A simple example is a goal would be to increase revenues. Here are two real examples of outcomes that resulted for different organizations.

Disney’s Magicband. Disney made a significant investment in truly innovative software and hardware because they knew it would pay off in terms of revenue. A key to that was extending the average guest stay at Disney World from three days to four and a half days, a 50% increase, and the way they did that was largely through education (of course, in a magical way) to help the guest plan their visit through the My Disney Experience portal. So what are some outcomes that you could foresee from this revenue lift? Well, one of the most obvious if you are having people stay 50% longer, is that occupancy of their on property resorts would change dramatically, and if you failed to foresee that outcome, that could be a disaster for both guests (customers) and cast members (employees).

Starbucks Mobile Order & Pay. With a similar goal to lift revenue, Starbucks chose to also invest in software to change the customer experience by allowing them to order their food and beverages from their My Starbucks Rewards app before entering the location. With a long list of foreseeable outcomes, one of the most glaring is that at certain times of day, the employees they call partners are already at 100% productivity and lines can be long, so adding any additional orders into something that is already at capacity could be an employee and customer experience disaster. So leveraging from the learnings of restaurant reservation app OpenTable, Starbucks constrains the number of mobile orders they will take in five minute increments so as not to overload the system.

Shared Performance is an organization specializing in Outcome Management and they enable an organization to track all organizational goals and outcomes in one software platform, from the most strategic to the most tactical.  Shared Performance is the key missing piece organizations need to know in advance when or if any of the short or long-term outcomes is at risk. No other solution enables an organization to track their outcomes in real time in a way that alerts them when an outcome is at risk – with plenty of time for them to decide how, or if, to respond, confidently keeping all other outcomes on track. 

Back to the boiling frog – what specifically is caused even the best and brightest leaders to come up short in aligning and managing outcomes across their business today?  There are five key reasons for this.

1. Something is needed to pull it all together.  With various spreadsheets, project management tools, even complex enterprise software such as ERP, nothing is able to connect everything like the patented approach used by Shared Performance.  Leaders may think they have things connected, but if that were true – they would not be missing their outcomes.  The Balanced Scorecard is a fantastic overall method, but without Shared Performance, organizations cannot get the linkages and dependencies that deliver confidence in achieving outcomes.
2. Issues surface too late – if at all.  No one wants to miss a goal, but if it is discovered that a goal is at risk – and the notification comes too late to do anything about it, that is the bigger issue.  What is needed is signal with sufficient lead time to act on it.  With sufficient lead time, leadership can assess how critical the outcome is, as well as the best use of resources to address the risk, if any.  The bigger and more common risk that relates to #1 above, is when there isn’t the proper linkage to outcomes, so there is not even a chance of getting signal in time.  Shared Performance on its own helps to solve this issue – adding what is now commonly available AI will make it even more powerful.
3. Information is two-dimensional.  Leveraging the tools in place today, especially something such as ERP, which when first introduced was transformational for organizations – still amounts to management by looking in the “rearview mirror” – with no ability to look forward for context about trajectory/telemetry data on trends.  Further, because current systems lack the ability to be forward looking, absent Shared Performance, everything amounts to a one-off report rather than a forward-looking three-dimensional view of all outcomes unfolding over time.
4. They are data rich and information poor.  While most organizations are collecting mountains more data than they used to, given the points mentioned above, they are ultimately lacking the information they need.  In many cases this leads organizations to have a false sense of security – and they are surprised when they miss another outcome.

So, that’s an overview of what Outcome Management is, and why organizations need Shared Performance – what’s to stop every organization from lining up to buy Shared Performance today?   Outcome Management is a new category of software.   This is a case of “we have seen this movie before” where what happened with Customer Relationship Management (CRM) and ERP is likely to resemble the adoption curve of Outcome Management, for these four reasons:

