Cater to Your Personal Pathologies

Managing your time, I’ve found, is mostly a psychological problem rather than a logistical one. Many books lay out a particular system – from the Covey quadrants to David Allen’s 43 folders to a sea of nifty acronyms. What I’ve found from trying them out, and watching others try to use them, is that a system only works if it matches your particular needs. More specifically, if it caters to what I call your pathologies.

We all have some idealized version of ourselves that we aspire to be. This paragon of virtue may never procrastinate, or always rise above temptation .. whatever takes your fancy. Then there is the actual, flawed, imperfect person we actually are. Many people try to use a system that ought to work, rather than one that does work (for them). Hence a sea of unused DayTimer notebooks, mountains of abandoned organizational gear, and endless hopping from one To Do app to another. If cosmetics are “hope in a jar”, then organizational tools are “hope in an app” (or for the traditionalists, “hope in a binder”).

So what do I mean by pathologies? I don’t know what yours are, but I’ll share some of mine.

I Hate Clutter

Some people feel comfortable surrounded by things. They naturally keep papers in piles and leave lots of things lying out on desks. Not me – I like a spare and streamlined work environment. How does this relate to being productive? A friend of mine built an elaborate set of rules for sorting his email. Messages were passed automatically to a lovingly organized cascade of email folders. It worked well for him and was really cool, and I thought I’d give it a try, too. Result: disaster.

All my mail would come in, be sorted into the appropriate category, and I would look at it and be soothed by its orderliness. The problem is that I achieved this calm and pleasing result without actually doing anything. I had to throw away the whole thing and go back to having everything pour into my inbox and annoy me. Then I would be motivated to clean it up, by actually looking at the mail, making decisions, and taking action.

I Like To See My Whole World in One View

When I’m figuring out what to do, I like to see everything that matters all at once. I get stressed out when there are things I need to be thinking about, but they aren’t in front of me so I’m not sure I’m remembering all of them.

I like to plan out my week every Monday morning, and for many years, I have used two facing pages in my notebook to show: the big projects I’m responsible for, any deadlines for the week or in the near future, active to do items, key appointments, top priorities for the week, and top priorities for each day. It is a challenge to capture all that in two pages, but I’ve found it to be a really good exercise – it forces me to think about what’s important and distill it. Each time I have a new kind of role, I have to change those two pages. What I needed to capture when I managed a big team was radically different than when I’m a team of one in a startup and mostly work by myself on a set of projects. I keep those two pages open on my desk most of the time, so I’m always reminded of the most important things that I’m supposed to do that day and that week.

I could keep going for a while (I like to write and draw on paper, I can’t use bound journals because pages can’t be inserted or rearranged, ..), but I’ll spare you, because the important thing for you is to figure out what your pathologies are.

Sleuthing Them Out

A good way to start is to ask yourself:

  • What system has worked well for me? What did I like about it? Why did I like using it?
  • What didn’t work? Did it fail (you kept forgetting to do something important), or was it too much overhead, or did you just stop bothering with it? Why?

Remember, this is not about some idealized vision of yourself, or what works for somebody else – this is all about you. When you answer these questions, especially the second one, try to avoid value judgments – it’s not constructive to beat yourself up with things like “I’m lazy” or “I suck at organization”. Stick to thinking about what you have tried, what worked, and (for the things that have not) why they failed you.

The answers might be psychological (“I like writing things on paper because it is more visceral and I feel more committed to getting it done”) or mundane (“I didn’t carry around the binder because it was heavy and didn’t fit in my bag”). Don’t scorn the details – your whole system can founder if you just don’t like using it. If the color of the notebook bugs you, or you have a fetish for fountain pens, pay attention. If you are using an app, the details of the user experience matter a lot. “This app made me set up all these categories and I just got lost – I need something simple.” Or “I hate looking at the interface – it’s ugly”.

Your “system” might be very informal – maybe you like post-it notes on your monitor. Or piles on your desk organized a certain way. As long as it works for you, that’s what matters. Try to figure out how to eliminate any friction that prevented you from using (or wanting to use) some solution. Try to enhance any quality that you really like.

At the end of the day, the measure that your approach works is that you know what is important and you get it done. Then you have created a magical accelerant for your life.

The Magic Tomato

A new productivity idea has been making the rounds lately, called the “Pomodoro” technique.  I’ve been using it quite a bit at our startup, and it’s been a great help, so I thought I’d share it on the blog.  The name comes from the Italian word for “tomato”, because the inventor (Francesco Cirillo) had a kitchen timer in the shape of a tomato that he used when he was coming up with it.

Pomodoro is really helpful for doing focused work on important projects, especially when they require creative or deep thinking.  It’s so easy to get distracted by easier work or email or interesting discussions with co-workers.

