Crossposted on GovLoop

The other day I was having lunch with Rich Dougherty, the CEO of Expert Choice, a collaboration software company in Arlington, VA that is a client of mine. We were discussing the trends towards a more transparent and collaborative federal government. I decided to record it with my iPhone and turn it into an interview.

Here it is:

President Obama came into office promising a more transparent, collaborative and participatory government. We’re one year in. Is it?

There are some bright lights, namely in the area of transparency with data.gov and the CIO dashboard.  There are solid examples of where more information is available that was not available before. In a format that’s attractive, meaningful, and accessible. So I do think that progress has been made.

Are we to the levels that were promised? No. Did we ever really expect to get there? Who knows? You’ve got to set the bar high and reach for it knowing that you’re probably going to fall a bit short. We have to realize that this is a massive organization, and change takes time. It will simply never happen in one year or even one term. These organizations are still civil, with a political management structure. Just like any organization of that size, they don’t change on a dime.

From a collaboration standpoint, there has been more collaboration-style interaction. Has it been dramatic improvement? No. But I think there’s the intent.

Is it spotty? Are there pockets of forward movement or do you see all of the agencies trying to get there?

I’ll break it down this way. For it to actually play out – to meet the goals of transparency and collaboration – several pieces of the puzzle need to come together. There needs to be the will, the desire to be so. There needs to be policy that helps to guide and direct that effort. And there needs to be the means, the technology. What’s lagging right now is the policy.

I think there’s a general intent and good will. Certainly it’s pocketed in that some are more interested in this than others. There’s a general administrative intent – a desire from the Administration to be more open than in the past. Certainly there are some agencies that have little interest in being more open than before, but there’s genuine desire to be more transparent than in the past.

There are technologies that are making it easier, and some of these technologies that have been around for a while. The Web is making this easier. Social media is making this easier. But there still is the need to allow us to better take advantage of the information. It’s one thing to just collect the information, but we need to use it. We’re seeing a positive dialog trend and there are pockets of success, including efforts at the Bureau of Land Management and NASA’s Goddard Space Center to collaborate around major IT portfolio decisions.

Where we’re short is with policy. What should be shared? What shouldn’t be shared? How should it be shared? It’s not clear who should be sharing information. There are multiple shareholders if you will. Who owns that information? How should it be put forth? What are the security concerns associated with it?

With social media for example, it can be a matter of whose account is it? Is it the agency’s Facebook account or a personal Facebook account? There’s technology that’s making this feasible, but there’s a lag in policy to direct the interaction.

On the technology side, it’s one thing just to banter, have conversations and put data up on the Web. It’s another thing to filter through large bodies of information to make sense of the information and to use it. I don’t think we’ve necessarily gotten to the point we want to be on the participatory side of things. We are more participatory in that we’re engaging and creating more conversations, but I don’t know if those conversations are necessarily yielding any more effective government as a result.

A lot of the progress and action has been on making data and information more available, more transparent. But where do we go from there to use this data in reinventing the process of government and how decisions are made, such as procurement decisions? Is this proving elusive?

The government and its processes are just as elusive as they’ve always been. That’s going to take some time to overcome and it’s a tough nut to crack. These are organizations with embedded processes, stated and unstated. The framework or foundation is in place to enable the use of this information, but I haven’t yet seen it yet other than the occasional one-off examples.

I don’t think the will is there to air dirty laundry, but the will is there to be more open and collaborative.

You brought up dirty laundry. How far do we want to go with transparency? Folks like Larry Lessig have pointed out the Perils of Transparency – sometimes it can be a negative. How do you think agencies are approaching these questions?

Agencies are just starting to figure this out. What is appropriate and what isn’t? I do think there’s a dark side to transparency.  I think there’s room to be more transparent than we have been – that’s not necessarily a pejorative statement. There’s more room for many reasons. The technology is there to make it a more efficient process, but if we demanded levels of transparency that required a tremendous amount of manpower to achieve, we’d be more focused on transparency than the job of governing.

