measurement
Please Tell Me All About Me
For many years we’ve been helping our clients sort out how to create and sustain value for their customers. Few would argue that the Voice of the Customer is essential. We all too often find that the Voice of the Customer collected and reported is more about the organization, how well they are liked, or opinions on performance (not real performance), rather than those that focus on the customer’s world. Hearing and understanding the actual Voice of the Customer has too often been interpreted from gathering data that feed survey instruments, reports, dashboards or scorecards. By searching for and producing data that can be rolled up, opportunities for critical insight are lost. Feeding the tool or report can become the goal and by the time the report comes, the customer might be gone. Are we missing something? “Happy families are all alike; every unhappy family is unhappy in its own way.” Leo Tolstoy, Anna Karenina. Count Leo has a point.
Let’s consider firms in the business of making money. The public sector has lots of added complexity in sorting out voices and timeframes. The Voice of the Customer is or should be The Voice of Revenues. Understand why we make money and who has it. What we’ve found often are a great deal of questions that deal with how we make money, and opinions on how well we do the basics, not why. Consequently, we spend lots of money on questions we should be answering with our performance capability data. Customer satisfaction scores are not performance capability data.
Here are some questions to consider:
• How do we know whether we are capturing what we need to know from our customers?
• What do we do with this customer survey data? How and when is it useful?
• We are measuring service and product satisfaction, and yet why are complaints rising and customers leaving?
• There are so many “voices” to deal with, how do I cope?
• How much change are our customers facing?
• How does our service impact their ability to succeed?
•How is time spent in our organization:
1. In a stable repetitive work stream (The process world)?
2. Building and implementing new solutions (The less stable project world)?
3. Responding or reacting to changing requirements (The unstable world)?
• How and when do we find out about customer facing issues?
• Is that good or bad?
• How dependent are we on suppliers?
• How much do our suppliers impact our customers?
• Does our current Voice of the Customer process and information keep up with the “drumbeat” of the marketplace?
Any thoughts?
Class Struggles
Best in Class! How often do we run into the term? I believe it’s a term that has lost much meaning. I suspect that overuse, or selective playing around with what “class” we pick, or the unreliability of rating organizations render it useless too often. In the world or process improvement it is applied to a goal setting step for evaluating how large a gap there is to close and subsequently chartering projects and resources to close that gap. There are some pitfalls to the approach:
• If the “class” we are selecting as a benchmark is a poorly performing one, we may be aiming at becoming the “best of the worst” or “the cream of the crap”.
• If becoming best in class for a unit within an organization does nothing to positively impact the performance of the total organization, we may be investing in meaningless improvement.
• The goal may become obsessive, a powerful distraction, directing attention and resources away from value adding opportunities.
• The customer, shareholder, or taxpayer does not benefit.
The last bullet is very important. Most organizations are not created with a primary purpose to have functions, departments, employees, IT systems, training centers, enterprise applications, procurement groups, or resources of any kind. That’s not why enterprises exist.
• If they are commercial organizations, they exist to deliver goods and services that financially profit so that they can earn the trust of their investors through returns. Yep, they are around to make money. The best ones do it legally, ethically, with respect to all stakeholders, no adverse externalities, and with a vision to create new value. They deliver value to customers and returns to investors.
• If they are a public service organization, they exist to fulfill a mission to deliver beneficial outcomes to their stakeholders (taxpayers and public at large). The best ones are effective, efficient, ethical, agile, focused on delivering benefits and positive societal outcomes, responsive to their public, and transparent. They spend public funds and deliver positive and beneficial outcomes.
• Purpose is fulfilled when value is delivered. There is a value stream that threads what delivers value and it provides the ruler with which to measure what is appropriate or lacking.
So, resources, systems, functions, departments, assets …, within the organization should exist and operate in order for the organization to thrive. That means that goals for units or entities within the organization have real value and legitimacy to the extent that they can verifiably contribute to the organization’s value proposition. Of course, this is unlikely since significant waste abounds and gaps in performance are forever with us.