1. No budget for it.  While CRM and ERP were especially difficult because they emerged when enterprises were still buying software compared to the SaaS model more common today, still organizations need to have budget to roll something like this, and the cost of consulting to deploy the solution can be item
2. Threatens something already in place.  As much as you might like to think people always do what’s best for the business, the reality is that someone will probably be threatened by Outcome Management, either because it exposes a flaw in their approach, or it means shifting resources from their team to an Outcome Management team.  
3. Don’t need it until competitors use it. There are countless examples of products where organizations clearly see the value, but unless there is some clear competitive pressure to change, they can delay moving forward with this, a quarter, or even a year or more.  
4. Leaders who already feel the pain of lacking Outcome Management need to be the early adopters.  As you look at the three previous bullets, what this really means is that for short term – this has to be a CEO decision – and for all practical purposes they have already realized all of the “boiling frog” issues above, and they also understand only they can get the budget and drive this. While Shared Performance already has referenceable customers, more are needed to really move the so-called flywheel in this new category. 

So, if you know a CEO who fits this description – you should reach out to them.

So, if this is such a big problem, why aren’t these SMBs doing more to protect themselves?  Four things make a large part of this issue:

1. It’s a foreign language.  When people start talking about phishing, ransomware, network infrastructure, and devices, those are words some people have heard, but they aren’t part of their day-to-day language in running their business.  This makes it hard to know where to start.
2. No sense of urgency.  It’s fine to say huge dollars and high per centages of impact, but when you don’t understand it, or how to talk about it, it can become a “not here” bogeyman sort of fear where it might keep you up at night, but there is nothing on your to do list today that will help you feel you have mitigated the risk in a quantifiable way.
3. No one is responsible for it.  If you are smaller, and you don’t speak the language, and you don’t have a way to quantify the risk to drive a sense of urgency, it’s pretty hard to assign it to anyone when budgets are already pretty tight.
4. There really is no one size fits all solution, and custom can be expensive.   It’s easy to spend a lot of money on cybersecurity, but the good consulting companies often don’t want to help with little organizations with small budgets, things become even harder when the company doesn’t their own IT person – it’s literally often a family member they see once a year at Thanksgiving.

With this mix of challenges, and with hackers getting more sophisticated every day – hacking SMBs starts to look like stealing candy from a baby.

So, what’s the solution?  Naturally there is no “silver bullet” for this, but for this piece, we will focus on the first point above – that it’s a foreign language.

One of the leading organizations helping SMBs with cybersecurity today is the Cyber Readiness Institute, and if you go to their web site and see that they have a “starter kit” which looks like this:

This seems like a great starter kit – but if point #1 above is true, then starting with cyber-lingo is going to keep some companies stuck at #1 and never get to 2-4, which would result in them understanding their risks and knowing what resources are needed to mitigate them today, and as their business evolves going forward.

My suggestion for getting past #1, is to start with words the business uses every day and use that to connect to the language like that in the starter kit above.  Once you have bridged #1, then the path and priority for 2-4 become clearer.  What do I mean by this, well there are many kinds of organizations, from non-profits, to retail, to professional services (doctors, lawyers, consultants, etc.) and they each talk about things a little differently.  What if you start with the basic digital assets of a type of organization, such as a professional services firm, and categorized which would have the highest risk, pain, or cost, if they were in the hands of a hacker.  See the below example which is purely illustrative and not based on actual risk of loss/hack data:: 

Note – this is fictional data in terms of the risk column, but I think this would be a clear way for a leader in a professional services organization to start the discussion.  With this foundation, you can start to discuss all of the things in the starter kit and help the business get on their way. 

Not to suggest this is perfect, only making the simple point that if you start by talking about something this organization is already talking about – and then link it to something else, be it cybersecurity, cloud services, or what have you – it seems like that would significantly increase the odds of helping that organization understand where they are, what they need, and what a roadmap might look like for them in terms of costs, risks, and other tradeoffs.

We’d love to get your thoughts on this.  The next posts will dig further into bullets 2-4 above.

Fact #1

The reason we don’t want that, is because a vote for Biden is really a vote against Trump, and a vote for Trump is really a vote against Biden.

Fact #2

The nation is badly divided which is preventing government from getting anything done, and with people getting news from different places, we have communities basically living in very different realities that won’t even talk to each other at Thanksgiving.