We do have to be careful not to lose sight of the goal, which is to do an effective job of governing. Part of that is being transparent, and the technology is there to make this process more efficient. We’ve been involved in helping federal agencies bring together stakeholders and subject experts to prioritize objectives and bring alignment to funding decisions in a transparent way. They save significant time involved in making these decisions and the participation and transparency involved results in buy-in throughout the agency.

Regarding the dark side of transparency where security is clearly a big concern, there are going to be times where we shouldn’t make data available, particularly around national security. Ultimately it makes sense to share it, but when the threat is reduced. That’s the easy one to throw out there.

Another is when the data is wrong. Granted, you can make an argument that it’s useful to get information out there to be able to discover when it’s wrong and deal with it. But you can create a lot of stir and lost time around wrong data. Let’s take an example of data.gov around the spending of a given agency or the performance of a given investment. It’s not impossible to report the wrong information and show the investment is way behind or way ahead of its budget when it very well may not be. But I think that at the end of the day you’re better off exposing it.

There are some things like the old sausage analogy. Congress was going through this with the health care debate on what to televise and what not to televise. Your first reaction may be not televising it is “BS”. But we also realize that to get things done you have to compromise. Deals get done through compromise. But quite often when they’re public, you don’t want to be seen compromising because you appear weak. So when you televise it we’ll just fight all day long and nothing gets done. When we really want to get something done, we’ve got to compromise.

So there’s always got to be a balance. There’s a time to be transparent and a time to not be. There should be periods of transparency. Give it time to evolve.

It could be a difference between real time transparency and eventual transparency.

Yes, that’s right.

Do you see a trade-off among decision-makers between positives, such as a CYA effect that comes from a transparent, collaborative decision-making process and losing control or power they may have had?

I think there is a trade-off between the command and control “I’m going to make the call” and a collaborative approach. If you truly have mandate and you need to make rapid decisive calls, sure, to be in the position to just make the call and less collaborative and participatory you do it, then there are time savings.  The classic analogy goes to the battlefield. There’s no time to deliberate whether you’re going to move these troops here or advance there. It’s life or death. There are times that call for quick and decisive action. So that’s the trade off.

The flipside is that when you do take that approach you lose the opportunity for meaningful input and the outcome could be better informed with different perspectives. There’s a time-value trade-off, but it’s disappearing. The processes and technologies exist to quickly capture inputs around decisions, and we’ve worked with a number of agencies to use them internally to increase collaboration and participation while cutting the time-to-decision. The successes and lessons learned are there for others to take.

There’s always the added benefit of the buy-in. Whether it’s the right decision or not, they’re all behind it and you can enjoy the efficiencies that come with having that alignment around a decision.

Are some agencies in a better position to embrace collaboration and transparency than others? The Department of Defense has been a leader in embracing social media and other tools, which may seem counter-intuitive.

You do see some agencies stepping ahead. I can’t speak for the entire government and offer a report card on which agencies are ahead of others, but you do see DoD ahead of the game in certain respects. They’re certainly not blogging about whether or not we should surge in Afghanistan. But they are getting input in “life” type of issues. They’ve got a huge staff and deal with a wide range of issues, so there are a number of areas where they can benefit from that kind of interaction and dialogue. They have the budget, and they’ve always been a technology-advanced organization. They’ve also been able to effectively leverage technology, so it’s not entirely surprising that they tend to be more comfortable with these engagements and the technology. But they’re selective in how they use it.

What are some of the major challenges that an agency faces in this area? Is it the legacy bureaucracies and processes? Human resistance? Technologies?

I’ll answer it two ways. There is generally, from an Administration standpoint, a willingness to be more open. From a human element, you often find a risk aversion mentality among civilian employees. It’s an impediment if people feel the exposure will bring risk.

A much larger impediment than aversion to risk is the lack of policies around how to do this. Who’s responsible for that data? Who communicates that to the public? When and how? How do we deal with the security issues? Who can speak for the agency? Those are the issues that, to date, have been the biggest impediments. I think they’ll get worked out.

