measurement
The Egg and I
Ever wonder about the question of which came first, the chicken or the egg? It’s hard to escape the current media about eggs, salmonella outbreaks again! I confess that part of me is a chicken, more than a bit concerned about the eggs. Although the broadcasted data says my eggs are likely to be safe, the current outbreak is disturbing. Egg farmers everywhere are sharing the chilling thoughts of what fear can do to our buying behaviors. A bad egg amongst the good can spoil the lot. It’s not just about eggs, is it? So, what would we be willing to pay for the good eggs? I know all about the value of data in decision making, the power of an objective lens, the better understanding of what risk really means, how it improves performance, and that is all good. That is, in fact, good as long as we have evidence that the data is good, timely, and reflective of what we really need to know for good decisions. So, how do I make up my mind about the eggs, particularly when my grandkids want some “cheesy eggs”? Cooking them thoroughly is supposed to kill the microbial varmints, but the old, “just in case” whispers in. I’m making decisions with second hand information with a cost versus perceived risk imbalance. Does that happen with other decisions we make at home, work, or play? (The golf course counts here)
It’s complicated since good eggs look the same to me as bad ones. What I need to know is inside the shell, and I don’t have the tools or knowledge to check. Here’s the challenge. I only know that eggs are bad by the damage they’ve done to someone and if somehow the word gets out and if the media decides to share it and if I happened to catch the news. Those are lots of ifs. Someone has to crack the shell and eat the egg. I don’t have testing data on the carton, and food safety failures are nothing to ignore. The wonders of science and high tech supply chain systems make eggs plentiful and really cheap. I suppose that applies to lots of other stuff that’s really cheap. So if we were in the egg business, we would want our customers to enjoy our eggs safely, always safely, and come back and buy some more. A history of great safe eggs is important and I would want to make sure only good ones hit the skillet.
But, this is not really an egg problem; it’s a quality management problem. The golden rule of “thou shall not use your customer as your inspector,” has been broken. That’s a rule that is foundational to ethical business practices. When we make a sale, accept an order or sign a contract, we are in fact making a promise that our customer will get what they expect, based on either a standard, a contract, or what we advertise or put on our “boxes.” Accepting a specification is the same as making a promise, and those that don’t intend to keep it but still sell the “stuff” are “fibbers” as my grandkids might say, or something much uglier in our adult language. It’s a real problem in industries where all the suppliers make the same promises and claims.
So, how do we make promises to our customers? How do we keep them? Do we rely on customer failure data to know, or do we know that the likelihood of failure is unlikely? How unlikely? Do we need someone with a badge and a club looking over our shoulder or is our respect our customers, employees, and investors a big enough motivator? There is really no difference between eggs, or cars, or cough syrup, or toys, or the innumerable products and services we provide. A promise is a promise and when we break one and harm is done, it’s on our name and reputation.
• Do we know what we’ve promised, or more importantly, what our customers believe we’ve promised?
• Do we lead and manage from the big print or the fine print?
• When was the last time we checked our processes? Are they about always keeping the promises? To whom?
• When did we last evaluate how effective and efficient our controls are? How likely are we to keep the promise?
• How and when do we decide what is “good enough” for our customers?
• What evidence could we produce on demand that would support our promises and earn the trust of our customers?
“Quality is not an act, it is a habit.” Aristotle
Oh, Now I See!
“I was seldom able to see an opportunity until it had ceased to be one.” Mark Twain.
“Oh, now I see!” It’s a phrase we use so often to convey that we understand, or get it. We use sight as a metaphor for understanding all the time. The word lens is used to mean a channel through which something can be seen or understood. “Mary sees the world through rose colored lenses,” (an optimist, or naive). We are creatures of pattern recognition and our conjuring process requires imagery to put things in place, or to make sense of what we experience or think. We will typically apply what we know (our storehouse of imagery) to what we see and work hard to make sense of things.
