"I'm very impressed with the level of professionalism of this network. I registered my request over three months now, and the response has been overwhelming; beyond my expectations. Although I have not closed any deals as yet, I'm still very hopeful. Keep up the good work!"
Posted on March 21, 2017 @ 09:41:00 AM by Paul Meagher
I recently came into contact with the phrase Profit Resilience from reading Zach Loeks new book The Permaculture Market Garden: A VISUAL Guide to a Profitable Whole-systems FARM BUSINESS (2017). In the farming industry there is the problem that profits often don't come in steadily throughout the year and this can obviously be challenging for the farm business. To maintain income the farmer may have to take out loans to cover costs until the next production and sales period happens. Or, the farmer might create another line-of-business designed to generate income during these slow seasons so that a constant level of profits is achieved throughout the year. The latter option gets you closer to profit resilience.
Farmers can achieve more profit resilience if they don't rely upon one line-of-business to sustain them all through the year. Profit resilience is
achieved by introducing specific amounts and specific types of diversity into their income stream. I say specific because too much or too little
diversity can be detrimental. If we try to manage too many diverse types of business, then the complexity of managing it all can outweight
the marginal benefit of adding a new line-of-business. One solution might be to make the businesses less diverse so that similar skills can be used to manage each line-of-business (e.g., CSA, specialty crop, Garlic seeds). Unfortunately, the lack of industry diversity means that income may all track the same seasonal pattern we are trying to avoid. To achieve greater profit resilience the diversity of the lines-of-business have to be greater (similar to portfolio investing).
Profit resilience depends upon having the proper amount and types of businesses in your enterprise portfolio. The proper amount is 3 lines-of-business and the proper types are lines-of business whose profits are not correlated in time. Why 3 lines-of-business? This is just to give you a feasible number of businesses to consider in your planning. Ultimately, the number should be chosen based upon looking at all the small enterprises out there that are demonstrating profit resilience and tallying the number of lines-of-business they are engaged in. Ideally we would also examine small enterprises that failed and examine the number of lines of business they were engaged in. If 3 lines-of-business was identified as ideal then this could be a normative suggestion. Why do the lines-of-business we select have to be uncorrelated? This is ultimately an empirical question but, in the case of farming, it is clear that there can be problems with seasonality of income and if you select all your lines-of-business without ensuring the profits from them are uncorrelated or anti-correlated then you may not achieve profit resilience. The Portfolio Theory of investing might also be used to justify the need for a higher level of diversity among the businesses you invest in. The portfolio theory is arguably about achieving profit resilience, and not just profits.
Is the goal of your business to be profitable or to have profit resilience? You can be profitable without having profit resilience. It happens in lots
of businesses. The automotive shop I frequented went under in early February because they hit a low revenue part of their season and were carrying too many overhead expenses (they moved to a nicer shop with higher rents and more staff). Perhaps having more than 1 line-of-business would have helped but maintaining profit levels is made more difficult when you have higher expenses and encounter rough patches.
Everyone has to be concerned about profit resilience even if you are a senior on a fixed income. When you move from the daily grind into retirement it would be nice if you could achieve some profit resilience in the transition. Your income may be lower but if you also lower your expenses significantly you might be able to achieve some profit resilience during this transition. Likewise, if a business is going through a patch of low sales, then cutting out some expenses might help to achieve some profit resilience (difference between revenues and expenses remains relatively constant). You may also voluntarily decide to restructure your business to have lower income but also lower costs. If profit resilience is your goal rather than simply increasing gross revenue then this makes sense to do.
Profit resilience is a temporal concept in the sense that our time to rebound back to a previous level of profitability is measured by some time interval. If your income nosedives and you rebound back to your previous profit level a year later, is that still an example of profit resilience? Probably not. In the business world we tend to measure things in business quarters and that is probably as good an interval as any to use for measuring profit resilience, although monthly accounting is also a very popular accounting time frame.