I use Pomodoro for projects that

  • Don’t have clear short-term milestones.  For example, I spent a number of weeks diving into the latest techniques in machine learning and figuring out how to apply them to our product.  This project took hundreds of hours and I just had to chew away at it day after day, working through the algorithms and how we can use them most effectively in our application.
  • Are hard.  In most jobs, there are a myriad of useful and productive things to work on.  A few of them are really important … but the others are often a lot easier.  It takes very little intellectual effort to update the feature spreadsheet, or answer some emails, or do a QA pass over the website – all fine and useful things to do.  But they aren’t the projects that are going to yield huge amounts of value.  Often, a project is “hard” because you don’t know what to do.  You just have to bash away at it until you figure out how to get traction (possibly using some of the ideas from the “crack the nut” post).  Or, it might be hard because you are trying to create something new, and that can be scary.

So How Does It Work?

There is a detailed online guide, which is well worth looking through.  I do find that it can be overly prescriptive about how you are supposed to use the technique, and my approach is somewhat simpler.

Say you have a project that you want to focus on.  The basic idea is that you tackle it in blocks of time, choosing the block size that works for you.  The guides recommend numbers like 25 minutes; I have found that 50 minutes tends to work best for me.  You commit to working for that long without stopping – no answering the phone, no getting up, no checking email, no distractionsYou just work.  If anything comes up that you need to attend to, write it down and get right back to work – don’t do anything else about it.  At the end of the block of time, you stop and get a rest period, where you can deal with things that came up, check email, etc.  The rest period might be 10 or 15 minutes, or whatever works for you.  Check off the Pomodoro when you finish it, and it doesn’t count if you didn’t spend the entire time on your project without stopping.

At the start of the day, I might decide that my goal is to do (let’s say) four 50-minute Pomodoros.  Maybe I’ll spend two of them on machine learning, one designing our user profile system, and one on learning about business metrics for SaaS companies.  I find this approach works really well, because it makes it pretty easy to line up my time against the really important priorities.  The chunks of time are big enough that you can make decisions about them pretty easily.

At the end of the day, I’ll look at how I did.  If I didn’t get very many Pomodoros checked off that day, I know that I wasn’t able to focus on the projects that I wanted to.  I got interrupted, or other things came up.  That’s ok .. the point is not to beat yourself up, but it is important to be honest with yourself about whether you are really moving ahead on the things that matter, and if not, figure out what to do about it.  You’ll also be surprised at how few Pomodoros you can really get done.  In a multi-tasking environment with meetings and so forth, you might get zero significant blocks of utterly focused, undistracted time.  In a startup with virtually no meetings, I’m able to get several 50 minute Pomodoros done on a really amazing day, which is an incredibly good feeling.

Why It Works

One of the things I really like about this technique is that it makes an open-ended project quantifiable.  A multi-week or month project that doesn’t have a lot of interim milestones suddenly has a countable milestone every 50 minutes of work.  You can plan in terms of these chunks of time, you can check them off, and you get a feeling of progress even if there isn’t anything else you can really point to.  I think most people find it much easier to work on a project when there are tangible results along the way – I know that I definitely do!

It also makes it much easier to psyche myself up for a big hard task, because I know that I can stop in 50 minutes – it’s a real comfort to know that no matter how bad things get, I only have to push for that long and then I get to stop.  What almost always happens in practice, of course, is that once I get going, the project sucks me in and I pound happily along, annoyed when I’m “forced” to stop at the end of the work period.  But there is a lot of research that you are most productive if you do sustained bursts of work with breaks in between.  It’s also healthy to get up and stretch regularly.

Another good thing is that it gives you permission/”coerces” you into ignoring potential interruptions.  When you are doing something intense or creative or hard, it’s death to be constantly starting and stopping – you don’t get into that flow that is so magical.   When you are in the midst of a Pomodoro and you know that you won’t get to count it if you let yourself get pulled away, you actively resist interruptions.

Tools

You can do a fine job of using the Pomodoro technique with nothing but a piece of paper and a watch or a kitchen timer.  I do use two pieces of software that I find helpful:

  • My Little Pomodoro – a cute little app for the Mac that will time your Pomodoro interval and chime at the end.  There are several apps like this, or you can also use a kitchen timer, or just your watch/smartphone.
  • Omnifocus – a great productivity tool I’ll write about in another post; the key thing for Pomodoro is that any time I want to note something, I just hit a quick key combination, type in a phrase, and hit return.  The window disappears, and I know the note is squirreled away where I can (and will!) deal with it later.  A lower tech solution is a piece of paper that you scribble a note onto.  Anything works if it is a quick and dependable place to jot down an idea or task, so you can forget about it and get back to your Pomodoro work.

Since I work in an open office, I have a bit of a ritual for starting the Pomodoro.  I put on noise cancelling headphones, start up a special playlist of music (my favorites are choral pieces from the 16th and 17th century), start up the Pomodoro app timer, set the program I’m using to full screen so no other software will be visible … and WORK.