Lenses matter and the choice of lenses have interesting effects on what follows. We believe that lenses allow us to see better, and that is true, but for a very limited and specific range of stuff. The lens is helpful in that it blocks out an infinite number of things we could see or consider so that we get clarity and detail on what the lens puts into focus for us. I’ve looked through telescopes and microscopes, sunglasses and readers, wide angle lenses and telephoto ,,,, all bringing into focus different stuff and making me oblivious to everything else around me. If driving fast, I do no longer see what was in front of me seconds before. Nor should I, be looking anywhere but where it’s critical when driving. Texting while driving is illegal in some states, thank goodness.
In our enterprises, we make choices about lenses all the time. We don’t call them lenses, even though they affect what we see and subsequently interpret. If our lenses are the wrong ones, then we’ll just have to deal with interpreting what we see and worry about what we don’t see. If our lenses cover too much to absorb at once, because we’re driving the business so fast, then we’ll just to trust our luck that we did not miss an important turn-off or on-ramp. If our business roadways are all smooth and devoid of danger or speed traps, then it doesn’t matter so much. If the scenery doesn’t change or we’re not trying to take our enterprise anywhere new, then all is good.
Among our most important lenses are what we measure, how well we measure, how often we measure, and what we do with what we measure. They are important if we do actually do something of value with what we measure in time to make a difference. It does us little good to find out that we missed a turn-off two weeks or a month ago, unless we’re pretty good at u-turns and restarts, except when opportunities don’t wait around for us to u-turn. Also, who decides what to measure, or who interprets what we measure, or who decides what to do with what we measure, or who reports what we measure, or doesn’t report what we measure is likely to matter a whole bunch too.
When we go for our annual physical, all the same measurement stuff applies, and we surely hope the doctor and the lab get it right. I lost a cousin to cancer this weekend because a doctor and a lab got the measurements wrong years ago when they could have done something in time to save Bob’s life.
So, when was the last time you checked the lenses you use at work, home, or play?
“There are three classes of people; those who see, those who see when they are shown, and those who do not see.” Leonardo da Vinci.
Who’s Not on Board?
Not that long ago, a major mobile phone carrier had an effective advertising campaign with a catchy slogan. Yet, I found their slogan troubling. It was troubling in that their banner, “We have fewer lost calls” left with me an impression that “we’re not as bad as the other guys” was written with the intent to establish a positive differentiator of quality and reliability. My reaction then was that the goal was to be the best of the bad, or cream of the crap. Upon reflection, I realized that the problem was with me, and in fact, the carrier’s message was the right one. This carrier was actually speaking the language of quality, not of spin (as I confess was my reaction). Quality is measured by the likelihood of failure against a specification. In their case, our case, it was a message that what mattered to the customer was continuity of service and there is a probability that that service will be interrupted, and the best do it fewer times. The carrier must have studied Dr. Noriaki Kano and realized that in some cases, the best can mean fewer defects, and failures against a basic requirement can only bring dissatisfaction. For the basic requirement of service availability, a service unavailability measure is the right metric and satisfaction is not achievable, that is, zero defects can bring only zero dissatisfaction.
This last week, we witnessed what appeared as truly bizarre behavior from Apple. The new flagship, the iPhone 4, has a troublesome performance problem with the reception. The very beautiful phone integrated the antenna into a smooth metal casing, creating a problem when the phone was held in a particular, albeit very normal, way. Some would argue that the decision process for the product launch suffered from an unhealthy bias wherein form trumped substance and engineering warnings. It’s saddening, coming from an exciting and innovative producer of form and substance. What was befuddling was the chairman’s response to the defects. It began with hubris with what appeared a dismissive tone that trivialized the problem …. Customers don’t know how to hold our phone properly, what’s all the fuss about; it’s the bad media at play. As the evidence mounted of the reception calamity and the web took over, sharing the data, the next stage of responsiveness focused on an attack on the competition, asserting that other smart phones shared the same problem. From here it sounds like it’s about “my” product and brand, not the customer pain. That strategy was a big boo-boo. Motorola, HTC, and RIM did not remain silent, each stating that their designs did obey the laws of physics and sound engineering, after all, customers wanted continuity of service.