Profit resilience can be achieved if we plant things today (e.g., apple trees) that might bear fruit in the future. We can't invest too heavily in
the future, however, if we want to retain profit resilience because the future is not generating revenue today. When selecting another line-of-business to add to the enterprises we should have a significant bias towards adding lines-of-business that will generate profits in the near term. One useful example comes from Mark Shepard who purchased more nut tree seedlings that he needed and used the proceeds from selling the extra seedlings to cover his purchase cost and then some. Even though something is being done for the long term it is nice when you can obtain a yield from it in the short term as well.
The term Resilience is popular these days so when I heard the phrase Profit Resilience I thought it was worth spending some time reflecting on various aspects of that phrase might mean. The last observation that I want make about the term Resilience is that it has been contrasted with two other terms - Fragile and Antifragile - by Nicholas Taleb in his important book Antifragile: Things That Gain from Disorder (2012). Profit resilience might be contrasted with profit fragility and profit antifragility, the latter being another concept worth exploring in a future blog.
Posted on March 16, 2017 @ 07:53:00 AM by Paul Meagher
In the lean startup literature there is alot of talk about validating the startup vision through Minimal Viable Products (MVP) and customer feedback. In today's blog I want to examine the phrase "startup vision" and why we use might choose to use this phrase.
I would argue that one good reason why we use the term "vision" is because a good startup vision can be visualized, as in represented graphically for others to inspect, share, and discuss. If it cannot be visualized, then another term should probably be used - the startup idea, the startup concept, the startup proposition, for example. This would make usage of the phrase "startup vision" more precise.
A large part of the human brain is dedicated to processing visual information. It is a highly evolved system for navigating and interacting with the world. It is arguably our most important sense. There is also lots of evidence that when we imagine things we engage many of the same brain areas that are used to process visual information. The hypothesis of shared brain areas helps to explain why we have the ability to vividly imagine and visualize things that don't exist in front of our eyes. It can also be used to explain why imagination is a powerful ability - it taps into our highly evolved visual thinking ability.
A virtuous loop can happen when we visualize the startup vision. Being able to see the vision expressed on paper or on screen can get our visual systems engaged in further problem solving and add more detail and specificity to the vision. Our ability to hold ideas in working memory is limited but our ability to visually process many items at a time is much greater. When our working memory cuts out our visual system can cut in and help us with longer chains of reasoning.
If I asked you to tell me what is involved in selling carrots to customers you might imagine someone planting a carrot seed, growing it, harvesting, washing it, and selling it to a customer. If we visualize the full cycle, however, we might stand a better chance of seeing that there are many additional steps involved that our conceptual appreciation omitted. Zach Loeks, in his new book The Permaculture Market Garden: A Visual Guilde to a Profitable Whole-systems Farm Business (2017), created this visualization of the carrot selling process:
Zach's book contains many such visualizations to help readers understand a host of ideas and processes. This particular visualization helps us to appreciate all the steps involved in the carrot sales process and allows us to think in detail about each step in the production process and, perhaps, how we might optimize or improve them. What I also like is that the visualization doesn't require excellent drawing skills to express the steps involved. This sketch looks like something many of us could create with some colored pencils.
Another aspect of Zach's book that is interesting is the use of color in all his visualizations. Often when we think of the startups vision we don't think of it as involving color, but why not? Bill Mollison, in his magnum opus, the Permaculture Designers Manual (1988), also had abundant visualizations but they were all grayscale line drawings. It is hard to make certain distinctions "pop" when you don't use color to code the differences you want to draw attention to. Color also contributes aesthetics to your vision which can also be important.
The purpose of this blog is to draw your attention to the odd use the use of the term "vision" in the phrase "startup vision". Often when discussing the "startup vision" words alone are used to describe what the startup wants to accomplish, however, that does not explain why the term "vision" is used ("startup intention" might be better). When the startup vision is strong, the founder can see what the future should look like as if it is already in front of them and can also visualize it with diagrams, figures and line drawings, ideally with some color included as well. Perhaps we should reserve the term startup vision for cases in which actual visualizations accompany the startups intent to shape the future.
