, how did you help them get unstuck?
Mark Graban: Yeah. So I worked with, a healthcare client. This was in like summer going in the second half of 2019. We'll call it. So pre pandemic and their main focus was trying to improve, what are called patient experience survey scores. So this is a measure and they will chart and plot some of these key measures every month. One of those key measures would be what percentage of patients would recommend the surgery center? You know, when you're asked, you know, how likely are you to recommend the surgery center from one to 10? What percentage of patients said nine or 10? Now we could quibble, like, I think that's a strange way of measuring patient satisfaction, but it is a very standard metric. So they have it, they're running with it. We were looking at it and they wanted to improve that. Because they, they know, they, they knew comparing to other surgery centers that they were in the bottom half of performance nationally. So I think they would describe, and we, we, we looked at their data going back about two years and we charted it on a process behavior chart. And you can see that number was very stabley. Fluctuating around an average, it was fluctuating within those limits or guardrails. And so we could look and say like, your, your performance is stuck in a certain range. What have you done to really improve patient satisfaction? And they might point to a number of relatively superficial things that they tried.
But I think part of the realization was what we didn't really do. A whole lot that really would have been expected to boost performance, to get them unstuck and on target. That's why I love the name of your podcast Mike that's what they were trying to do. They were stuck range of performance and they weren't reaching their target. So for one, the process behavior chart helped them better understand that where in the past they would've had the tendency to kind of, you know, pizza or punish. We also decided that it was worth looking at that metric in weekly buckets instead of monthly buckets, because we did go through, you know, this lean healthcare process to analyze and understand.
We looked at voice of the patient data. Now the surveys, it's an, it's an imperfect metric because not everybody returns the survey. So the people who tend to be really happy or really upset, or maybe really bored fill out the survey. So is it a perfect representation? But everyone's got that struggle. So maybe it's apples to apples. You know, so we started looking at the data and started asking why patients were dissatisfied. Now, again, like we, weren't asking why was last months number bad. That wasn't a helpful question in this case, but to step back and look consistently over time. Why are customers unhappy? And the main thing that bubbled up was, my procedure started late. I was, you were behind schedule. I waited too long. So we dug deeper and understood what are some of the causes, if not root causes for those delays and waits, we made some changes to the system. So now we had a hypothesis of making these changes would boost patient satisfaction. Now, if we were only measuring that monthly. It would be really slow to possibly see some results. So we started looking at the weekly buckets, and again, we weren't going to hang our hat or declare victory on slightly better than average performance like that wouldn't have felt right. So what we did look for was, you know, very quickly we were able to generate a data point that was above the upper limit of the old range of performance. So we could say statistically and in a mathematically valid way, not just guessing or playing politics, internally that that performance got unstuck and it was now closer to target. And then what we saw as a result of making that change, kind of like my weight now fluctuating around a lower average there, their patient satisfaction scores started fluctuating around a higher average. So you see, not just that one data point above the limit. Now you see eight consecutive data points. That are above that old average level of performance. And they realized like their work wasn't done. They weren't yet fully on target, but they had built some confidence that they were improving and that they could improve again.
And we would keep tracking those metrics. And then, well then the pandemic happened and they probably didn't do any surgeries for a couple of months. So that, that was certainly an unexpected, dynamic, but yeah, I mean, I think, you know, the combination of the chart. And some coaching around, whether they call it process improvement or understanding cause and effect in our system. I think that did really help. It did get them unstuck.
Mike O'Neill: That's a perfect illustration by which you encourage them to step up back. If you tweaked the frequency, you also went back and you did more of a drill down and then drilling down. You saw that there were factors that were influencing that. And when you identified that and you were able to adjust that, make the changes necessary as reflected on the process, behavioral charts and assume, then you began to see that that trend line began moving in the direction. You wanted, you know, as we're kind of thinking back, we have as listeners, primarily leaders, and yeah, I'm trying to kind of encourage us to be thinking, what does that mean to me? How do I apply what Mark is sharing here to me and to my organization, as you kind of reflect on the things we've discussed thus far, what might be some of those themes that you want to make sure. That our listeners have as takeaways.