Today’s connected world is a dangerous place to forget that respect for the customer and respect for the competition are essential for sustainability of brand value and economic goodwill, just ask Toyota. I’ve always loved Apple’s creativity in form and substance. I also believed that Toyota put the customer first. Funny how often bigger does not beget better. It’s called entropy, another engineering insight often forgotten.
On reflection, I wonder how much of the problem had to do with poor engineering and how much with a culture of “enforced optimism” or some variant of the “emperor’s new clothes?” The evidence to date on the catastrophic BP oil rig explosion and the subsequent environmental opening of Pandora’s Box seem to support the dangers of “enforced optimism” leadership behaviors.
How often does the “enforced optimism” show up in planning (pick any type), budget sessions, objectives, progress reviews and reports, investor sessions, group decision making, scheduling and commitment setting, …., other stuff?
Thoughts?
It’s Your Call
A blown call costs a pitcher a perfect game. This week, it really happened and everybody felt terrible, apologies ensued and the guilty umpire felt genuine remorse and accepted full responsibility for the failed measurement. A poor measurement did not change the perfection of the real performance, a better gage, instant replay validated that, but rather the record of what happened. Those that missed this story and are evaluating the statistics of pitching performance will only have the historic data to evaluate, data that is a false witness of events. Imagine the effects of all the poor measurements in one year of major sports events. Do they change important outcomes? Do they steer rewards or punishments? How about all the stuff that goes on with gamblers in or out of Las Vegas?
Bad measurement in sports evokes big emotions, outrage, indignation and a score of aftereffects that include bragging rights. Does bad measurement in our enterprises conjure similar reactions? What are the chances that we are making decisions as a result of poor measurement, the wrong lens, an obstacle in the way, poor technology, get the picture? If so, the issue is ubiquitous. In over two decades of helping organizations with performance gaps, poor measurements have always been at play, sometimes with disastrous consequences.
The issue is not a simple one. For example:
• Do we use the data that we have and try to conjure meaning from it? Or do we start with what we want to know and then measure accordingly?
• Are we sure that the movement in the data is representative of what is actually happening within the process?
• Do different individuals or functions measure differently? Would they come up with the same value when measuring the same process?
• Does the data just not make any sense?
• How about our “calls” on what we evaluate? Do two managers reach the same conclusion about someone’s performance? If not, who is right? What are the consequences to the individual?
• Do we introduce our own bias into the measurement and evaluation?
• Do we have folks who are easier graders and those that are more demanding? Do they evoke similar or different performance?
• How much of our decision process rely on a subjective call (an opinion) versus an objective measurement (an actual number)? Do we know how often our calls are wrong?
• Do compliance requirements change how we measure performance?
• What happens when lab results are wrong? What if wrong results bring really bad news or they mask the bad news and bring good news?
• Are we ever surprised by events that would have been very visible had we measured differently?
• Does a part of the organization hide or hoard data?
• Do our customers measure our deliverables and call about problems that we should have prevented them from experiencing? What did our data say?
• Do we have our vision checked from time to time? Why is that?
• Do we ever catch how some advertisers deceive with clever use of statistics? How about in our enterprises?
• Is it safer for ourselves to call someone “safe” rather than “out” when we’re not sure, just in case? Consequences are often more severe in one direction versus the other.
• Have we ever spent a lot of money and resources on a decision made with poor data?
So, how’s our data today?
Think About It!
Have you ever thought about how we think, particularly the kind that leads to decisions? What drives important decisions? How do we know if we made the “right one”? As we enter into the New Year, how will we decide how to navigate ourselves and our enterprises successfully?
How we approach this tends to fall into two major categories (with some dangerous variations within). First, there’s the type of thinking that comes from experience. We observe and experience, develop some pattern describing the experience and tuck it away for reference. When we believe we recognize the pattern, we pull that memory out and make some conclusion about what is in front of us. Some people can store lots more patterns than others, have longer memories and can capitalize from that. It’s called inductive thinking and people with “good” inductive thinking can market that as experience. Hiring practices validate that the marketplace places a positive value on that. Experience is not always good, nor is experience a sure bet, so some further prodding and poking is usually a good idea. There are some areas where inductive thinking can be very valuable, particularly when there is little time available for decision making. It is a subjective realm, nonetheless.