When you talk about participatory, then you’re going to another level. It’s one thing for the federal government to say “this is how we’re spending your money, good or bad.” It’s another thing for the federal government to effectively engage stakeholders and the citizenry in making decisions that guide the government. So we’ve got to collect input, triage it, understand it, find common ground, and use it. That’s going to take some time.

Some of the federal government’s efforts in the area of participation have been “give us your comments and ideas and let the community vote them up or down.” Is this a true effort to involve the public or is it designed to make people feel like they’re involved?

There’s always going to be that element of checking the box, but I do think there’s a genuine interest relative to previous Administration to engage the public. In some ways it’s technology and lifestyle driven. Facebook is new on a macro level. There’s a coolness factor, and how it’s used is changing. That gets applied to how we can approach governing.

There’s two pieces of the puzzle. There’s the government and the citizenry, and let’s lump industry in with the citizenry. The government publishes information and asks for input, but the citizenry has to want to engage. One of the things I’m hearing anecdotally – one client is a CIO and FOIA officer for a Federal agency – is that there’s been a spike in FOIA requests, hundreds of percent increase. Maybe citizens feel that the government is more open to their requests. Maybe they’ll listen, so maybe I’ll ask.

Do you think we’re closer to changing the processes of how decisions are made in government and understanding why they were made?

A little bit but not much. We’re better at sharing information, but that doesn’t say anything about how we made a decision and the data that was used. We’re better at putting a dashboard out and showing investments, risk levels, budget schedules. But that doesn’t inform on how or why the decision was made to fund it in the first place. It may become more apparent on why we kill a program because it’s always been in the red.

It’s one thing to publish data… it’s another thing to act on it. Right now we’re seeing more transparency around the outcomes, the facts and data.

Are you seeing a push to transform the collaboration and decision-making processes?

I think they’re still trying to work out how to get data out there, but that won’t take forever. They haven’t transcended that first step. Whether the will to continue to the next steps will depend on A) if the Administration continues to demand it, and B) if there have been positive benefits from phase one. If we feel we’re better off at governing making data and information more transparent, then I think we’ll be making progress.

There’s a movement in the private sector around encouraging people to fail early and fail often. Is this changing?

You’re hearing from the top that we want people to feel like they can take risks. The message is there, but the question is has the organization caught up? If HR procedures and incentive structures haven’t caught up, nothing’s going to change. If a performance review doesn’t include these incentives and performance structures to include taking risks, the system won’t change. I haven’t been close enough to the OPM performance review process to know if these changes are coming, but that’s what it will take.

What do all these changes mean for government contractors? What opportunities are there? Challenges? Implications for small business contractors?

I think transparency helps contractors because they can become more aware of what’s going on. You can have better conversations with clients and prospects, and put forward better proposals. It certainly levels the playing field by reducing the importance of chummy relationships and insider information.

Decision Science Roles in Medical Decision Making

Medical decisions are difficult for several reasons:

·         They involve multiple objectives, such as alleviating pain and suffering, quality of life, long term health impacts, cost, and so on.  

·         They involve numerous participants:  the patient, doctors, insurance companies, family, employers, and yes, even the government.  

·         More and more data (both good and not so good), is becoming available.  What information is more reliable and what treatments do the more reliable information support?

The question of who makes a medical decision is paramount.  Ideally, for most of us, it would be the patient, and ideally it would be a decision to select that alternative which best satisfies the patients objectives.  (A decreasing minority of people would like nothing to do making with the decision but just leave it up to the doctor).  Determining which alternative is ‘best’ is usually difficult because it requires a synthesis of tradeoffs among conflicting objectives, interpretation of opinions of more than one physician, and an understanding of the complex and often competing data and research results. 

Common practice today consists of a series of medical examinations, tests, and consultations, followed by a haphazard search for additional information.  The patient is often left weighing pros and cons that result from physician recommendations that are: conflicting, biased (naturally so since each understands their specialty best) , and constrained by cost/insurance considerations.  The patient must make a gut feeling choice after sleeping on an overload of information.  Moreover, the decision alternatives may be limited to a set of alternatives that have been pared down because of what some bureaucrat (does it matter if the bureaucrat works at an insurance company or the government?) has decided.