When To Use It

Paul Graham wrote a wonderful essay about the difference between a “maker’s” schedule, and a “manager’s” schedule.  When your time is divided up for you, where things are very structured, and you go from meeting to meeting or activity to activity, you don’t need Pomodoro.  But when you are taking on something open-ended and creative, or you have to think really hard about a problem you don’t know how to solve .. give it a try.  Perhaps you will find that it is as magical for you as it has been for me!

Rise of Data Science

Radically accelerated by the advent of cloud computing and devices, a role has begun to develop that will flourish in the coming years, and I am convinced that it will have a major impact on our lives.

New technologies often usher in new disciplines; they typically begin as a chaotic area of focus, with all sorts of people falling into them from different backgrounds.  Over time, they take on structure, books are written, educational and training programs develop, and they turn into a mature discipline.  That’s what happened when the Web was created – building a web site requires a mix of skills that draw from what had been quite separate worlds of activity: art and visual design, image processing, and programming (among others).

The same arc happened a few decades earlier when programming was invented – it drew from fields like mathematics, engineering, and linguistics.  It attracted people from those fields and many others (including more than a few high school students who were supposed to be doing something else!).

This new field hasn’t been officially named yet, but one of the terms that people are using for it is “data science”.  I’ve been diving into it pretty deeply for our startup, and some remarkably interesting work has been happening over the past several years.

What Does a Data Scientist Do, Anyway?

As you would expect from an emerging discipline, people don’t agree yet on exactly what it is all about.  But the fundamental idea is that enormous bodies of data are being gathered through software, and somebody has to make sense of them.  The analysis can influence decisions that people make (“hey, this version of our web service gets 15% more people to sign up for an account than the other one”) and decisions that software makes (while browsing items on Amazon, the web site will tell you that people who bought this product also were interested in …).

A data scientist is somebody who figures out what data to gather, how to analyze it, and what to do with the results of that analysis.  The discipline combines ideas from areas like statistics, machine learning, mathematics, databases, and psychology.

What’s it good for?  Well, here are just a few ways it is being used today:

  • The magical ability of Google search to find what you need from a couple of words and no other hints.  Compare that experience to what you typically get from software – you usually have to tell applications in painfully explicit detail exactly what you want, in very tightly scripted sequences of commands, and it can be extremely frustrating if the programmers haven’t anticipated what you want.  With Google, you type just about anything into the search box, and with incredibly high probability, it will give you a useful set of answers.
  • The ability to recommend things that are likely to interest you.  Amazon is very, very good at helping you find a book you want on any subject under the sun, through a combination of search and recommendations.  Netflix has gotten to the point where 75% of the shows that people watch on their streaming service come from a recommendation
  • Web sites present users with multiple versions of their product simultaneously, watch how users react, and pick the best one.  Large web companies are running dozens or hundreds of these A/B tests simultaneously and are updating their product daily based on the result.  I used to ship large packaged software products to enterprises, and we would conduct a manual poll of our users years after we shipped to try to figure out whether they used the product and what they did with it – the results were very spotty, very late, and highly inaccurate.  It’s like trying to drive by covering the windows of your car with black paint and having somebody write you an occasional letter about where you are and the condition of the road.

Those are just a few examples – almost every Web-based company depends on data science as its lifeblood to make its product come alive for users and to run its business internally.

The Future

What’s being done today with data science, while impressive, just scratches the surface.  The current economic models have only begun to evolve.  And many parts of our lives remain deeply inefficient and filled with friction:

  • Transit is very wasteful – guessing about traffic patterns, individual drivers maneuvering 3000 pound chunks of metal with dubious competence.
  • Integration of medical carediagnosis, and monitoring our bodies, remains technologically primitive.
  • Energy use is highly inefficient, partly because we have little idea how to optimize or the implications of our decisions.
  • Education hasn’t improved much in the last few hundred years, when President Garfield said that the ideal college was a famous teacher (Mark Hopkins) at one end of a log and a student at the other.  It’s arguably the most important competency of a successful nation in the modern age, and our system (in the United States at least) is hardly flourishing.

Along with much of the economy, these areas are ripe to be transformed, and I am convinced that data scientists will be at the heart of that transformation (for good and for ill!).  If you’d like to learn more:

It’s a discipline that I think anyone involved in technology should understand at some basic level.  Pretty much whatever you do these days, there are probably large quantities of data being generated around it that can be mined for insight.  You want to leverage this power, to make your own decisions and to create a great experience for people using your software.  It’s going to continue to transform the world over the coming years .. and maybe you can become a real-life Hari Seldon.