Fact #3

While showing signs of brilliance as a US Senator, the current US Vice President (Harris) has not been getting positive reviews and will not help in a 2024 ticket.

If you are with me so far – you might not like the proposal – but you will have to concede it is at least better a better “Not Trump” than the seemingly inevitable choice – and it’s important that you see this idea through that lens.

The Reveal

• There is a person who was once a Democrat but served under a Republican President.
• This person was Secretary of State and would be warmly received by the international community and would be adept at dealing with situations such as those in Russia, Ukraine, China, and elsewhere.
• This person is nearly 20 years younger than either of the two other leading candidates.
• Like the sitting Vice President, this person is an African American woman.
• If you haven’t gotten there yet – it’s Condoleezza Rice.

If I could think of a strong unifying Democrat to replace Harris, I would, but I have not been able to think of anyone else that could be this potentially unifying.  What Rice may or may not lack in some of the inflation, deficit, education, Social Security, health care and other issues – she’s very bright and can surround herself with greatness.  And when the time is right, Biden can step away and receive a warm thank you for his service.

Americans deserve a candidate that earns our vote for because of the promise they bring, not because they are the merely only the means to avoid someone else.  Biden should thank Harris for her time, appoint Rice, then when he earns reelection, gracefully, and with a wink, resign and welcome our first woman President, Ms. Rice.  

It does look as though Vivek will be the running mate on the Republican ticket, and a similar outcome on that side has a lot of appeal, should Trump be re-elected.  A better solution no matter who wins.

Put another way – ERP has helped organizations manage by looking in the rearview mirror – what has happened.  What is really needed, and is now possible, is something forward looking related to outcomes, like a GPS driving app.

You may remember the scene at the end of the Pixar film Finding Nemo, where Nemo is swimming past a group of fish trapped in a large net being raised out of the water.  Nemo notices the fish are all pointing in different directions.  He instructs them to all “swim down” so they are all swimming in the same direction. When the individual efforts of the fish align with the efforts of the group, only then do they have the strength to free themselves from the net – which in the moment is the only outcome that matters.  As simple as the example is – this is, in fact, a vivid illustration of the benefits of Enterprise Outcome Management.

“Enterprise Outcome Management (EOM)  is a system for deploying and managing the Outcome Management discipline on an enterprise-wide basis, with special emphasis on those key outcomes that drive and determine performance. – including Discipline, Tools, and Process”

Put another way, companies are falling short with their ERP system because they are unable to see the dependencies that cause the outcome, or outcomes, that matter most.  Many learned the vivid difference between correlation and causality in the landmark book Freakonomics .  Causality (often manifested in the form of dependencies), linked to accountability (both Discipline and Process above) are the fundamental pieces missing in the typical ERP solution.  And when it comes to larger organizations, it’s completely unrealistic to track these details manually at the necessary level of granularity, and that’s where the tools come in.

Two vivid examples of the power of Enterprise Outcome Management are:

1. ERP reporting showed everything was progressing as planned to fulfill orders.   What was not seen was the delayed outcomes that had to be delivered now to improve the processes required to achieve the profitability targets the following year.   Once the new year arrived, ERP showed the profitability problem, but the solution to implement change over nine months still remained.
2. Growing customer satisfaction and competitive demand saw declining orders but the solution was not in operations, it was a lack of outcomes achievement within the marketing and product strategies last year which showed up in lagging ERP metrics now.

We still need ERP, so it is still necessary – but it is no longer sufficient. Today the importance of Enterprise Outcome Management is clear for both tactics and strategy and not leveraging the tools needed to stay on top of this, makes life much harder and less predictable than it should be for senior executives.

One of the biggest challenges with any big change is that it can be expensive and risky, and it can be much easier for senior leadership to say “no” than pursue the change unless there is a clear forcing function (such as a competitive threat), or an overwhelming business case.  Things that prevent a major transformation are very well explained in the book, The Innovation Biome, by Kumar Mehta – available on Amazon and required reading for anyone working in or near this arena.

Many have written specifically about digital transformation, and there are all sorts of pictures depicting what it is and how to think about it.  This one by Mike Rogers is an interesting take on it.