The issue is not whether to improve or not. The question is how much, by whom, and to what ends. Where should we set the bar? How good is the good we should be? In a relay race, how would we decide where to focus our efforts? How do we create the appropriate focus, discipline and follow-through? Of course, most groups aspire to be the best at what they do, but unfortunately, it is overly focused on only what they do. It would be tragic, if not ridiculous, to claim success within a unit where the organization or enterprise is tanking. Our operation was successful, but the patient died.
Thoughts?
The Winter of Our Discontent
The yearly onset of winter has been a critical milestone in our history, life for that matter, on this planet. It triggered severe constraints in access to food, travel, safety and the quality of life overall. Travellers who needed to get across mountain ranges had to make tough choices, and often make winter quarters and postpone travel until the thaws. Even in war, some armies huddled in winter and fought from early spring to late fall. Today, winter continues to constrain and often reminds us that our advancement and technology can be humbled by severe weather. Those in the tropics see a different face of nature, the tropical cyclones and monsoons.
This winter’s snow storms have rolled in with a frightening frequency, size, and impact. For travellers, their effects have been far reaching. Our highly networked transportation systems suffered from and precipitated aftershocks, stranded trains, planes, automobiles, pedestrians, and passengers, … , felt well outside the snowed in airports, streets and terminals. For airlines, this winter has caused the most flight cancellations on record. With steep fines brought on by regulatory “bill of rights” constraints, risking “maybe” flights have far too much downside risk making flight cancellations the less costly alternative. The broad brush of regulation brings on predictable rigidity for the many in order to control the few. Airline losses from storm cancellations exceed $600 million with plenty of winter still left.
The impacts on businesses and enterprises are incalculable, but many economists believe that the adversity this winter has wrought will be felt by many for years to come. The fragility brought on by the forces of nature affects some enterprises more than others. If a business requires travel, face to face transactions, or physical accessibility, the consequences are more severe than those that don’t. Brick, mortar, asphalt and place bring unavoidable rigidity. While technology has increased the effectiveness and efficiency alike, value does not arise until customers derive the benefits they seek. Discussions about lean and waste eventually come to what adds value and what are currently unavoidable costs.
I like to use the story of two business partners, one in New York and the other in London. The year is 1711, and the partners must meet twice a year to review contracts, strategies and business direction. They will alternate venues. The meetings run about six hours. So, one partner travels for eight weeks on a galleon through whatever the seas bring to get to the meeting. Two hundred years later, their descendants repeat the process, but now travel eight days by steamship and 100 years later the subsequent pair makes the trip in eight hours by air. Improvement in travel reduced wasted time, but it was still wasted. One could argue that all of the time in the six hour meetings added value, but that is arguable by anyone who endures six hour meetings. Video conferencing changed the game, no travel with all meeting. The web changed the world and how we look at it.
Blockbuster is in bankruptcy, the iTunes world has replaced music cd media, streaming has replaced the rest, Microsoft has replaced boxed software executives with those who can reach the cloud, AOL has purchased Huffington in order to re-enter the way we access information and content.
Looking back on this winter, what would we have done differently if we knew then that it was coming? Would we have been stranded or connected?
Fuzzy Plans
“The most dangerous strategy is to jump a chasm in two leaps.” Benjamin Disraeli.
It’s October, and for many, this the month wherein our business plans go from aspirations to commitments and planned investments, or, what we will do and how much we will spend. It is at this juncture that many “stretch goals” are stretched out across time and spending with some promise of results and outcomes. In other words, we get money, people and kit in order to execute processes and projects for our enterprises. What are the probabilities that next year will be as we’ve planned? Well, how confident are we in our predictions and assumptions for next year? Does our plan plot out as a line over time?