Eyes of a Stranger

I’m always looking for best practices to adapt and adopt, and I got an idea that I really like from a mentor.  It is a way to combat the complacency that sets in as we settle into any role – that tendency to become accustomed to the way things are, even when they are pretty screwed up.  “Well, of course you stand on one foot and tug on your left ear with your right hand .. that’s just how things are done here.”  With fresh eyes, we might ask “but, umm, isn’t that kind of stupid?”  And, “about the fire burning over there .. maybe throwing some water on it would be good?”

So periodically – maybe once a quarter, or once a year, the idea is to do an exercise I like to call “eyes of a stranger”.  Pretend that you just got your job and are figuring things out – you are in your “first 30 days” and are coming up to speed on the important things you need to focus on.  What is a top priority issue or opportunity that you would see and decide that you absolutely have to pursue?  What inefficiency would you discover that would just bug you until you got it fixed?  What joy-killer is afflicting the team (or you) that needs to get taken care of?

There’s a scene from a book that got stuck in my mind; it’s in Kon Tiki, the really fun story about an anthropologist who gathers a set of kindred spirits to prove that it is possible to sail a raft from the Peruvian coast to the Polynesian islands, using only the technology available in ancient Peru.  At the end of the book, they have crashed on a reef and the raft is smashed, they are pinned down and waves are pounding over them, and one of the people clinging to the remains of the boat says calmly “This won’t do.”  I try to apply that same calm but determined spirit to situations at work that feel desperate.  As you look at your job and the environment around you, what “won’t do” that you’ve gotten used to and have been letting slide?

I’ve found that you probably want to come out of the exercise with a very short list of things you are going to pursue more aggressively than you have been – one is good, three is probably an absolute max.  If you come up with a longer list, revisit it after you do something about the top ones.  I tend to find that you get wildly more bang for the buck by focusing on a couple of things (or one!) rather than dutifully writing down ten “priorities” and feeling overwhelmed so you just go back to ignoring them.

For each of the issues that you’ve picked, you need to figure out what concrete steps you can actually go take to deal with them.  I like to sit down with a piece of paper and do a mind map.  If the issues are worth addressing and you haven’t been doing it, it’s a good bet that you are a bit stuck in figuring out what needs to be done.  Maybe you just need to spend 30 minutes listing next steps or coming up with a plan.  Or, perhaps it will work better to pick somebody you have a good rapport with, and brainstorm about it together.  If it’s a really big issue, you might find it helpful to apply (some of) the framework that I outlined in the series on “Cracking the Nut”.

I’ve done this exercise over a dozen times, and each one has helped me get hard core about tackling something that needed doing and that wasn’t moving forward.  See if it works for you, too!

Cracking the Nut (Part 4) – Wrapping it Up

It’s time to get this decision landed.  What’s Slimy going to do?

Defining the Possible Solutions

Early in our project, we came up with a list of possible options for competing with BigSludge.  By this time, with all the discussion and analysis, we’re ready to update that list.  We’ve refined some of them, maybe some have crumpled under their own weight, maybe we have some new ones.

In our case, here is what came out of our investigations:

  • Direct head to head competition in their core markets looks like a losing strategy.  We went and talked to people on the front lines, we talked to some customers we’d like to convince to use our industrial slime, and we mapped out what kind of return we’d get from additional spending on marketing and sales.  It all looks lousy.  BigSludge is entrenched, they have relationships we can’t disrupt, the market is pretty locked in, and our products aren’t different enough to give us a unique value proposition.
  • We found some intriguing sub-markets where we are doing really well.  We’ve gotten serious traction selling slime for cleaning the grime out of industrial manufacturing machines.  And, you can cover buried power generation plants with it to reduce temperature fluctuation and do weather proofing.  BigSludge has no presence in those markets and our products work much better for these uses, so our specialized slime offerings are growing quickly and have a good head start.
  • The kid market for prank slime looks like a potential winner.  We’ve tested our slime out with kids, our test version is flying off the shelves, and it’s showed up in a couple of edgy TV shows as the Next Big Thing.  Word of mouth is strong.
  • The kid market will take several years to develop.  Based on every precedent we’ve looked at, it just isn’t possible to grow a large new toy market quickly.  No product we looked at that relied on selling through retail channels was able create a new category and grow to a large size in less than five years.

So our updated options are:

  1. Aggressively pursue the specialty commercial markets
  2. Aggressively pursue the kid market
  3. Do a blend of both

The next step is (yes, you saw this coming) to write them down.  We put together a summary for each:

  • Define the option in one page.  Capture the intuition for it, and keeping it short forces us to stick to the essentials.
  • What’s the plan – outline how we’d execute on this idea in very concrete terms.  Milestones, key steps.
  • What you have to believe.  I learned about this approach from a class I took on strategy, and I’ve found that it is a really useful way to capture the key assumptions for a particular option.  You write down the key things that you have to believe in order for the option to be viable/optimal:
Option What you Have to Believe
Pursue specialty commercial markets Slimy can make enough revenue from these markets to sustain our growth needs and can protect our position from BigSludge and other competitors.
Pursue kid market The market is big, viable, and will develop quickly enough to compensate for relatively flat growth in the core business.
Pursue both Slimy Inc is capable of effectively carrying both initiatives forward at the same time (resources, time/focus of management team).  And, the kid market will be slow enough to develop that we need some nearer term revenue.