Posted on March 9, 2017 @ 08:37:00 AM by Paul Meagher
A stopping rule is used to determine when one should stop searching for things like a spouse, parking spaces, investment deals, a new home, a new secretary, etc.... The "look then leap" stopping rule suggest that we should just look for awhile so that we increase the likelihood of encountering the optimal spouse, the optimal parking spot, the optimal investment deal, the optimal house, the optimal secretary, etc... The question is how long we
should keep looking before deciding to leap?
A considerable amount of research has been done to find an optimal strategy for determining when we should stop looking. It turns out that
we should stop looking at secretary applicants after we have interviewed 37% percent of them. After that we should jump at the next secretary
that is better than the previous secretaries we interviewed. If we are looking for a marriage partner, then we should figure out how long
we are prepared to look for that partner and once we have used up 37% of that time, we should consider proposing to the next marriage
partner that we regard as better than the ones we have been with to date. The 37% rule applies to either the number of items to be
searched or the amount of time we have to search.
If you use this optimal strategy then 37% of the time you will pick the optimal item you are looking for. There is no optimal stopping
rule that gives you certainty that you will pick the optimal item. The best investment deal may have been in the 37% of deals you
reviewed to date and didn't make an offer on or perhaps if you waited until you reviewed 60% of the deals you would have found the
optimal deal. If you set your optimal stopping rule at some number other than 37%, however, your chance of finding the optimal item will be
less than 37%. That is all that optimal means in this context.
This form of the optimal stopping rule makes alot of assumptions so whether it is applicable or not depends on your particular situation.
For example, if you are allowed to go back and pick the best secretary of the 37% you have interviewed, or if the secretary is allowed to
refuse your offer, then the math behind the stopping rule changes and we would have a different optimal strategy for that situation.
The "look then leap" stopping rule also assumes that we are ranking items relative to each other (ordinal scale) rather than relative to
some absolute scale (cardinal ranking). If we have some absolute criteria we can use to evaluate candidates then we can pick a
candidate if they exceed some threshold we have set for selecting them. Using a "threshold rule" to determine when to stop is another
stopping rule stategy we can use.
A "threshold rule" allows us to potentially finish our search faster than using the "look then leap" strategy. Instead of looking for who
you might "love" the most by comparing each to the last, you instead set some criteria that your potential marriage partner must meet and
as soon as the person meets those criteria you propose.
Stopping rules are important to determining when we should walk away from an investment. Those who lost everything during the 1929 Wall
Street crash did not stop in time. Gerald Loeb pulled out before the crash and credited his stopping rule for his success in doing so:
"If an investment loses 10 percent of its initial value, sell it".
There is also a rule when climbing Mount Everest that if you are not on the top by 2 o'clock then you should turn around. It does not end
well for those who ignore this rule.
In my next blog on The Lean Startup book, I'll be dealing with the chapter titled Pivot and we'll see that this is very much concerned with knowing when to stop in your present course and when to persevere.
Posted on March 6, 2017 @ 03:32:00 AM by Paul Meagher
I recently became aware of farmer Richard Perkins. He is an innovative farmer that runs Ridgedale Permaculture in Sweden,
at a location that offers six months of winter and six frost-free months. He recently published a book called Making
Small Farms Work that has received very positive reviews.
It is impressive how quickly Richard and his wife have converted a 25 acre farm into a productive, profitable and sustainable farm (took over the farm on Mar, 2014). He calls farming a "land-based business" and he is offering permaculturists a vision of how to productively and profitably occupy larger amounts of land ("small farm" acerages). Richard appears to be publishing videos more frequently on his YouTube channel where he shares his ideas.
His video introducing people to Ridgedale Permaculture is a good place to start to learn their systems:
I became aware of Richard when I checked out Permaculture News and came across the video below. Those with little interest in farming might nevertheless learn something that might apply to their situation as well.
Posted on March 2, 2017 @ 06:44:00 AM by Paul Meagher
In my last lean startup blog on measurement, I talked about using a Minimal Viable Product (MVP) to test hypothesis derived from leap of faith assumptions
contained in the startup vision.