There is another kind of thinking that has to do with the world of math and data and science (real science, not the subjective pretenders…). It requires evidence that is measurable and leads to the quantitative practices where many people will reach the same conclusions when presented with the same data. This kind is deductive thinking and there are lots of professions and methodologies that are built upon deductive thinking. It’s very powerful, learnable and very scalable. It too has limitations in that the person who engages in deductive thinking must learn how to do it correctly and not all of us learn or remember well. Experience here is important insofar as we can use it to demonstrate competence in the applications of the rules and tools. It is supposed to be the objective realm, subject to our ability to measure correctly. Memory also plays a role here. I would be challenged to apply much of what I learned in engineering school decades ago with any confidence.
Variations of the two types of thinking, comingling, and the influences of biases are always at play, so certainty or absolute correctness is elusive. There is however a dangerous type of thinking we may all be subject to. It’s called wishful thinking. We know it well and if we are practitioners in it, we now it’s capability to disappoint. We bring to bear what we have in deductive and inductive capabilities and we put the right bit of optimism and conjure really great scenarios. Sometimes wishful thinking blinds us to lots of really good inductive signals and deductive facts along the way. Some misapply the meaning of positive thinking to the process and don’t survive to tell about it.
So what is the right mix for the upcoming year? We know that there has been a lot of change amiss. The financial rules of engagement have been rattled by poor inductive, pseudo-deductive and far too much wishful thinking so as to create a fair bit of timidity. The way we are interconnected and interdependent in a multi-polar world present us with new data and rules as to what may or may not work. So how do we decide?
- Are we planning for a good year? Why so? Why not?
- Is uncertainty scary or energizing?
- What opportunities does a new playing field present?
- What do we induce, deduce or wish for 2010.
Happy New Year and Good Hunting!
What’s the Score?
Have you ever balanced a scorecard? What did you do? How did you decide what balanced meant? What did you do with the scorecard? Did you win? Was it a competitive win or was it a within the scorecard win? Would an outsider evaluate you as a winner without seeing your scorecard?
The balanced scorecard has been a source of lots of debate and consulting armies going about guiding organizations on keeping score. My observation has been that too often the exercise has amounted to filling data into a predetermined template from what data is available and accessible with follow on work to “interpret” what the scoreboard means. What continues to nag me is the distractions that some predetermined “balanced” views may precipitate.
First, no two categories are ever equal. But if you try to make them equal on a scorecard, you will get unintended consequences. The more something is claimed in a slogan, the less likely it is true in measurable practices.
“Employees are our greatest asset” is a statement of value, not a measure of opinions that are captured in an employee satisfaction survey score. What does the scorecard really measure? I would argue that, if asset quality matters, maybe it should measure how quickly we acquire good assets, secure the most out of the earning capacity, and then how quickly we dispose of bad assets. However, political correctness and actually treating people as assets is challenging and likely look bad on surveys. A scorecard would be sensitive to what the game is and how people are to be utilized at what stage of the game. The categories are dynamic as well as the numbers. Take a hard look at what tracking “training hours” does within very large organizations. You will find some interesting compliance systems that actually govern the speed of learning (check the on-line stuff) so that the scorecard hours are achieved. Yes, we are willing to slow down the quick studies and reduce their productive time for the sake of the “score.”
Financial strategy is even more dynamic and much more complex. What we desire to emphasize on the balance sheet or the income statement is very different for industries, organizations, health, global economy, volatility, growth, risks, competitors, asset mix, exposure … to name a few. So, the scorecard categories and weights are dynamic, not static, so the scorecard structure is not structural, but fluid. A structured scorecard in a dynamic environment will always lag the signals and thereby trigger responses inappropriately. Does it enable or constrain the best decisions? And, we can’t use the scorecard to score itself.