Evaluating the Options

By the time you have written down the options in more detail, sometimes you will find that the decision basically makes itself.  It is obvious to everyone that one makes the most sense and you are done.  That’s a nice outcome.  But let’s assume we aren’t so lucky; how are we going to decide?

The next thing I do is to assess every option against every one of the criteria we came up with in part 2 (link).  There are two basic ways to go after this – quantitative and qualitative.

Quantitative – if you want, you can create a precise mathematical model to weigh your options.  You can build a spreadsheet with a numerical value for each of the criteria against each option and a weighting factor per criterion.  Then the spreadsheet will happily compute a score for each option, and the highest score ought to be the answer, right?  I’ve done that before, and it has been useful on occasion, but I think it generally gives a false sense of precision to the exercise.  Your tidy spreadsheet full of numbers and formulas can leave you convinced that you are engaged in a scientific analysis.  But you aren’t, really.  At the end of the day, you are making a decision based on (informed) guesses about the future and intuitively chosen priorities.  So I usually don’t bother to build that spreadsheet.

Qualitative – what I generally find more useful is to assign a rough score (maybe 1/2/3 or A/B/C/D/F) to each option for each of the criteria.  Have a justification for each score, so you don’t spend all your time arguing about B’s vs. C’s when people look at the table.  Then eyeball the result and you are in a pretty good position to decide, or to have the debate among the decision makers if it isn’t up to you.  The Slimy, Inc table might look something like this (note that we updated our criteria a bit):

  Specialty commercial Kid market Both
Medium term revenue (3 yrs) A C B
Long term revenue (5-10 yrs) B A B
Risk of revenue projection B D C
Ability to execute A C D

It might seem much too simplistic at first to distill many, many hours of analysis and detail into a little chart with A/B/C/D on it.  But I have found that there is remarkable power in simplicity.  It’s like the old line about writing a shorter letter if you had more time.  Having to summarize a mountain of analysis in a very succinct form forces you to commit.  Complexity is often a security blanket against making a hard call – as long you as you can say “on the one hand, on the other hand”, you can avoid making a decision.  By committing to the values in the table, it gets you in the habit and helps walk you towards the harder ultimate decision that you are trying to make.

And now that you have all the analysis done, and summarized .. get whomever you need in a room, and DECIDE!

Conclusion

I hope that this approach to analyzing issues has given you some tools that you can use the next time you are confronted with a difficult decision.  Use as many or as few of the tools as you need .. in some cases, as in Part I, you might just pick a couple of them.  Other times, when facing a really complex and involved question, you might need to throw the kitchen sink at it.

Remember that no tool or approach will make a tough decision for you – that’s your job.  And a hard decision will stay hard no matter what.  But a framework like this one can let you approach it with what I like to call systematic subjectivity – you make your judgments in a systematic and thoughtful way that helps you wade through unknowns and emotional entrapments.  Good luck!

P.S.  Slimy decided to aggressively pursue the specialty commercial markets.  They will continue to incubate the kid products to see whether they get further traction.

Cracking the Nut (Part 3) – Heart of the Analysis

Carrying forward from part 1 and part 2, we’ve gotten the foundations laid down, so let’s keep powering ahead.

Context

This is the quadrant where we focus on two areas: what we need to know that is knowable and what’s blocking us.

Know What Is Knowable

As we saw in Part 2 (link), there is a big debate within Slimy Inc about the potential size of the kid’s slime market and our ability to generate revenue in the commercial slime market against the dominance of BigSludge.  While these are both predictions about the future and hence cannot be perfectly known, they are subject to analysis.  By bringing some data into the conversation, we can help reduce the uncertainty around the value to assign to these criteria for our various options.

Figuring out the potential kid market is probably the hardest problem.  There is always a lot of risk in any new kind of product, but we can do many kinds of analysis to get insight: look at comparable products that we would be competing with/displacing, consider which channels we could use to go to market and how hard it will be to break into them, look at the historical ramp of comparable products, and so forth.  Beyond analysis, we need to actually get into the market and mix it up in the real world with some customers and partners.  We could sell samples through a handful of selected toy stores, or give some away to kids and get their reactions, or do a limited advertising campaign and see what kind of response we get.  The key thing here is, as Steve Blank says, to get out of the building.  All of these tests will give us some data about how much our target audience will actually want our product, what market size we could aspire to, how to build our sales at what cost, and how quickly we could expect it to grow under best/average/worst case.