For the past ten years, I have led work at several big companies including Disney, Starbucks, Microsoft, and others.  In some cases the work was labeled digital transformation at the outset, and in other cases, it was only called that after the fact.  What I have learned is that there are some classes of work where it was called digital transformation before the work began, and some where it did not, and I am going to use some examples to elaborate on why it matters.

• Start with a very simple business goal.  In one case, the organization had a goal to grow revenue by 50%, and that led to discussions about how to achieve that, which led to the identification of a radically improved customer experience, which ended up being a very innovative use of technology that had never been done before.  The company made a huge investment in this effort, and the return on investment was much faster than they anticipated.
• Start with technology and then back into a business goal.  Another project started with the idea of digital transformation that also related to a radical change in customer experience.  Because the business case was only a secondary consideration, the project went down a number of paths that turned out to be a mistake.  In retrospect, it’s obvious that if the business case had been the driver, it’s likely that fewer mistakes would have been made.  While this effort took years longer than it needed to, to see the light of day, it finally did, and it was every bit as successful in terms of return on investment as the other project.
• Start with the realization your business and your employees deserve better.  In this case, a large global organization realized that all of its internal systems and processes for things like accounting and human resources were badly out of date.  It dawned on them that even while those departments were not what made the company unique or special, those employees still needed to be building skills they were proud of – that gave them some hope for advancement and promotion.  So that was a project that was labeled digital transformation from the outset, and while the return on investment was subtler – the decision was clearly a good one for the ongoing success of the company.

Over the last year, I have been working in an industry that is new to me, commercial aviation, and what I have observed is that there is a category of digital transformation that is new to me, but it won’t surprise me if there are attributes of this opportunity that extend to other industries as well.  Most aircraft flying around today are old.  Boeing 737s that were made 40 years ago can still be flying around today, and Airbus A320s, which are newer, can still be over 20 years old.  There are data buses on all aircraft, that in large part for safety reasons, broadcast status information about the aircraft, whether it is in the air or not, every minute, sometimes more frequently. Everything from how fast it is going, how much fuel the aircraft has, the level of potable water on board, to whether a door is open or closed, and on and on.  There are two things that are shocking about this data:

1. In some classes of aircraft, there are over 23,000 different pieces of information being broadcast at least once per minute.
2. Airlines have historically had no way to get this data off the airplane, so it is what some in the industry refer to as digital exhaust.  It’s right there all day every day, but no one can access it.

This information would be so useful to the airlines in many, potentially obvious, categories:

• Real time route optimization.  You would expect that in today’s world, pilots are getting real time updates on things like wind and weather so they can make informed decisions about how to save time or fuel on their flights.    They can’t do that today because they have no access to this data.
• Aircraft health and maintenance.  With over 23,000 pieces of information, not only could you be alerted about when something is damaged or broken, even rudimentary machine learning on this data would easily enable airlines to be more predictive of when an aircraft is going to have an issue, and fix it ahead of time. They can’t do that today because they have no access to this data.
• Turnaround.  There are many moving parts and people involved in cleaning, refueling, catering, luggage, boarding, to prepare a plane for departure, and if there is a sensor that knows if the starboard door of the plane is not open, then catering has not begun, and the plane will be late if catering does not start in the next ten minutes and the right person can be alerted.  They can’t do that today because they have no access to this data.

Tapping into this wealth of data for both real time as well as historical patterns analysis as well as opportunities for machine learning and artificial intelligence leads to obvious opportunities for cost savings, operational efficiencies, and increased safety. So this then is another class of digital transformation that wasn’t even possible until very recently.  There are some simplistic and perhaps obvious comparisons to the Waze driving application and the real estate site Zillow, that those businesses were not possible until certain data was available as well.  

APiJET is a company I have been involved with for nearly a year, and they have figured out how to deliver this data to commercial airlines.  Elevāt.IoT is another company doing something similar on the ground with industrial equipment.  So there are companies that have found a way to get to this rich data and it will be interesting to see what other industries find ways to transform by tapping until previously untapped reservoirs of data. If you know of others like these, I would love to hear about them.