Newer techniques for helping patients decide are evolving.  These typically involve a more systematic way of gather information and presenting it to the patient (see “Weighty Choices, in Patients’ Hands”, Wall Street Journal, Aug 4, 2009 <http://online.wsj.com/article/SB10001424052970203674704574328570637446770.html>.  

However, even if the patient has the latest and best information, the decision is not likely to be one that best meets the patients objectives for at least two reasons.

First, and perhaps at the center of today’s debate on health care, is that patient  alternative choices need to be broadened by reducing restrictions imposed by insurance companies, government, and the ability to pay.  Vested interests are making it difficult to change from what is obviously a poorly functioning system where a patient is rarely even aware of the cost of alternative treatments, and  is sometimes even prevented from choosing  specific alternatives  which are deemed inappropriate by a third party.   Decision science has much too offer in this debate, but has contributed little thus far.

Second, in order for patients to make decisions that best meet their objectives, they must be able to synthesize data and information (much of which is very technical), physician opinions (sometimes from physicians in different fields, each only superciliously knowledgeable about fields outside their own), and most importantly, their own objectives (which are often conflicting).  

Medical decisions, are, by their very nature, subjective.  This is because the relative importance of the patients objectives differ from patient to patient.  But subjective doesn’t mean casual, sloppy, or inconsequential . Subjective simply means that the decision will differ from patient to patient.  There is, in fact, a single best choice for each patient.  Theoretically sound and practical techniques in the decision sciences, such as the Analytic Hierarchy Process,  have been shown to be able to help patients determine the alternative treatment best suited to their individual circumstances and objectives. (A Novel Computer Based Expert Decision-Making Model for Prostate Cancer Disease Management”, Journal of Urology 2005 Dec; 174(6) 2310-2318) http://linkinghub.elsevier.com/retrieve/pii/S0022534705009626.  Not only can such techniques help patients make decisions that best meet their objectives,  reassure patients that they are making the ‘best’ decision for them, are convincing to attending professionals and third parties who may be footing part or all of the bill, but the decisions can actually be less costly to the patient, insurance companies and the government alike.  The use of such techniques is likely to become widespread in the not to distant future.

The Financial Redress

Three score and four years ago our fathers brought forth upon this earthen sphere, a new order conceived in economic liberty, and dedicated to the proposition that all trade is created equal.

Now we are engaged in a great idea war, testing whether trade, or any human interaction so conceived and so dedicated, can long endure. We are met on a great trading floor of that war. We have come to dedicate a portion of our future income, as a resting place for those banks who here gave their shares that financial markets might live. It is altogether fitting and proper that we should do this.

But in a larger sense, we cannot dedicate – we cannot consecrate – we cannot hallow – liberal trade. The brave institutions, past and present, who traded here, have consecrated it, far above our poor power to add or detract. The world will little note, nor long remember what we say here, but it can never forget what they did here. It is for us, the remaining, rather to be dedicated here to the unfinished work which they who fought here have thus far so nobly advanced.

It is rather for us to be here dedicated to the great task remaining before us, that from these failed institutions we take increased devotion to that cause for which they gave the last full measure of devotion; that we here highly resolve that these liberal efforts shall not have died in vain; that this world under God, shall have a new birth of freedom, and that this world order of the people, by the people, and for the people shall not perish from this earth.

Management is a form of herding.  Sometimes shepherding, sometimes cat-herding, but most of the time it’s much more complicated — like guiding a distrusting group of friends, who’ve grown apart, to regain the vaguely shared glory of some imagined past.  Envision herding a group of lions and lambs, foxes and hens, insects and birds to a meadow where the herder is paid based on how many people mistake this motley crew for a circus.

Leadership is different: leaders are to groups what cowbells are to cows — they provide a signal that others can follow.  A successful leader polishes the bell, tunes it to the sound of success, and convinces all it is the purest note ever struck.  But a false leader cannot sustain the true tone for long.  The inherent challenge of leadership is then to stay true in times of trouble, to appear — and to be — an honest broker among competing interests.  There are not many leadership tools available, other than experience, intellect, and integrity.  Not the type of things they stock at your local Home Depot. 