The other question should be easier to answer – we probably have a lot of insight into our ability to compete with BigSludge, because we have products in market and have been selling them.  There is always the possibility of some brilliant new stroke that changes the game, but in the absence of that kind of insight, we probably know the channels, the costs, the margins, and the levers that exist in the current business.  So we can estimate with some degree of accuracy how much revenue/margin we can generate doing the kinds of things that are conventionally done.  If somebody has a clever idea for disruption, we should do some analysis/investigation to get a sense of how much to expect from it.

The net of these exercises should be some real data on what we can expect under a variety of different assumptions.  That helps assign a value to each criterion for the proposal under consideration.  Think about each one and ask whether you are ready to assess the proposals against it, or if you need more information to do it as well as possible.

Know What’s Blocking the Decision

Many things can block the ability to make a decision aside from the inherent uncertainty about what to do.  In our case, after thinking it through, we realize that there are three:

  1. This decision is supposedly owned by the VP of marketing, but everyone knows that he doesn’t have the authority to make it stick.
  2. One of the original founders of Slimy Inc., who is very influential, is hell-bent on going into the kid slime market.  He’s going to reject any plan that doesn’t focus on that.
  3. The possibly acquisition of Slimy by BigSludge is really distracting senior management.  They aren’t sure how aggressively they want to go after BigSludge until that’s landed, so they will be reluctant to rock the boat.

Any of these three things could torpedo our whole effort.  There is no point in beavering away and coming up with a great answer, if nobody is going to pay attention or act on it.  So we have to get all three resolved in some fashion, or we need to reconsider if there is any point to the whole project.

Meta

That leads us to the “housekeeping” quadrant – all the scaffolding we need to drive the project.  There are a series of important questions we need to think through:

  • Who are the stakeholders and what is their role?  Who can make the decision and make it stick?  Who needs to be consulted before the decision is landed?  Who can veto it?  Who needs to know after we’ve landed it?
  • What are we delivering?  A deck?  A presentation?  A document?  To whom?  When is it due?
  • Workback/milestones – are there any needed steps along the way?  Maybe an early review where we present progress and get feedback?
  • Key open issues – from our analysis so far, we should have a pretty good idea of the open issues – list them, get them owned and driven and landed.
  • Workstreams – are there any sub-projects that have a life of their own and need to be owned/driven?  Maybe that analysis of the kid market, which might involve finding stores and doing trial sales and evaluating results and doing mini-ad campaigns.
  • Next actions – what specific actions need to happen next?  Who will do them?

That’s the heart of the analysis.  In the next post, we’ll wrap it up and land the decision.

Cracking the Nut (Part 2) – Tackling a Messy Problem

In the last post, we used the model to analyze a constrained problem.  Now, we’ll take on something a lot more open ended.

We work for Slimy Inc, an upstart company in the hotly competitive market for slime.  There is a dominant player in the market – BigSludge – and we are trying to figure out how to compete with them.  The traditional slime market is focused on commercial uses, and we’ve been having a tough time competing with BigSludge because they are the market leader and far larger than we are.  But, we’ve created some innovative new slime for kids to play with – a radical development in the slime market.  We’re definitely going to be first to market, though we have heard that BigSludge has a team investigating toy slime.

There is a raging debate within Slimy, Inc about how to compete with BigSludge.   Some people want to continue going after them head-on in the large commercial market, relying on our superior products.  Others want to put all the company’s efforts into the new kid slime product line (but is there really a big enough market, and will it develop soon enough?).  Another faction is pushing for an acquisition – BigSludge knows about the cool new products we’ve come up with, and they’ve had a couple of discussions with our leadership team about it.  As usual, there are dozens of variations of these basic ideas, and they’ve gotten tangled up with each other.  Emotions are running high and discussions have been going around in a circle.

We’ve been asked to take on this problem, analyze it, and get the decision landed.  The stakes are high – the decision will probably determine the future of the company and perhaps its very survival.  So, it’s time to get methodical.

Defining the Problem

We start here, as always.  The problem may seem obvious, but often the various stakeholders in the conversation have quite different notions.  So we’ll start with a statement of the problem, and it’s incredibly important that we write it down.  There is a great quote by Leslie Lamport, a well known computer scientist: “we write things down in order to realize how poorly we understand them.”  In our case, we land on this: “what strategy should Slimy use to compete with BigSludge?

Looking at the other tools in the quadrant, there are a couple that will be helpful.

Scope – what is in and out of scope for our problem solving effort?  In this case, let’s put the decision to pursue acquisition out of scope – that’s an interesting analysis, but it’s pretty separate from figuring out how to compete.  Our project may provide good insight, though: if we can’t come up with any compelling way to compete, then we may have a lot more enthusiasm about acquisition.  But we’ll confine our scope to competing with BigSludge.  We also have to make sure we get the key people to agree on our proposed scope!

Assumptions, Axioms, and Principles – I think of these as the foundation of the analysis, and they are incredibly useful to work through and write down.  They are related notions, but I try thinking about all of them to see which are most relevant to the problem at hand.

