Category Archives: Leadership

Some thoughts on leadership in technical environments.

Persistence or Stubbornness

I’m attributing the motivation for this post to public radio, where I heard this recently:  Persistence is often touted as a key attribute of a successful entrepreneur, and one of the attributes I  have remarkable evidence for possessing.   But maybe I’m just stubborn?

In an article for HBR, Muriel Maignan Wilkins wrote that you can manage your stubbornness by being open to new ideas and being able to admit you are wrong.   The best entrepreneurs I have seen are willing to consider other choices but also balance that with a need to stay on course — changing plans to chase the “next best idea” is not leadership, yet neither is following  a course assured to fail.  Most adults have likely had an experience where they were convinced something wouldn’t work, and then it did.   That’s likely because someone else believed, beyond the obvious reasons why it would fail, that it could work.

In my startup, RideGrid, we believed that people would ride in a car, one time, with an  non-professional driver they don’t know.   People said we were crazy.   You could talk them through the rationale, but safety  and trust were their first concerns.   That was 2007.   Uber has now launched Uber Pool, which has some similar characteristics to RideGrid.   Very few people have that safety fear today:

  • My mother has used Uber.
  • People I work with in Tijuana told me this week that Uber drivers are more trustworthy than taxi drivers — if you left your laptop in a Tijuana Taxi – it’s gone.  If you left it in an Uber car, you might get it back.

Good entrepreneurs analyze evidence and motivation, and can pivot when they believe they are wrong, but don’t shift at intuition before doing some analysis.  Jumping at  the intuition of others is entrepreneurial suicide.  The analysis doesn’t have to be quantitative, but must consider all  relevant variables and their interaction.  The entrepreneur also has to filter out distractions of analyzing too much.

Tolerance of ambiguity, self awareness, and the fearless pursuit of what might end up being a waste of time but you don’t think so….. that’s persistence, and there is nothing stubborn about that.

This post is also the subject of a Leadership Minute Video.



Negotiating – do I care?

There are two fundamental approaches to negotiation, and a very simple decision to make to decide which one to use.  The approach to take depends on whether you care about the other party.

When you don’t care

As an example, this happens in residential real estate during a for-sale-by-owner transaction.   If a broker unknown to the seller presents a buyer, then there is no relationship for the seller to worry about;  there are no future deals or business or relationships to be concerned with.   Assuming the seller doesn’t sell that many properties, his objective is to get as much as he can,   since he has no reputation or relationship to protect.

In this approach,   agree to things only if you think not agreeing will undo the deal, and you have no other choice.  If you have another choice, like a backup offer, then there’s really no point in compromising on anything.   Do the right thing in your mind.   If it doesn’t feel right, the answer is “no”.   If you’re labeled uncooperative, unreasonable or worse – you really don’t care.

You should still determine what the other party’s real needs are, because otherwise you may just push them out of the deal when it wouldn’t have cost you much to meet their needs.

Because you don’t care enough to give anything, you also don’t care whether the other party cares or not.   That’s not the case with the other model.

When you do care

This is the usual state of affairs.   It happens in business because you care about repeat business and collaboration.   In this model you should spend a lot more time listening.   Everyone talks about “win-win” scenarios.   You can’t find them if you don’t try, but if you do try, it will be apparent to the other party and hopefully it will be reciprocated.

Someone told me years ago that most people debate solutions instead of the problem.   This is very true and it is essential to understand when that is occurring in this model of negotiation.  If you can figure out what they really need, and meet their needs without giving up something you really need, you’ve just earned respect and the next deal.

In this model, if you care and the other party also cares, the best path is to share needs and desires openly and hope that you can find something that works.

If the other party doesn’t care, then you should tread carefully and decide how badly you need the deal.

This post is also the subject of a Leadership Minute Video at


This post is also the subject of a “leadership minute” video at

Many of the companies I’ve worked for suffer from a common ailment: lack of focus. It surprises me that businesses manage to survive without it. Yet many do, and because they hadn’t failed yet, they assumed that what they were doing was just fine. One tech giant was proud of their choice of evolution instead of strategic choice. Evolution may lead to a solution if it doesn’t lead to death, but it is not an optimized path (credit to Jason Hoffman, founder of Joyent). Even with focus, many startups fail; without focus, precious resources are wasted leading to higher probability of failure.

One of the guys I worked for once said something like “Imagine how good it could be if we worked on it like it really mattered”. It was his usual way of teasing us to do the right thing, but I think it points to focus. What matters? You can’t work on everything, but if you focus on what matters most, you can accomplish great things. If you don’t think it matters, you don’t focus on it, it gets done poorly or not at all.