As usual, it reads a bit like a salary list from the NFL, NBA, or MLB where the numbers are so big, it borders on silly.  By the way the highest paid player in the NBA, Steph Curry will make $34 million this year, which is almost double the median salary of these public company CEOs.

Eavis did hint at the fact that the #1 job of a public company CEO is to deliver shareholder value, but did not comment much on the fact that many of these highly paid CEOs were in the red when it came to delivery of shareholder value.  Seeing the stock down a per cent or two would not be so surprising, but several of these CEOs were into the red in double digits which is pretty amazing.

So I decided to do something with the numbers that Peter Eavis did not do.

Eavis did (in the print version) indicate the change in stock performance of the company year-over-year, but it was way off to the right and seeing that a few were negative did not pop out at me when I read them.  When I put them into a spreadsheet, I colored the negative ones red.  I took the market capitalization of the company as of May 27, and I am pretty sure Eavis did it as of the end of 2018, so this is an imperfect set of data, but even with that asterisk, some of these numbers are pretty shocking.

I thought would be interesting to see how the CEO compensation mapped to the change in Market Cap of the company – since delivering shareholder value is their #1 job.

What I did was take the increase in stock price (per cent) and calculate the Market Cap value of that increase.  So looking at the first one – Tesla’s stock was worth $33.7 billion yesterday, a 7% increase in that is $2.204 billion.   Elon Musk’s 2018 compensation is 103.598% of the value of the increase in their Market Cap.  So scanning the list, it’s pretty common for the compensation of the CEO to be around a per cent or two of the increase in shareholder value, and that seems to make some sense.

A couple of things were most shocking in this analysis:

1. Most companies lost value.  You’d think that the top 200 highest paid CEOs all delivered shareholder value and that’s why they made the list.  Nope.  For the top 75 highest paid CEOs, 38 of the companies or 50.7% were in the red for change in stock price in 2018. That’s really incredible.
2. Some of the best CEOs had the smallest compensation relative to delivery of shareholder value.  It’s no secret that Microsoft and Apple have done incredibly well in the stock market and many people give credit to their CEOs.  If you scan down to #36 on the list, you will find Microsoft CEO Satya Nadella at $26 million, which is .009% of the value of how much their stock has gone up.  Apple’s CEO Tim Cook ended up 136th on the list with $16 million, which is just .006% of how much shareholder value was delivered.

You will notice some of the smaller percentages on the right are in bold.

Moneyball is a book and a movie highlighting that Major League Baseball was using batting average as the #1 statistic for choosing their players, when it turns out that On Base Percentage is a better indication of whether a player will help them win baseball games.  I think the way the numbers are organized below should raise some questions about whether these CEOs should be getting as much as they are – in the context of how much shareholder value they are delivering.  It seems like the CEOs who delivered the most shareholder value should be paid much more – and the 50.7% that delivered negative shareholder value should call a meeting with their compensation committee. . .

There is another silo issue that is much less obvious, but every bit as problematic for an organization.  The words people use to describe their work tend to silo as well.  People in one silo may use the same word for a very different thing, where others may use different words for the same thing.  It might start percolating a “so what?” from you – but it’s a big deal.  And I am going to give you three examples of just how costly this language barrier can be.

But before I do that – before I get to the heart of the importance of clear and consistent communication, a bit of levity, here’s a clip where none other than Jerry Seinfeld explains how strange it is when we use words to describe things – but the words we use are actually the opposite of what we are describing: https://www.youtube.com/watch?v=EbHaQYDo7Zs.

OK – on to the examples.