One constant I have observed in great leaders is that they allow — demand really — that each person they interact with become better than that person really thought they could be.   There is complexity in this.  A great leader in times of war — Churchill comes to mind — may not be so great in times of tranquility, and of course the other way around as well. 

So, are great leaders born?  Yes, of course.  They are just not born great leaders. 

When the going get’s tough, the tough have some choices to make.  There are some schools of thought here.  The first is that this is a golden opportunity for most companies to lay off the unproductive bottom 10% of their staff.  A second is to reduce future revenue generating efforts (such as new product development projects).  A third is to ask for an across the board reduction in exempt staff salaries.  A fourth is to reduce bonuses to an absolute minimum (especially since most staff will not quit their jobs with the economy as it is).  A fifth is to shift support staff to sales efforts (hence reducing the non-productive time of sales people).  A sixth is to ask for graduated reductions in pay (those with highest salaries receiving a greater share of the cuts).  A seventh is to slash prices on all items that don’t move, while reducing prices on hot sellers less.  An eight idea I heard was to offer all customers an iPhone with their purchases, since that seems to be the only thing that’s still selling like hot-cakes.

But whatever you choose to do, how will you make the decision?  Alone with a bottle of Jack?  With Jack, and a bottle of Perrier?  Or with Jack and Pierre and Otto and Lakysha and Anil and Sergey and Wang?   Today’s companies operate in 24 time zones (or 24 home offices in one city), have wastly different local customs, regulations, and success levels.  What’s perfect for New York may not work in Tokyo, and what’s right in Berlin can seem foolish in Cape Town.

Here’s an outline of process we are using to help our customers:

Part I – And the problem is…
You have to define the problem before you plan a solution.  Too many companies attempt to make changes to their plans without defining what has changed and how the new plan should address this.

Part II — …we need a process…
You can go without a process… you just won’t be very successful.  Circles are nice for doodling.  But don’t get caught going in circles when times are tough.  Without a process, you are walking with one leg a foot shorter — and will tend to circle the room.

Part III — …that we can buy into…
So you have a process.  Great.  Does anyone buy into it?  If your process is opague and non-inclusive, no one will buy into the results.  Open it up to the relevant people and set expectations for how their input will be used.  Just because people participate, the have to know that companies are not democracies — but why not let them bring good ideas into the mix?

Part IV – … and communicate to the organization
Once the leaders decide on what to do, they have to find a way to have the followers follow.  You have your carrots and your sticks, of course.  But usually there are not a lot of carrots in a recession, so that leaves sticks…  Not a good way to have people follow leadership.  So find new carrots that don’t cost money.  Communicate, provide non-financial benefits, give stock in lieu of cash bonuses.  But whatever you do — just make sure you communicate your sincere intent (unless of course your intent it’s insincere, in which case you are unlikely to be reading this.)

So, that’s the process.  Now get going.

By the way, I make software that helps with this.  www.expertchoice.com.

We’ve created a new site, OlympicDecision, to highlight the current International Olympic Committee process around choosing a host city for the 2016 Summer Olympics. The finalists are Chicago, Tokyo, Rio de Janeiro, and Madrid. We built a collaborative decision exercise for the community to help determine what criteria should matter as well as evaluating each city against the criteria. Check it out!

Tolstoy begins Anna Karenina with a flawless blog-entry:  “Happy families are all alike; every unhappy family is unhappy in its own way.” Admittedly he loses his blogging style a little as he goes on for about 700 pages explaining his point.

But there’s more to this epanalepsis than witless wit.   Could it be that our choices and decisions fall into a similar logical structure?  Put differently, is it true that “All good decisions are alike; each bad decision bad in it’s own way.”

In the most simplistic sense this is true.  All decisions that help us achieve our goals are good in that they achieve their end — decision that fail, fail for any of a number of reasons, with luck and execution often playing a prominent role.  It seems very dissatisfying, however, to qualify decisions based on their outcomes.  We all have made a good decision, one that we felt was the right one, only to never see the wished for result .  This is because for all non-trivial decisions there is some uncertainty about the outcome.