Customer satisfaction is a fascinating score to evaluate, if it leads to better decisions in time to make a difference, where it needs to make a difference. How often have we observed what appears to be poor business decision making in order to appease a “customer tyrant” for fear of low satisfaction scores? We all have. So again, the complexities of a dynamic world require sufficient agility in the relationship between what matters virtually so that the “score” leads to proper action. Again, what does balance in the score really mean and what does it really drive in behaviors? Does the statistical “dulling” effect hide the scary customer stuff happening on the fringes where risks are born and changes are incubating?
Now, for those that feel this is going in the direction of winging it and data anarchy, not so. Score is important, but balance cannot always be predetermined or should be hard-wired in dynamic environments. If life is quiet and stable and predictable, this may be an irritating and irrelevant sounding blog posting. I don’t know anybody like that anymore.
The questions that we should be vigilant about measurement and scorekeeping must be configured around decision making only. Data is useful for what I am about to decide. That’s it. The scorecard, scoreboard, or dashboard must fit the game we are playing and where and when we are playing it. Balance can be a dynamic challenge for multinational entities in a multi-polar world.
This should be exciting, if we agree. It is exciting because technology today enables transparency at the speed of light. Our interconnectivity and networked interconnections have the capacity to render a view to enable dynamic balance. Balance is a consequence of judgment and agility. Both require virtual transparency that grabs new and relevant lenses to look at what is happening when the decisions can alter the future most effectively.
Thoughts?
Throwing the Flag
Those who follow sports know that the quality of officiating is receiving much needed and overdue attention. In fact, there is one officiating team in NCAA Football that is currently sitting on the bench for terrible calls in very important games. In fact, the poor officiating may have determined the winners and losers. Sports are a great place to talk about poor measurement because we’ve all seen it. With the advent of better technology and high definition instant replays some of the boo-boos are much more evident. Competent people in the business of evaluating performance of any type are very aware of the impacts of measurement and very skeptical of any decisions people make …. Measurement issues surround us …. I used the word competent intentionally because those that don’t pay serious attention to the quality of measurement and render opinions, advice, or recommendations on data or information are dangerous people to have on board.
Let’s stay with college football for a little longer. Bad calls lead to new conditions that redefine all of the subsequent plays. Some calls don’t end up having terrible consequences, but others do. (Apply these points to everything else … work, play, health, safety, purchases, promotions, politics, war ….) Let’s take the bad call that changed the outcome of the game.
- Rankings changed among the competing teams
- Who played at bowls changed along with the commensurate compensation and attention? Also, all of the people who went to bowls changed, … , the travel, vacations, and lots of other secondary and tertiary order effects.
- Coaches got fired, hired or moved. Lots of the press chimed in labeling winners and losers. Life changing events took place ….
- Different kids got recruited by different coaches….. And on and on and on….. the dominoes keep falling …
- This was due to just one bad call (measurement) that changed the game, just one game.
Apply that to any professional sport, the gambling industry, and the lives of the happy and despondent whose lives revolve around the sport … it continues. There is good and bad from all of this …but it is different. So the better team doesn’t always win, and it wasn’t from poor performance….
Now, how about business performance? Have we considered just how much is impacted by poor measurement? How many big and small decisions alike were made on the shoulders of a bad call? Was the bad call on the shoulders of bad information or data? How about performance appraisals, promotions, demotions and the like? Any capital spending decisions made on poor data? Did we ever spend bundles fixing something that wasn’t broken beacuse our data was crap?
Sports are changing and some for the better as our measurements improve.
How about what we do?
“One Thing …”
It’s really great to be surprised, particularly when it’s a good one. For close to two decades I’ve been ranting about three rules, the only three rules we need to execute, improve, or accomplish close to everything. There are many attributes that contribute to success, brains for example, but those are not what this is about. The three rules are focus, discipline, and follow-through. They are applicable to better golf, getting a prom date, getting through school, and an endless list of goals to meet or ends to achieve. I have found that trying to get “there” and stay “there” without following all three is unlikely, geniuses included. What most of us call luck in the successes of others may have the hand of randomness, but more likely you’ll find the rules behind the “luck.” I’m pretty sure that by now some have figured out that “luck is when preparation meets opportunity.”