• Starbucks. When we were just starting out with Aimee and Janet on what was then called XOP, Express Order & Pay, the word was that executives wouldn’t approve of it.  What my colleague Tony figured out that day – the first day we were there, something Starbucks was blind to, was that the ten executives (and it was ten) who had a vote on whether to move the project forward, was using the same expression “mobile order” but it meant ten different things. One had a very specific compliance concern that fit in their definition, another made assumptions about where the customer was relative to the café when placing their order – which turned out to be an unimportant assumption, and a third was aware of a data issue in their existing systems that would make the project too complex (this one turned out to be crucial – but we solved it).  At the heart of this was that each executive was operating in their own silo with their own incentives and assumptions in mind and it was difficult for them to look more broadly.  They were using the same words and arguing, without realizing they were arguing about ten at least slightly different use cases.  Once Tony pointed this out, and got the ten executives to agree on a single definition, with no hidden or false assumptions, it was immediately approved, and all of the reasons they “couldn’t” do mobile orders went away, or were deemed solvable.
• CH Robinson. This is a large logistics company in Minnesota with five different lines of business for transportation – vessels, full truck loads, partial truck loads, and so on.  We were asked to see if there was any opportunity to consolidate technology solutions across the five different lines of business, which operate very much as standalone business units – siloes.  At the beginning of the discussion, the executives in charge of the groups said that each group was unique – that they all did such specialized tasks that it was very unlikely to consolidate anything.  We then went step-by-step to decompose all of the business capabilities that made up the transportation journey for each division.  At first glance, it looked like the executives might be right, because nearly all of the words on these different journey for each group was different. Then, step by step, we asked the difference between the words, and it turned out that in many cases they had simply been using different words for the exact same thing.  In the end, we found that there was, at most, only about 10% difference in the capabilities of any one of the business units, revealing the opportunity for massive consolidation.  So this one was essentially the opposite of the Starbucks case.
• Avalara/Zappos. Avalara is a Seattle area company specializing in tax software.  As you might expect, the word “price” comes up often in discussions at Avalara when they are talking taxes.  But in truth there are at least six specific kinds of price at Avalara – list price, discounted price, and on and on.  The problem at Avalara is that because there are teams of people focused on specific areas – they are able, within their own team, just say “price” and have it always mean “discounted price” – because that’s the group they are in. The problem occurs when they talk with people in another team – another silo – about price, they still just say “price” and that opens the door to confusion and errors and sometimes those errors can cost a lot (the case of Zappos where the price of one specific line of shoe from a brand were supposed to be discounted, but because of this exact type of silo problem, the person applied the discount to every shoe from that brand and not only did it cost Zappos millions in lost revenue – it also created massive inventory shortages because people spotted the discounts and word spread).

It’s not always easy to take a step back and wonder about the context of your conversations – but there are things that can be done to standardize language across the silos to help avoid the pitfalls of miscommunication.  Some of this is also cultural and that’s not always the easiest thing to change – but it can happen.

The “so what?” question may be coming back up – and the question is, if these language issues are so prevalent in silos of companies, and those language gaps can be the cause of all sorts of problems, how does that get solved?

In the case of Starbucks and CH Robinson, it took an outsider, a consultant to point it out.  In the case of Avalara, an employee tried to solve it by reminding people to specify which of the six prices they were talking about – that by itself was not enough to change the behavior – they would continue to just say “price” – so this raises the question – how do you solve this?  There isn’t a one-size-fits all solution to this, but starting with awareness of the problem and pointing out specific cases of where it cost the organization money, or an opportunity can be a good place to start.

1. Fear of job loss.  They worry that this product will put them out of a job.
2. Fear of not getting the bonus/promotion on their annual goals list.  They already have this item on their list of annual goals, so if some software product solves things for them, they won’t get credit and they won’t get their bonus.
3. Fear of asking their boss for money.  If they ask their boss for money for a product, there could be a “why do I need you  if this is here?” discussion.
4. Fear of collaborating across teams/silos.  Everyone is measured differently and there’s no way to get a collective “yes” on this sort of thing.

Any or all of these happen all day every day in most very large organizations.  These are what I call “boogeyman problems” the fear is not ever going to materialize into what they are afraid of – spoiler alert – there is no boogeyman (I know some spell it with one “o” – that seems strange to me).

But I am getting a little ahead of myself.  This really traces to company culture.  I worked with a company in Boston called Altitude which has since merged with Accenture, and someone on their team came up with this model related to company culture:

The basic idea is that there are three different types of companies, those that are data-driven (like a lot of manufacturing companies), those that are consensus-driven (Starbucks is a vivid example of this), and those that are vision-driven (Apple under Steve Jobs is a great example of this).  This table (from the folks at Altitude) is really useful for thinking through the different ways in which companies operate.  I do think that Silo-driven is a 4th that should be in the mix, and there is no shortage of those.