The corollary is that if you jump from one shiny object to the next, your team will know that you don’t know what’s important. They probably won’t tell you either. The sad part of being an unfocused leader is that your team is less likely to tell you that you need to change.   Stay the course unless you are confident that the course you are on is inferior to the one you propose.   If you make that shift regularly, your team is going to rightfully assume you’re not a good navigator, and they’ll start to focus on other things that they think are better.

Technical Innovation doesn’t inherently create markets

This post is also the subject of a “leadership minute” video at

The March 2015 Harvard Business Review article “Red Ocean Traps” discussed a number of management mistakes that inhibit strategies that create new markets. Trap three is: “Confusing Technology Innovation with Market-Creating Strategies”, where the authors point out that market creation is not inevitably about technical innovation. They claim that the reason market-creating products win is because they are simple to use, fun and productive. The customers of these products no longer notice the technology, but notice the ‘cool’ new features they get. This was the case with Uber, and Quicken — all technical but not the reason they created new markets. It was not the case with the Segway – technically marvelous but not supported by other transportation systems. It is value innovation, not technical innovation that creates new markets. Organizations missing this point may develop products that are too complex or different.

I have experienced this first hand. Unfortunately the article doesn’t mention how to avoid the trap, or how to get out of the trap once you’re in it.

The European Business Review did a study ( which included a measurement index that revealed that the top 200 companies in the Forbes 500 are losing, on average, 10.2% of their profits due to value-destructive complexity. That’s an aggregate $237B annually.  The article gives a six point “simplicity revolution”, which is practical if the business you are trying to simplify has acknowledged its own complexity. Once you get there, it’s a relatively straightforward change management engagement driven from the top.

The larger challenge in my opinion is when a startup’s leadership doesn’t see that their initial focus is too complex. How do you get the leader to understand? The problem described in “The Innovator’s Dilemma” is that if you focus too much on what customers think they want, you’ll miss the pivots necessary as the environment changes. The converse of that, however, is not true. You cannot ignore the customers’ desires. If you don’t know your customer, and you don’t have a plan to find and engage him, you will almost certainly lose. So although I didn’t find a reference for this, I think the ‘lowly’ Business Plan, with target customers, is an essential tool.

If your CEO doesn’t have one, keep pushing until you get one. You need a defensible business plan with a go-to-market strategy that makes a compelling argument for how your identified customers will discover and want to adopt your cool new idea.

If you have that, you can reduce complexity by asking how it supports the strategy.

Or, you can just noodle around in technical complexity and hope that someday, magic will happen and a market will develop.

Managing Extreme Ambiguity

Every organization must cope with ambiguity and uncertainty.  At a former employer, we used to interview candidates for the skill “tolerance of ambiguity”… because we had plenty of it.   Many management articles discuss ambiguity as something externally given to the organization to deal with.   For example,    Courtney,  Kirkland, and  Viguerie characterize four levels of uncertainty, ranging from “forecasting the future” with some certainty, all the way to situations where the range of outcomes can not be identified.  The term “forecasting” alone indicates that the ambiguity is about some external force or state.

In contrast, at MIT in 1993, Schrader,  Riggs, and Smith argued that uncertainty and ambiguity are different, and that they are chosen by how the problem solver frames the problem.

In the MIT model, they describe the decision process as having  a model to evaluate outcomes.   Uncertainty occurs when the model is understood, but information relating to the variables of the model is not understood.   Ambiguity is where the model is unknown, and in the worst case (level 2) the variables to input to the model are also unknown.   The matrix from their paper is here:


The difference is important because to resolve uncertainty, we just need to go collect some data, then apply it to our model.   To resolve ambiguity, however,  we have to create a model, then get the data.  In the worst case we have to propose the variables to put into the model as well.  Ambiguity is significantly harder.

Some environments will have inherent and extreme ambiguity as a consequence of the leadership and organization in place; according to the MIT model, they have chosen the ambiguity.    My theory is that some organizations bias towards the chaos of ambiguity precisely because it defers decision making.  If you are trying to lead in such an organization without either power or authority (or both), the best you might be able to do is reduce ambiguity by making or forcing decisions that enable models to be formed.  Start with decisions that have relatively well understood consequences and little resistance, and use them as guideposts to build a fence around the problem.   Eventually you should have a smaller number of variables so that a model can be envisioned.