  • Assumptions – something you believe to be true, but you are aware that you might be wrong.  “There is a large potential market for toy slime that BigSludge will not be able to address for at least three years”.  Once you’ve identified your assumptions, you can decide how risky they are, how much your potential wrongness could hurt you, and hence how much you need to validate them.
  • Axiom – “a self-evident truth that requires no proof” – you simply accept an axiom without debate or validation.  In our case, an axiom might be “commercial slime is an essential need for current customers and nothing will replace it in the market during the next ten years.”  Your axioms can save you a lot of time, since you don’t need to bother analyzing them.  But, they are obviously dangerous, because if you are wrong about them, you can choose a really bad path.  DEC had an axiom that PCs weren’t a threat because they were too small to do “real computing” – and DEC paid dearly for that axiom by going out of business and being acquired in a fire sale by one of those scorned PC makers.  So one of my main reasons to poke on axioms is that groups generally have a set of them that are accepted unconsciously and unquestioningly.  It is worth teasing them out and stating them explicitly to make sure that they really should be axioms, and are not just questionable assumptions masquerading as revealed truth.
  • Principles – a core belief that you are going to follow.  Ex: “we will produce no toxic by-products in our manufacturing processes” or “we will tell every customer the turnaround for any order within 2 days of accuracy.”  Principles help you be clear about what you believe in, and they guide you in terms of what solutions you are willing and able to consider.

Goals and Defining Success – often when people are disagreeing about a course of action, it is because they don’t agree on what “success” means.  Are we trying to achieve a good ROI on our product development investments? Establish ourselves as the share leader in a new market?  Win share from BigSludge in the current market?  Grow revenue or profit by a certain amount?  Survive as a company?

I have found it best for the goal of a project like this to be succinct and measurable.  I also prefer if the goal

  • Doesn’t pre-suppose a particular strategy.  In our case, if we define the goal to be “create a large new market for slime”, then it heavily influences the approaches we can use to get there.
  • Is defined positively, not negatively.  I much prefer “radically increase our revenue and profitability” vs. “take share from our competitor”.  The negative approach can lock you into a zero-sum mentality, rather than creatively looking for any way to achieve your true goal.  Presumably what you really want is to make massive amounts of revenue and profit, regardless of what your competition does.

For our purposes, we will use this: “a successful strategy will yield a set of quickly growing product lines in the market that have higher profitability than anything we currently sell.”

Constraints – we are always under many constraints and we need to understand how they limit our options.  They might involve resources (money or people), legal requirements, etc.

Solution criteria – just like we did in the last post, we will need to come up with a ranked set of criteria for evaluating our options.  This is often the hardest part of defining the problem; fierce disagreements are often disguised arguments about the criteria.  For example, we have one group that wants to tackle BigSludge head on in their core market, which is large and well established.  Another wants to dedicate the company’s resources to expanding into the new kid slime market.  What’s going on?

The real challenge is that there are competing (and valid) criteria to judge potential strategies.  In this case, they are:

  • Size of the target market – one group questions whether the kid market is real and large.  There is no question that the current market is large.
  • Growth of the target market – the current market is mature and is growing with GDP.  We don’t know of anything on the horizon that will change its trajectory (per our axiom above).  The future of the kid market is much harder to predict; if the company can really nail an offering, it could be a huge and high growth market.  Or, it could stay tiny because only the early kid adopters will ever bother playing with slime.
  • Riskiness of our market prediction – obviously one is not risky in terms of its existing, the other is high risk.  Also, BigSludge has that research group that might get a clue and develop a competing offering in the kid market – it’s unclear how long we can have it to ourselves.
  • Ability to capture target market – to get the traditional market, you have to find a way to compete with BigSludge and take share or expand the market somehow.  The company probably has a pretty good sense of how hard this will be and has some ability to execute on it, but it may be very difficult to succeed.  To create a whole new market, even if the demand is there, calls for specialized skills and new partner relationships and the like.  Does Slimy have what it takes to pull this off?

The disagreement between the two groups is a disagreement about the value to assign to each criteria and the relative priority of the criteria.  This is really key to understand.  Until you start digging at the real basis of the disagreement, you will often go around in circles and everybody will just get locked more deeply into their point of view.

The faction that wants to go after the traditional market believes that (a) the opportunity in the kid market is small and will stay small, (b) betting on that market is much too risky and will take a lot of energy to pursue, and (c) Slimy doesn’t have what it takes to create new markets.  The other group believes that (a) the kid market has huge potential, that (b) it will grow quickly, (c) Slimy is in a good position to take a risk for huge upside, and (d) the company can learn how to sell to a new audience.  They also (e) doubt whether Slimy can compete effectively with BigSludge in their core market.  So the two groups differ on:

  • The value to assign to a criteria: is the kid market going to be large and high growth or small?   Can Slimy really make headway in the traditional market?  These questions can’t be answered perfectly, of course, since you are predicting a future outcome.  But you can certainly get data to support the analysis.
  • The relative priority of the criteria.  One group is risk-averse, the other isn’t.  This is a useful debate – how much risk is the company willing to take on?  What kinds of risk?