In the case of Joe's lemonade stand (see previous blog), the first leap of faith was that the customer would buy the lemonade. Customers purchased the lemonade but not in the amounts he was looking for (10 customers). Joe then tested the price people would pay for it starting off at a premium price of $1.50 a glass. He measured sales volume at that price and another price ($1.00 a cup) and concluded that it was better to sell at the lower price because the volume more than compensated for the lower price. Joe is making progress towards operating a successful lemonade stand.
In this blog I want to look at the process of hypothesis testing in more detail and see how it maps onto some of the terms we have been using.
Let H be a class of hypothesis and h be a specific hypothesis.
Let M be a class of measurement outcomes and m be a specific measurement outcome.
We can use Modus Ponens (latin for "the affirming mode") to draw conclusions about whether our hypothesis is true:
If H=h Then M=m
We can also use Modus Tollens (latin for "the denying mode") to draw conclusions about whether our hypothesis is true:
If H=h Then M=m
So far we are in the realm of formal logic and these two forms of inference are foundational in guiding automated forms of inference.
We can cross over into the realm of informal logic by using the P( ) operator around all our assertions, where P stands for "the probability of".
So Modus Ponens now looks like this:
P(If H=h Then M=m)
And Modus Tollens now looks like this:
P(If H=h Then M=m)
It is this form of Modus Ponens and Modus Tollens that we are dealing with when we test our startup assumptions. The application of scientific
methods to startup hypothesis does not necessarily yield clear cut answers, but answers where one hypothesis might seem be better supported
by the evidence than another hypothesis, without being able to completely rule out an alternative hypothesis.
In the case of the learning platform company Grockit (see previous blog), they were adding new peer-learning features to their learning platform and not seeing any effects on their metrics. They concluded that the learner only wanted peer-learning up to a point, then the learner wanted to engage in solo mode learning. A logical possibility was also that Grockit didn't zone in on the proper peer-learning approach yet. The alternative hypothesis is not completely ruled out by testing and measurement, but made sufficiently implausible that a pivot was deemed necessary.
We will be getting into the topic of pivoting in the next blog, but it is important to note here that deciding when to pivot or not is made difficult by
the fact that the original and alternative hypothesis may each have merit making it difficult to decide what to do.
Recognizing that probabilities are involved can be helpful in deciding what decision making framework you want to use in your startup hypothesis testing. If P(H=h) is .6 perhaps that is enough certainty to go by in situations of irreducible uncertainty (you don't have the time or resources to achieve greater certainty).
You could examine formula-laden articles on sequential A/B testing and bayesian A/B testing to try to figure out when to stop collecting data and what to conclude (which I recommend reading), but I'm also interested in a more practical approach based on using informal logic to evaluate the probability of the premises P and the probability of the inference (i.e., P(if P Then C)) to arrive at a probability of the conclusion C of an argument.
P(If P Then C)
The evaluation of the premises and the inferences is based upon informal logic techniques appropriate to criticizing scientific arguments, combined with common sense, to assign probabilities to each premise. The evaluation of the premises and the inferences of the argument determines the evaluation you assign to the conclusion. Bayesian forms of informal logic may also involve assigning a prior probability to the conclusion so that the posterior probability of the conclusion can be evaluated.
P(If P Then C)
Whether these probabilities are to be combined additively or multiplicatively to yield the posterior conclusion is worth thinking about, although multiplicative combination tends to used more often and to work better. Informal logic nowadays often involves creating a graphical representation of the argument. Below is how we might graphically express this Bayesian approach to evaluating arguments (where hypothesis testing is just one type of argument). The premises (e.g., the measurements and other assumptions) appear at the top with lines connecting them to the conclusion. The lines are your inferences (if P1 then C, if P2 then C). The prior probability of the conclusion C (based on previous knowledge) appears next to the premises as a separate contribution to the posterior conclusion probability C. The posterior probability of the conclusion at the bottom is what you get when you combine your prior probability of C and a likelihood estimate (the left side of the argument below).
The purpose of this blog was to dig a bit deeper into what startup hypothesis testing might involve from an formal and informal logic perspective. I am not a practicing logician and this is not a peer reviewed discussion so you may or may not find this a useful framework to use when approaching the problem of testing the leaps of faith that your startup vision implies.