The true question is if we can describe a universal optimal decision making procedure that would apply for all decisions where the outcome is uncertain.  Ironically, the quality of a decisions cannot be measured by the outcome at all.  Since we do not know the outcome at the point we make a decision, it is outside of the scope of the analysis.  What we rely on instead is the much less concrete notion of ‘expected outcome.’  The sad secret is that people are rather poorer judges of what will actually happen, than they think.  In short, we are overconfident about our ability to predict the future.

So, what is the universal decision making procedure?  I’ll leave that answer for a non-blog dissertation, but instead offer some observations.  Before you make a non-trivial decision you need to know some things.  Below are some of the things that I look at — I don’t always look at them in a particular order, and some I may look at more than once:

• * When is the earliest/last moment I can make this decision? 
• * What would be true of the outcome that I desire?
• * What are the factors that are relevant in that outcome and how important are they?
• * When examining alternative solutions, how will I select among them?
• * What information do I not have that is important to have — who could help me get it?
• * What evidence disconfirms where I’m leaning?
• * Can I reverse this decision once made?
• * What assumptions about the future am I making in my deliberations?
• * Should someone else (e.g., boss or a direct report) be making this decision?
• * Does how I make this decision matter in getting the results that I seek (i.e., do I need to involve other’s to get their buy-in, understanding, assistance)?
• * Is there a legal, ethical, or moral dimension to this decision that I should consider?

This may seem like a lot of steps, but for a small decision I can cycle through them in a few minutes, or even seconds.  For an important decision it may take longer.  These questions are never superfluous, however.  If the decision is important, making explicit (even if only to yourself) your choice, instead of keeping entirely intuitive is valuable.  If you need input from others it is critical.  If you are making a decision outside of your experience/expertise it is the only way you can really properly make the decision.

Cooperation and collaboration may rival computers and communications technology as the most improved aspects of business in the past 50 years.   Optimists hope that management by fiat, grunts, and growls will sometime soon be fully replaced by a conscious attempt to arrive at the best solution, regardless of its source.  This, I’m afraid is folly.  Two major problems remain to be solved before we herald in the era of kumbayaesque business practices:

1. The transaction cost of keeping everyone happy, and
2. The elimination of poutology as a career strategy.

Let’s treat them in turn. 

Transaction costs is a technical term from economics.  In it’s simplest form this can be thought of as just what it costs to exchange things in a market place.  More generally, transaction costs can be seen as the direct and indirect costs of obtaining a certain outcome.  So, in a business decision environment we can view transaction costs as the price of paying off the foot-draggers, saboteurs, whiners, and single-focus freaks.   In a highly collaborative environment where consensus and collaboration are valued as an end in themselves (because they are believed to bring about better decision options and execution actions) this cost is not negligible.  Who hasn’t seen a decision delayed, implementation altered, or lowest-common-denominator choices prevail, because someone appeared to object.  This is especially prevalent in hiring decisions, where a single ‘uhmm’ can be seen as the prelude to a veto war. 

Poutological behavior is more pernicious.  While more common among friends and family, pouting is often employed effectively as means to an end in business.   This refers to the act of pouting to gain leverage later.  In a sense, this is a particular type of anchoring bias.  If I pout about a decision today, but then acquiesce ‘because I’m a team-player’ then next time people will, whether they realize it or not, take into account my “magnanimous” gesture.  The net effect is that the pouter has greater leverage coming into the next round of collaborative decision making.   A pouter who is perceived as being invaluable has double leverage since the implicit threat of abrupt departure hangs over the team like Damocles’s sword.

Tomorrows collaboration tools and team training in business school have to do more than just help us collaborate and achieve consensus.  Managing the process of collaborating, disarming the poutologists, and reducing transaction costs are very important to help us avoid the politics of teams, and the dreaded ‘groupthink’ which poorly configured teams often sink to.  Such tools will allow us to prioritise tasks, and maintain a goal-oriented focus, thereby making politically motivated pouting as transparent as a child’s crossed arms and foot-stomping. 