The big question is – is the organization behaving rationally when it comes to making business decisions?  The alternative is that it’s behaving politically or selfishly and that flips the benefit to the individual rather than the company and that’s a very dangerous place to go.  Harvard Pilgrim Health was found themselves to be in this spot, and as a result they “drifted” into a different operating model, and when they “woke up” from this, it was very painful to navigate back to rational ground.

How does this happen?  There are probably endless reasons – some of it is in the quality of people hired.  The old adage that A’s hire A’s and B’s hire C’s (because B’s know they are B’s and don’t want to hire anyone that’s a threat) is absolutely true – and probably plays some role in this.  The B’s are the ones that my friend Kumar Mehta (author of the truly great book on innovation – The Innovation Biome) refers to as the ones that say “no” to new ideas, because “no” is so much easier than a “yes” answer.

The real trick is gathering examples of how to get companies out of this silo culture.  It’s not easy, but it has been done and there will be more blogs on this site with those examples for the companies that, like Harvard Pilgrim, have “drifted” – to return to rational behavior.  Stay tuned.

If you grew up with Atari, as I did, you probably know, or can infer, a good chunk of that story.  A guy named Nolan Bushnell saw the opportunity to take some of the most recently created computer chips to create the ground breaking game “Pong” that was about as simple as simple could be – and it changed things forever.  Pong was a coin operated video game that took up about half as much space as a pinball machine.  One of the interesting points was that as you might expect with a game simulating ping pong, you needed two players – which was really a first for any arcade game, so it ended up becoming a popular social game in bars for people to ask someone else to play Pong with them.  I am not going to retell the story – there’s a great podcast series called “How I Built This” and in it he interviews Bushnell and gets the whole story about the fact that when you lived in Silicon Valley in the 70s, it was common to talk about new technologies at kids’ soccer games.  Since he was in gaming, lots of people in the Valley didn’t take him seriously, but they were always happy to help.

So he got the hot new computer chip and hired a guy to write the code for Pong, and it took all of two weeks (which is pretty incredible), and then he hired a guy named Steve Jobs (yes, that Steve Jobs) to run quality control – and knowing what we know now, that was an ideal job for him.  Jobs of course ultimately left Atari to start Apple, with Steve Wozniak who was also at Atari.  Jobs offered Bushnell 30% of Apple for $50,000, and he says “no thanks” – which he admits was not his best decision.  As of March, 2019, 30% of Apple is worth about $250 billion, which would be a 5,000x return on that initial investment.   Back to Atari – Bushnell he ran into some issues, they couldn’t keep up with demand, it was a very capital intensive business, and copycats were popping up all over because they had never filed for patents or copyrights.

Seeing how much money these machines were making for his customers, people pumping quarters in them all day long – he realized he was on the wrong side of the supply/demand side of this business, and working way too hard at it.  As the manufacturer of the machines that would go into bars and restaurants, for a fixed cost, people were pumping quarters in them for years and they were creating significant cash for the people who had  them.

So he decided he needed to start a chain of restaurants that would be able to make those kinds of annuity-like revenues from these fixed cost machines.  But he didn’t want to compete with his existing customers.  He figured he had to create a whole new market.  He picked kids.  And he needed to create an experience that worked for the parents, that also required waiting – so the kids were assured to pump quarters into the machines while they waited for their food.  Pizza was the answer.

Yep.  The founder of Atari created Chuck E. Cheese.  Guy Raz gets into why they have a rat as a mascot (the short version is that they had a coyote costume people mistook for a rat) and how the chain was almost called Rick Rat before Bushnell’s marketing team revolted.

Obviously, it worked, but what an incredibly insightful guy to create one incredible business success with cutting edge technology, and then completely rethink the best place to be in the supply/demand of that rapidly evolving ecosystem and then go and create a new market segment so as not to compete with his other customers – and crush it again. Amazing.