Inspiration for this blog and the argument evaluation diagramming comes form my undergraduate mentor Wayne Grennan and his book Informal Logic (1997).
Ian Flemming in his excellent book Lean Logic (2016) has this to say about the relationship between informal and formal logic.
It sounds banal, but the syllogisms of formal logic are the building blocks of reasoning, which - in combination with a series of conditions, affirmed or denied in sequence and in parallel - can develop into a problem-solving capacity of great complexity, used as the logical structure on which artificial intelligence is based.
Informal logic is, of course, the junior partner in all this, since it depends on the reasoning of formal logic, and its mixing up of logic and content is exactly what you cannot do with formal logic. On the other hand, without content, logic has no purpose. Formal logic is the road, informal logic is the journey.
~ p. 165
Posted on February 27, 2017 @ 05:22:00 AM by Paul Meagher
A lean startup uses innovation accounting to properly measure the effect of design changes on customers. A startup can fail if it is
measuring the wrong things. The chapter "Measure" is about strategies we can use to make sure we are measuring the right things.
We discussed the concept of a Minimum Viable Product (MVP) in the last blog ("Test") of
this blog series on Eric Reis seminal book The Lean Startup (2011). One property of an
MVP that I didn't discuss was the use of an MVP to gather initial baseline measurements of the Key Performance Indicators (KPI). When designing your MVP, keep in mind that one important role that it can serve is to kick off the process of measuring baselines for
key performance indicators like the number of registrations, number of downloads, number of customer logins, number of payments,
and so on (sales funnel behaviors). Once you gather this baseline data for your key performance indicators, then you can verify whether any future design changes you make actually have a significant effect on the levels of these key performance indicators.
The term Innovation Accounting refers to the repetitive 3 step process of gathering baseline measurements, making a design change intended to improve KPIs, and then using these measurements to help you decide whether to pivot or persevere in your present course. The more times you can successfully complete this cycle, the more actual value-adding innovation is happening.
Lots of startups measure the performance of their business but you can still fail if you are measuring vanity metrics rather
than actionable metrics. Vanity metrics are numbers that portray the startup in the best possible light but which don't actually give
us much insight into what is working or not. These graphs often look like increasing sales graphs measuring gross numbers of users registering or performing some other desirable action on a website. While those numbers look good, it may be masking problems with other more critical metrics like conversions and sales. Ultimately the problem with a vanity metric is that it is not fine grained enough to inform us about what is working and what is not working. If we want to figure out what is working or not, then we need to apply scientific/statistical techniques to the design process.
If we made the effort to measure baseline performance with our MVP we are in a position to conduct A/B testing on some feature to see if it affects our baseline numbers or not. A/B testing involves presenting the potential customer with two versions of the product with one major factor made to differ across the two versions. If we find that version A delivers more sales than version B, and that A delivers more sales than our previous baseline sales, then we can start to develop a causal understanding of what factors are important to the success of our startup and which ones are not.
Eric unashamedly uses the term "cause-effect inferences" (p. 135) to describe the goal of measurement in the lean startup. He believes that
A/B Testing and Cohort Analysis are both readily available techniques startups can use to achieve such understanding. He provides a detailed case study of how the educational startup Grockit applied A/B testing to figure out what was working and what was not working on their learning platform. They believed that peer learning was an underutilized aspect of learning and developed lots of platform features to support it but eventually realized the new features weren't producing improvements in their KPIs. This lead to the realization that learners also want a solo mode for learning which resulted in pivot in their design approach to more fully support both peer-based AND solo modes of learning.
I've discussed the book Getting to Plan B as an important influence on Eric's thinking. Chapter 2 of Plan B, Guiding Your Flight Progress: The Power of Dashboards, offers more useful ideas and techniques around measuring what matters. Plan B advises using Dashboards what list out what leaps of faith you are testing, how they are translated into hypothesis, what metrics you'll use to decide if the leap of faith is true or not, what your actual measurements are, and what insights and responses are appropriate given the results. Here is a simple dashboard for a lemonade stand which illustrates the basic ideas and format/layout they advocate.