My surprise came at a conference this past week, one dedicated to performance improvement. These conferences almost always have gems and nuggets of insight and success stories, and this last one had a real humdinger. My first inkling that this was going to be good came when the presenter turned out to be the President and CEO of the organization. You typically don’t see folks from the C-suite presenting a story about performance improvement to a room full of professionals, consultants, gurus and geeks. With his story, Robert Weiner of PAS Technologies need never fear. I will leave the details out, but available to those with enough initiative to hunt him down and request a copy of the presentation. Those in the aerospace industry should jump on this, like now! It has ample examples of the three rules and lots of brains to boot. The three rules were evident and brilliantly executed. I can’t say that often, sadly.
There are two gems that stand out and can serve as benchmarks for those seeking to transform. Transform can apply from self to enterprises and everything in between. The first application has to do with understanding that fitness, typically governed by the laws of physics, is a precursor to exceptional business performance, typically governed by the laws of economics. Obese enterprises will not win races and sustain leads. Business fitness makes winning possible. The second part has to do with how to measure success and when to change focus, discipline, and follow-through. Robert Weiner got it right. As a consequence, his team was able to snatch success from the jaws of failure. If you want folks to get aligned, then they need transparency into what matters. If you want them to improve, they need the means to build capability that is measurable and scalable. If you really want this to work, focus on the essential. Then make sure all the consequences match. It’s hard to “walk the talk” when the signals “stumble the mumble.”
The coolest surprise came when he described the transformation that was executed with only one metric for fitness, then, and only after fitness was achieved, he shifted to only one metric for winning. Yep, one metric for each phase and that’s for the entire enterprise. It worked and will work. But this is not for the faint of heart or feeble in resolve. Many will moan that their metric is not there or that certain metrics belong for correctness and balance. Get the presentation from Mr. Weiner, read and weep. It is good stuff. When we pick the right one, the secondary stuff finds its place and aligns to contribute, rather than distract. Fitness requires all the systems to work in sync with clarity of purpose and outcome. It is hard and is likely to hurt, and that is good.
As Curly, the crusty cowboy in City Slickers said, “Do you know what the secret of life is? … One thing. Just one thing. You stick to that and the rest don’t mean …” we know the word …..
In the Dark?
There’s a pretty interesting debate going on between some really bright folks about whether information, or history, can be destroyed. It’s not among real historians, archaeologists, biographers, or anyone else most of us would imagine. It’s among very renowned physicists, luminaries including Stephen Hawking. Dr. Hawking was among the very early to write for the enlightenment of us outside the genius gene pool with “A Brief History of Time.” He is also credited with the conceptualizing and predicting of black holes.
Black holes are entities in the cosmos whose density is so large that they pull in, “suck up” everything around them including light. Nothing gets out, like some in-boxes we all know about. Black holes and their effects on information are what the big debates are about and where reputations are at stake. We know that the regular types of information and histories are destroyed all the time. Information or history is destroyed by cataclysms, wars, book burnings, oral accounts, my faulty memory, and a very long list of other means, including our scary hard disk crashes. It’s sad, but creates lots of opportunities for sleuths of all disciplines.
Here’s the fascinating part. The real physicists out there will rankle at my oversimplification, but I’m just not that smart. A big part of we actually “know” about what’s out there in the cosmos comes from bigger and better telescopes and other measurement technology. The stars, planets, galaxies and other cool stuff are visible because light has travelled big amounts of space-time. For now, let’s just say that it has covered very large distances across space in very long periods of time, light years in fact. We know by now that what we see all happened in the past, including everything near to us since light had to bounce off of or emanate from what we “see.” Light moves very fast, so we believe it’s happening in the “now” and that’s comforting to many.