The key thing you can do with an analysis like this is move the debate from an unproductive place – “We should go after the kid market!” “That’s crazy, we should go after the money, and that’s in the commercial market!” – to a much more useful discussion around the real issues – can we get facts to assign values to the criteria more confidently, and how should we prioritize competing values?  These are still very hard questions, and they still require us to make decisions in the face of uncertainty.  But they let us focus our energies on reducing the key points of uncertainty and on having debates that we can actually settle.

We’ve now got the foundation in place for our problem solving effort – we know the problem to solve and its scope, we know what our goal is, we have articulated our principles and assumptions, and we know how we’re going to evaluate possible courses of action.  Next, we’ll move on to other quadrants of the model.

What Should Managers Do All Day Long?

What managers spend their time on is often the source of (frequently cynical) commentary by the people who work for them.  I have found that it is also a source of anxiety for a lot of managers.  They often aren’t quite sure what they should be doing to add the most value.  It becomes even tougher, I’ve found, as you get more senior and have larger organizations to worry about.  You become very detached from the real work that is going on and what you do seems pretty distantly related to anything concrete.

Let’s take an example.  When I was the general manager of a pretty large team (400 people), I had a clear idea what the team needed to do – deliver a high quality next release of the product and grow the business 20% this year.  Great, but since I’m not writing any code or carrying a quota, how do I contribute to those goals?  What do I prioritize Monday afternoon at 3pm to help the team hit its goals?

To keep my sanity, I needed something that was my north star.  I created a document which I called “My Job”, and I reviewed it at least once a week.  It has the activities that I did, not the goals of the team.  For example, the first one is “Inspire” – I want to inspire the people on the team with a vision of where we are headed and why it is important and convince them that it is within reach.  Another is “Drive Rhythms” – for a team at scale, you have to have efficient rhythms to review the state of the business, check in with the engineering team each milestone, manage budgets, etc.

I scheduled an hour every Monday morning to plan the week, and one of the most important things I did was to take the “My Job” page and walk through these four steps:

1.  What’s F-ed up?

For each activity, I asked myself the question, “what’s f-ed up?”  And if I felt ambitious, “how can I move this forward proactively?”  This was an opportunity to dump all the hopes and anxieties buzzing around in my head down on paper.  The key thing was not to hold back – I wanted to get it all out.  And I wanted to make myself think about each activity in case it needed more attention than I was giving it.

2.  What can be done about it?

Next, I went back through the list to figure out what could be done about everything I had written down.  I needed to be in a very different state of mind – to go from a free-flowing brainstorm to focusing on concrete steps I could take.  I’ve found that it can be hard to switch back and forth quickly – once I’m being detailed and practical, the ideas don’t flow as freely.  So that’s why I do the whole second column first, then go back and do the third.  The things in the third column are very straight-forward and doable (“next actions” in Getting Things Done lingo).  These are specific actions I can do right away.

3.  Should I be the one doing it?

One easy trap to fall into (I am highly prone to this) when you are a manager is to over-function .. to jump in and do work that properly ought to be done by the people who work for you.  It’s like the over-protective parent who does everything for their kids, so they never learn how to do things for themselves.  It’s very annoying for the direct report who wants to solve their own problems.  So before I start firing off emails and diving into all those actions, I look them over to make sure that I’m the right person to do them.

4. Am I doing the really important “only I” things?

One of my favorite questions on this front comes from Peter Drucker, who was one of the people who basically invented management theory.  He wrote many useful books (try “The Essential Drucker” if you are interested – it’s a good survey of his ideas across a variety of topics).   And he challenges managers to ask themselves a very important question: “What can I, and only I, do, that, if done well, would have the most impact on the organization?”  This is a great question to ask yourself.  I suspect that every action item you identified is a useful thing to do, and will be of some value for the team.  So the question shouldn’t be “what adds value?”  Most or all of them will, hopefully, if you have a clue.  The question is, “what adds the most value that nobody else can do?”  Make sure you do those, before you fritter away all your time doing random things that aren’t going to have as much impact or that somebody else can do equally well.

Once I’ve gone through this exercise, I really feel like I have a handle on what I am worried about, what I should be worried about, what I could do about it, and what I will do.  This exercise translates high-level goals like “grow the business” into “set up a meeting with Mary to adjust quotas” and turns “ship a high quality release” into “review the latest benchmark numbers on the performance issues with the new version of the database.”   And it (helped) keep me out of the way of the team when they didn’t need me.

Do you have a north star that tells you what your job is?  What tools help you figure it out?