What Eric did was add many useful details about the need for baselines, MVPs, innovation accounting, split testing and cohort analysis to this framework. These techniques help the lean startup more reliably find a value proposition and business model that works.
I'll conclude this blog by asking you to think about whether these ideas can be applied to developing new songs? Should a musician begin by develop a Minimal Viable Song that they expose to audiences to get baseline feedback? What key performance indicators might they measure? What variations might they experiment with to see if a change makes the song better (e.g., same lyric but different melodic delivery)? Could they achieve a cause-effect understanding of what elements of the song are contributing to the success of the song? What vanity metrics might mislead them about the success of their song?
I was listening to an interview with a musician recently that suggested she was using a sort of lean startup methodology to figure out how to develop new songs and thought it was an interesting domain of application for lean methods.
Posted on February 24, 2017 @ 06:39:00 AM by Paul Meagher
This weekend I will be going to a Seedy Saturday event where I will invest in some veggie seeds to plant out this year. It is my plan to try to get an earlier start on the growing season this year by transplanting veggies into a cold frame I started building. I got to this stage before winter fully set in.
The cold frame sits on the site of a previous failed attempt to build a cold frame using hay bales in an 8 foot by 4 foot layout. I decided to build a more traditional cold frame this time. I dumped alot of plum seeds here after I processed them to make 5 gallons of plum wine and 5 gallons of plum port (see the reddish dots in the soil). One option would be to see if I can get plum seedlings to start growing in the cold frame and, if any of them take, plant them out to the farm this summer and give some away. I'm quite impressed with the productivity I got from 1 plum tree (10 gallons of drinkable wine) and the natural health and vigor of the tree (left to grow on its own) so I am interested in planting out plum seeds that come from this plum mother tree. I also started a more formal experiment on the farm where I planted 30 plum tree seeds harvested late season from under the plum mother tree. I hilled two rows of soil, made a trench in the middle with my hand, planted the seeds roughly equidistant from each other, then put soil back over the seed. When you are growing trees from seeds in cold-temperate climates, your tree seed planting ideally takes place in the late fall so the seeds cold stratify properly.
On the topic of planting seeds, Urban Market Gardener, Curtis Stone, has a new video on using the Jang Seeder to plant out a bed of radishes. That seeder looks pretty impressive as is Curtis' technique in seeding out a bed.
Seed investors might want to look into a new type of grain seed called Kernza that could be coming to a town near you soon. Check out the Land Institute Vision for perennial agriculture. The Kernza seed is in the initial stages of commercialization.
Maybe not what you were expecting under title of seed investment but the financial use of the term "seed" is a metaphor for the functions and roles of actual seeds.
Posted on February 22, 2017 @ 04:02:00 AM by Paul Meagher
In Lean Thinking the notion of quality is often used to define the type of product an established organization is trying to deliver to the
customer. It doesn't work so well for an innovative startup that doesn't yet know what quality is or exactly who their customers are. In such cases, you have to be less concerned about quality and more concerned about learning. Startup products and services are designed to maximize learning, not quality.
That is the main idea in the chapter Test in Eric Reis' seminal book
The Lean Startup (2011). Here he advocates developing
low cost facsimiles of the product and/or service you envision that the customer will want or agree to use. A mental roadblock we might encounter
is that the facsimile is too cheap in appearance and quality or too much of a kludge to want to expose a customer to it. We have to resist this
urge so that we can test the assumptions, or leaps of faith, that your startup vision implies.
It is in this chapter that Eric discusses the idea of developing a Minimum Viable Product (MVP) as a means of testing your core value proposition and to acquire useful customer feedback. Think up the simplest version of your product or service that might work to test your idea and gather user/customer feedback. Don't let the notion of "quality" hinder you in this effort because you goal is not to deliver a quality product, it is to try to test your main leaps of faith as early as you can with users/customer so you can maximize learning.