Here we go. If nothing can escape the black hole’s pull, including light, then the information about a star or galaxy is lost on the way to us if it comes near a black hole. As far as our instruments can tell, the star never happened, the information is lost. This argument has been going for a long while and even Dr. Hawking has moved from his position on the subject. His new position involves perspectives that include more dimensions than we can understand and multiple universes, some without black holes. This stuff is not for everybody.
So it is all about light. We’ve known about it for a long time. We use terms like enlighten, bright, luminary, obscure, in the dark, and other descriptions that have to do with information, knowledge, and other types of history. If we don’t put light on something, or if does not give off light that reaches us, information is lost. It is as if it never happened. Worse, if our management and information systems take data in and it never gets out, information is lost. We have black holes of our own making.
Maybe it’s time to take the debate from the realm of physicists, astronomers, and cosmologists and bring it into the realm of operating an enterprise. Information is being lost, history of what happened no longer exists, and we will make some decisions in the dark. These black holes can be found everywhere. In fact, the post 9-11 investigation revealed that critical information was lost because of interagency black holes and individual biases.
Dr. Hawking has concluded that if we are in one of the parallel universes that does not have black holes, information is not lost. So you can’t have it both ways in any given universe.
But there is hope for our businesses. We can change what and how we execute and create a black-hole-free workplace. It’s good for our health.
Fast Times with Heisenberg, Gretzky, and Carroll
Ever hear of Werner Heisenberg? Unless you are one of those people (confessed addict here) that is curious about lots of stuff, in this case quantum mechanics, you may not really care. Quantum mechanics has to do with the behaviors of the really small, what some physicists look at. What is really interesting about Heisenberg is a principle about measurement he developed, the Heisenberg Uncertainty Principle. He says that the more you want to know about a particular attribute like position (where it is), the less precision you will have about another attribute like velocity (how fast it’s going in a particular direction). I’ve believed for a long time that it is true about bigger things than the subatomic. It is true about what we measure and evaluate in our business performance. Stay with me, this may help.
One example is akin to the example above. The overwhelming majority of business data that I’ve been exposed to focuses on where performance has been, say position. That is important since we need to know what our demonstrated capability to perform is. The more we know about position, the less we can say about how fast it is moving in a particular direction, velocity. Our performance has a velocity, and depending on what aspect of velocity, a very specific direction. The velocity going forward is not usually the trend; it can sometimes require a little more calculus than algebra.
In fact, performance has multiple directions; the most obvious are cost, time, and quality. We can say with complete certainty that they move at different velocities (it’s a safe bet). The really important point is that we seldom, if ever, look at the velocities for decision making. Agile people and entities do. They also keep that part a secret (it’s called competitive advantage). If you follow sports, you may have heard the quote by the hockey great, Wayne Gretzky, “I skate to where the puck is going to be, not where it is.” Since Wayne has to manage his own velocity he needs to manage it to where he needs to be, at the puck. Applies to our businesses, doesn’t it? Performance decisions only affect the future, where stuff is going, not the past (unless you’re a good book cook).
I’ve spent the better part of the last two years on this topic and it has fundamentally changed my lenses to evaluate performance, capability, metrics, dashboards, product development, voice of the customer, innovation, competition, negotiation, human resources, … ad infinitum. Looking at the world through that different lens and feeding it through a different dashboard also changes our insight into where the ugly risks are and where to invest resources and time on improvement strategies. Additionally, the velocity lens redefines the applicability of gaming theory and network analysis in business decision making. These are really cool beans.
No reminder needed that the world of leading and managing enterprises is fraught with ever faster changes.
- Do we know how fast?
- When we execute the changes we’re deciding to make today, will we end up where the puck is going?
- Do our project controls and toll gates enable or constrain our ability to respond to an ever moving puck? Do scope creep, change orders, restarts, and rework sound more like the rule than the exception?
“The faster I go, the behinder I get”. “You have to run as fast as you can just to stay where you are. If you want to get anywhere, you’ll have to run much faster.” “Now, here, you see, it takes all the running you can do, to keep in the same place.” Lewis Carroll
So, where are we going?