There are three kind of data bigots out there:

1. Those who think their data is precise and torture it to justify any decision they’ve subconsciously already made.
2. Those who think their data is imprecise and then ignore it to justify a decision they’ve subconsciously already made.
3. Those who think Mr. Data should not have been given status as a sentient being, and hence that he was property.

The first two kinds of data bigotry are very common.  They both arise from the same particular psychological bias called “confirmation bias.”  Those of you who have or have been children should be familiar with it:  “You always give him more” is a childish confirmation bias, where the child will take any evidence of advantage to a sibling to be confirmation that the sibling is favored.  Similarly, children will neglect evidence that disconfirms this belief.  Asked if it’s not true that she also got ice cream, the child’s immediate response will be: “Yes, but I behaved better and deserved it” or some similar conclusion.

In business, where we would hope children are not left in charge, we see this same confirmation bias.  An initial hypothesis is supposedly ‘tested’ by systematically collecting and interpreting data to fit it.  I once frequented a little coffee shop that had a great location within walking distance of a major university campus and few competitors.  It should not have been able to fail.  I noticed however that the place kept getting more run down and sloppier as the weeks went by.  Fewer products were on the shelves and not as many people were sitting in there drinking coffee.  It was astounding–I actually saw people turn heel and walk out.  It was an example of a double confirmation bias.  The customers thinking the place was run-down and shabby didn’t trust it to deliver, and the owners seeing customers turn away didn’t want to invest in inventory and upgrades.  Soon it closed, but new owners re-opened a coffee shop and had great success.

The flip-side of using data to test a hypothesis is to deny the availability of data, thus making it impossible to test the hypothesis.  This make it very simple to justify an initial decision.  The example that comes to mind here is strategic decisions where sometimes data is used to justify a decision, but more often than not one or more people will claim no data is available and unguided intuition must be used.  As previous posts here indicate, this is just surrendering to laziness — not a good way to run business.

But why was Commander Data usually referred to as “Mr. Data?”

A company of two has politics in its decision making.  These office politics grow as the number of employees grows.  To examine this, let’s separate between three types of office politics: 1. Those that arise from specialization of functional skills; 2. Those that arise from differences in people’s personalities; 3. Those that arise from internal competition in the company and each employees’ trade-off between corporate and personal success.

We can see the importance of collaboration and establishing priorities as we examine the politics of decision making from these three perspectives. 

First we have the politics that arise from a function-based assessment of how to prioritize a company’s risks and opportunities.  The marketing/financial/operations/sales/etc. perspectives all have value, but they differ in how the evaluate available information, and in the time horizon they consider.  The marketer’s ‘luxury’ of focusing on the future may not be terribly relevant in the mind of a sales manager that needs to meet this quarter’s sales quota.

Then there are personal differences that give rise to politics.  Some people thrive on risk-taking and value a big upside.  Others may think steady-going is the way to go.  Some people like everyone to get along and need consensus building before making decisions.  And then there are the sociopaths and sycophants, the ignorant and the lazy, the smart and the arrogant.  The wallflowers and the wannabes, the we-don’t-do-it-like-that-here old-timers, the know-it-alls, and of course the never-do-wells. 

Lastly there is the simple truth that people change jobs, and that they want to work on things that makes them look good in the eyes of prospective future employers.  Hence, people would rather lead their own cool sexy project with the big budget, than work on someone else’s boring old infrastructure effort.  People’s behavior in order to get their project funded is often the source of office politicking.

Experience tells us that all companies have these dynamics, and that they are the root-cause of negative office politics.  Now it is clearly true that office-politics — especially as a mechanism for fostering healthy competitions of ideas and people — is not all bad.  The true question companies face today is how to harness their diversity of opinion, experience, and attitudes:  that is how to collaborate and prioritize.  Ironically, dispersed workplaces where people have more meetings that are not face-to-face may help here.  When run properly, telephone and online meetings can be very effective as they allow us to focus on the objectives and not the people.  Tools that enable this way of working are emerging–and will provide a way to reduce the negative aspects of office politics, while at the same time enhance the positive aspects.