In the case of web-based startups, developing a minimum viable product is often easier to do because you can create a demo that offers the minimum number of features that solves the customer problem and release that to a potential user/customer for their feedback. You can then quickly iterate on that demo adding new features based on customer feedback and your vision. When setting up a bricks and mortar business creating a minimum viable product is more difficult but possible. In farming, before you scale up to being a market gardener, you might create a smaller version of your garden that replicates essential elements of your growing system and the types of plants you intend to grow. You might even take the produce
from that garden and agree to supply a neighbor or two with a veggie box over a period of time. Each growing season offers an opportunity to test your growing capacity and value proposition and you might learn that you cannot reliably grow certain vegetables, that you need to plant more of this or less of that, that some piece of equipment might make your life alot easier, that your initial customers are asking for more of this and less of that, etc... Only after you have verified that you have a viable and potentially scalable market gardening business model should you start to invest in alot of the equipment, land, seeds, fertility and labor that would be required to be a commercial market gardener. This is the type of progression that Eric is advocating in the Test chapter - verify then scale.
It takes creativity to create the simplest and smallest version of a product or service that tests your value proposition. E.F. Shumacher observed that "any intelligent fool can make things bigger, and more complex. It takes a touch of genius - and a lot of courage to move in the opposite direction". Some of the most important work a startup will ever do will be done early on at a small scale, searching for, refining, and verifying the business model that you will scale with.
After you read the "Test" chapter, two books that you might want to browse to dig deeper on this topic are:
Value Proposition Design (2015) by
Alexander Osterwalder, Yves Pigneur, Patricia Papadakos, Gregory Bernarda, and Alan Smith.
Value Proposition Design is worth checking out because of the authors involved (check out Alexander Osterwalder's blogging) and because it uses a unique Info Graphics presentation format to express concepts. It offers visual tools and leap testing strategies you might want to use in the early stages of validating your startup vision.
The Startup Owner's Manual is also worth checking out because of the authors involved and the useful startup ideas and techniques discussed. Entrepreneur, educator and author Steve Blank invested in Eric's successful startup company IMVU on the condition that the co-founders attend his Stanford startup class where he applied Steve's ideas about Customer Development to his own company and to the book the Lean Startup. This book is a good resource for learning about customer development and many other ideas that a startup might want to be familiar with in the early stages of their venture.
It is important to recognize that what lean thinking looks like can vary quite significantly depending on context. In the case of early stage startups, lean thinking requires that a higher priority be assigned to learning than quality during the "search" phase of the business (but not the "execution" phase where quality becomes more important). What is produced by the startup in the early stages are products and/or services that are cheap, easy to assemble, and which can be used to test some important aspect of the business model. Startups that are too focused on launching a high quality product may end up releasing a high quality dud into the market place. If you wait to long to engage in the Build-Test-Learn feedback loop, you can end up building something of high quality that no one wants. That is the fatal danger a startup might avoid by engaging in early testing of assumptions via minimal viable products and customer validation techniques. In the early stages of a startup concerns about product or service quality have to take a back seat to concerns about learning. You need to setup a build-test-learn feedback loop as soon as you can to maximize validated learning.
I'll conclude this blog with the observation that Lean Thinking is often associated with the notion of quality but that quality can be sacrificed in certain contexts such as the early stages of releasing your product or service so that you can maximize learning. Ian Flemming in his book Lean Logic (2016) toys with the notion of sacrificing efficiency under certain circumstances. He believes that a lean economy should allow for and encourage a certain amount of slack so that other values beyond minimum prices/maximum productivity are operative. Creativity often occurs when a certain amount of slack time is given to employees to play around with ideas. Just as we need to resist the urge to maximize quality early on a startup, perhaps we should also resist the urge to maximize efficiency because learning and creativity are not necessarily or prototypically efficient activities. In addition to not worrying about quality as much, perhaps we also need to slack off a bit so that we are in the proper frame of mind to begin testing our business model. I don't think Eric would necessarily agree with me that a lean startup should be slack as the lean startup seems to be about being hyper efficient at honing in on a validated business model. Can that be accomplished, however, without introducing the ping pong tables, recreational outings, flex time and other elements of slack required to ensure a certain level of creativity happens?