One attribute of plans and budgets that I’ve frequently observed is the application of linearity, treating each month as a point on a line graph, not fuzzy at all. We feel fuzzy, but our system doesn’t want fuzzy as an input. How did we estimate or predict our planned inputs, processes, projects, and outputs? Reality is always fuzzy because randomness is such a big influence. When randomness is a part of multiple factors, it is a very safe bet to say that the plan and budget are not going to match a line.
There is one aspect of fuzziness in planning that can bite us. It has to do with the relationship between outcomes and consequences. Let’s assume that we have performance targets that we’ve committed to. These targets have measurable attributes that speak to time (cycle time and schedule), cost, and quality (defects and meeting requirements). Also, unless we’ve introduced some bias (made them bigger or smaller) due to timidity, overconfidence, bad math, or enforced optimism, our targets have some probability of being too high or too low. They have fuzzy, not certainty. Let’s assume for now that they have an equal probability of being higher or lower. What about the impact on the business if performance comes in higher or lower?
Often, the consequences of being late are far greater than the consequences of being early. Similarly, the consequences of spending less are not the same as the consequences of spending more. While the probabilities of an outcome might look like a familiar, like a normal bell curve, the consequences curve will not look anything like that. Multiplying likelihood by impact and then summing the values might well be a negative number. This is particularly true if we use historical data as a unit value to forecast future performance.
• Should we then introduce bias?
• What are the objectives of the plans and budgets?
• How do they affect what will happen?
• Are they static or dynamic instruments or tools?
• As time’s arrow moves ahead, does our view of the future shrink with what is left of the plan year or is the plan year always the next twelve months?
Check Up or Check Out?
Over the last two weeks, I’ve been going through a round of “safety checks” to evaluate my personal operating systems. Although the medical professionals may have more sophisticated terms, they are nonetheless evaluating my operating capabilities to see how much may have changed. These capability evaluations have paid off with rates of return that run off the charts. I am just like many business operating systems in that I’m subject to the risks of decay and disruption. Decay and disruption mean that some things gradually eat away at my capabilities while others can have a very big impact in a short period of time. I also run the risks of relying on the wrong data for decision making, just like a business might. I could, for example, believe that if something is wrong, my body would always let me know with pain, discomfort, fever, or other tangible nasty stuff. The big risk of using that kind of data is that I may find out way too late in the process and may not be able to recover. If I were a business behaving that way, I might wait for complaints, or rely on catching failures at the end of the process. If I were a business behaving that way, the consequences might be terrible since waiting on complaint data may tell me I’m already dead with certain customers before the complaints get my attention. Reality is a harsh teacher that ignorance is not bliss and complacency kills. Feeling good is not a reliable indicator of being good.
I combine this yearly set of assessments with quarterly check-ups so that my doctor can detect changes in my condition. Frequency of measurement is really important, particularly when systems are subject to wear and tear, or suppliers are changing, or requirements are changing, or the environment is presenting new constraints. It means that I need a frequency of measurement that can catch stuff in time to do something about it. Of course, having great measurement without the will or means to do something about what the data says is a waste of time and money. I have someone to hold accountable for the quality and interpretation of the data, but only I can be accountable for doing something with the data. Data is expensive, analysis is not so expensive, but both are worthless without decisions and actions when appropriate. In fact, data can have value if it improves the decision making process. Data is for what I am about to do … for decisions that need to be made, even if it is about what we had done before.
One unhealthy condition people can share with a business that will eventually kill any business is obesity; process and cultural obesity. It’s all the waste we carry around in our processes and decision making. We’ve all seen it; many of us have done it or caused it. It not only makes us slow, it also makes us expensive. In really good times, we can get by, but when times get tough, keeping up while carrying the useless load becomes challenging. I’ve always believed that fitness precedes performance. The things that I want to do may require a big investment into the things I need to do. Aspirations may require lots of perspiration.
This is the time when many of us are finalizing our goals, aspirations and planned expenditures for next year … it is all about what we want to do. Are our capabilities up to the task? When was our last check-up?
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!
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