So it’s a great story, but it played out 30 years ago, how is it relevant now.  Very.

A couple of big things have happened in the last 30 years:

*Almost everything is a subscription/service where you don’t have to outlay capital to buy things

*Sensors are on increasing numbers of devices (IoT, and AI both) which can report when a person driving a forklift is taking corners too fast (think Crown fork trucks) to when they are going to need their next oil change.

SaaS products have been around for over 20 years now (I started Onyx ASPiN in 1999, a SaaS CRM solution) and most of us are familiar with them.  The more companies can migrate from CapEx to OpEx for anything – they are listening.  So if they now can “subscribe” to expensive equipment like a fleet of fork trucks or Rolls Royce jet engines, and not have to worry about maintenance surprises, that makes a lot of sense and makes customer costs predictable and revenue for the equipment manufacturer, also predictable.  Some companies (Deutsche Post comes to mind – they outsourced IT for a flat monthly fee) will even pay a premium for “no surprises” in their technology costs.

This is really the intersection of what I have called “Do you know what business you are not in?” and managing the P&L.  This encourages people to be clear about what really differentiates them – so they can consider outsourcing other functions to experts – like the people  who make the jet engines or the fork trucks.

This may sound like a simple set of 2+2=4 sort of business decisions, but it’s not because in many cases, with larger organizations, there are different groups, you could call them departments, and you could call them silos, and that’s where this goes from being a two-dimensional math problem, to a three dimensional problem that includes politics and emotion (meaning it doesn’t behave rationally like a math problem).  When a situation spans silos and accountability – seemingly obvious decisions were very messy, until recently.

All of this new sensor data helps tip the scales toward a rational decision.

Instead of someone just saying they think they should outsource the management of their fleet of fork trucks to the manufacturer – it’s just an opinion, but when you can back it up with shifting costs from CapEx to OpEx and lowering overall annualized spend by 12% and shifting liability risk to a third party – it’s an entirely different conversation – and the CFO should have the ability to be the voice of reason on this.

But this article about the current Ford CEO highlights the fact that smart companies are not as worried about whether someone has had a certain title before, or even whether they have worked in their industry (remember Alan Mulally – former CEO of Boeing that became CEO of Ford ?).

This is the era we are in right now.  On a spectrum of Smart, Smarter, Smartest, the Smartest companies are looking less in the rearview mirror and more forward looking about where their industry is going and what matters today, and what will matter tomorrow.  The Ford article is a great example because historically a car was transportation where the most important things were either mileage (Ford Taurus), the number of seats in the vehicle (Ford Transit), or how flashy it looked (Ford Mustang).  Today, the Customer Experience matters to many customers, and that means the technology in the car – from navigation to maintenance warnings and simple pairing with the playlist on a smart mobile device to the comfort of the seat in the car (enter why someone with a background in furniture was selected to be Ford’s CEO.

This is significant because so many organizations and their HR departments look for “obvious” matches for hiring – and not just executive hires.  The trick for most industries – where change is so fast and prevalent where Customer Experience is a key success metric like never before, is to know what to look for – and what to ignore.  In many cases, the top candidates of yesteryear, are the “thanks, but no thanks” candidates of today.  The Smartest companies have figured this out, and that is already a competitive differentiator for them.

The action item for companies that are automating filtration of resumes submitted online for roles, through places like LinkedIn, is to change the way they write job descriptions – and that means taking a look at where things are today and where they are headed and being honest about the kind of person that will help them get to where they need to get.  Jack Calhoun is a very smart executive in Boston who talks about the way companies not paying attention can “drift” away from what differentiates them and what drives their key performance indicators, and one day they essentially wake up to this fact and have no idea how they got so far away from their core and have no real sense of how to course correct,  That’s still true today.

The basic takeaway from this is that if an old fashioned manufacturing company like Ford can make this sort of pivot – so can you – and you had better do it fast because your competition is likely already on this rethink path.  Focusing on Customer Experience and knowing how and when to break down, or cut across traditional organizational/departmental silos are the two biggest things companies need to do right now, and those are at the heart of what separates companies on the Smart, Smarter, Smartest spectrum.