Mark Graban: Well, I think the one suggestion is, you know, to, to take a look at how your organization, visualizes or displays performance metrics, right? So one challenge, that, that I have here with, with my, with my book and my teaching, and I'm trying to invite people to learn a lesson, these process behavior charts. That I think is a fantastic solution to a problem that a lot of people might not recognize as a problem. There's a challenge, right? So if we look and say, well, my organization tends to only compare the most recent data point to the previous month. That could be problematic that could lead to the overreaction, the pizza punish cycles what have you. If an organization is comparing the most recent data points to the previous month and to the same month previous year? Well, that gets confusing because if we're in this kind of predictable, repeatable, routine fluctuation. What we'll often see is our metric is better than last month, but it's worse than a year ago. So is that pizza or punish or both? And then I think another dynamic to look at is okay, even if we're looking at more than two or three data points, I see a lot of organizations. Let's say they're looking at 12 months and 12 data points. They'll they'll visualize the data in what's often called a bowling chart. So, if you look at like, when you go and bowl and keep score, you've got 10 frames and there's a number written in each box. Now in bowling, hopefully those numbers are growing frame to frame and know, but when you think of like looking at a list of numbers, people are, it's really hard to detect trends in a list of numbers.
So we have the simple technology again, Excel or any spreadsheet, would call it a line chart. Visualize the data that way. And it becomes a lot easier to tell. Has there been a shift in performance? Has it, is it just fluctuating around an average? And then another thing to look out for is color coding. So we have a target. Are we on target or not? If we're on target green off target red, and some organizations are constantly reacting to, well, it was red and now it's green. Hooray pizza party. And then it dipped back into the red. I've seen it in a lot of organizations where this year's goal is to be maybe three or 5% better than last year's average. Oh, now we haven't really improved the business or the organization. That number is still fluctuating around an average, and it's going to tend to flip not perfectly back and forth every single month, but it's going to be red, green, red, red, green, red, green, green, green. I mean like, Oh, okay, great. Now it's great. And then, then it jumps back down to red. And like that number is just fluctuating around an average. So, you know, if any of those conditions apply. I think there's an opportunity for process improvement charts to be a better mindset. But then we face the challenge of like, well, the red, green color coding, and that's how I was taught to manage. That's how my organization has always done it. And so that, that becomes a situation where, people are kind of personally stuck. And the way they manage and getting people, unstuck, is, you know, sometimes done best through some hands-on exercises and simulations that, that I've learned. And I've kind of adapted and modified, like teaching people through hands-on experience is more eye opening and less threatening than me trying to say you're doing things wrong because nobody likes hearing that. Right.
Mike O'Neill: No question. We learn by doing that. Sometimes a fresh perspective can really open up our eyes, open up my eyes to a number of things. We packed a lot in our time together. Mark, if folks want to reach out to you and connect online, what's the best way for them to do that.
Mark Graban: So I'm pretty easy to find online. Mark Graban is a pretty unique name. There's one other Mark Gaban who's an elementary school teacher. But if you just go markgraban.com, Mark with a K a G R A B like Bravo, A N like November, markgraban.com. That's one way, I'm pretty easily found on LinkedIn. If you want to search Mark Graban, Twitter @MarkGraban, probably the worst way to contact me. I've had sometimes people send me a message through Instagram and like, there was a couple years where I didn't even realize there was messaging in Instagram. I thought it was just looking at pictures. So don't, don't send me an Instagram message, but otherwise I'm kind of obnoxious, really easy to find online.
Mike O'Neill: Well, we are connected on LinkedIn, as your, my latest connection. So thank you for connecting as well. Also just for those, rather than worry about that, we will include. Mark's, website, his LinkedIn profile will include links to, his books. All that will be included in the show notes. You know, I had a sentence and chuckled a little bit. I was thinking when you have that dilemma, pizza or punishment, and when it's one of those situations where you don't know which one to choose, but what crossed my mind is, well, just order bad pizza.
Mark Graban: That's sometimes seems like a punishment.
Mike O'Neill: Yeah, I'm sorry.
Mark Graban: Or the, or the pizza is not compatible with my home objective of, losing a few pounds and avoiding type two diabetes.
Mike O'Neill: But, well, I do want to, we are recording this in early May, but the fact that you've lost 12 pounds since January my hats off to you, Mark as expected. I enjoyed learning from you. Thank you for sharing your expertise.
Mark Graban: Thank you for having me. Thank you for your questions. And, my gosh, you, you give me an opportunity to talk about some of my favorite topics. I hope it was interesting. I hope it's helpful for the listeners in the audience. So thank you for inviting me to be here.
Mike O'Neill: Well, it's my pleasure. I can see your eyes light up when you began talking. So I just want to thank our listeners for joining us for this episode of Get Unstuck & On Target. We upload the latest episode every Thursday. And if you haven't already please subscribe? You know, life is too short to let business problems keep you up at night. Our coaches love helping leaders solve the tough problems that may be holding you back from the success that you deserve. So if you've been listening to my discussion with Mark and you're realizing that something is keeping you or your business stuck, let's talk, go to our website, bench-builders.com. We'll just go to our browser and type unstuck.show to schedule a quick call. So I want to thank you for joining us, and I hope that you'd picked up on some tips that will help you Get Unstuck & On Target. Until next time.