Posted on October 18, 2017 @ 10:14:00 AM by Paul Meagher
Eric Ries wrote what is probably the most popular book ever on starting a business called The Lean Startup (2011). It is therefore worth mentioning when he publishes any new book on startups. I pre-ordered and received my copy of The Startup Way (2017) yesterday.
According to Eric, this book is 5 years in the making. He argues that many of the same lean startup principles (plus some new ones) apply at the enterprise level, to non profits and to government agencies that want to remain innovative and relevant.
I have not yet read beyond the first chapter of the book but what is particularly interesting to me is the issue of whether companies have to manage things differently at different stages of growth to keep on growing or whether similar management principles apply. In my last blog Scale and Complexity I suggested that different principles might apply to manage complexity as a company scales (based on the work by Verne Harnish); however, Eric appears to be making the provocative claim that many of the same lean management principles apply at all scales and for very different types of organizations (i.e., for profit, non profit, government). Eric argues for a unified theory of entrepreneurship that potentially applies at all stages of company growth if the company wants to keep growing. Obviously management of a company earning > 50 million is different in some respects from management in a company earning < 1 million, but what each company might have to do in order to manage ongoing growth and innovation might be similar in many respects. This is one of the issues that interests me and what I will be attending to as I continue reading this book.
For now, however, I just wanted to draw your attention to this book because it looks like it will be another very popular addition to the startup literature. The book launch appears to have been scheduled to coincide with the launch of Eric's new startup The Long-Term Stock Exchange that will be interesting to follow as well.
So far I'm learning about how the number of patents filed scales with city population size (superlinear - more patents in more populated cities), how the amount of infrastructure (e.g., length of roads, water pipes, electrical cables, gas stations, etc...) scales with city population size (sublinear - less infrastructure per person in more populated cities), how per capita Gross Domestic Product (GDP) scales with city population size (superliner - more GDP per person in more populated cities) and many other interesting scaling relationships. The book tries to give a more fundamental account for why such scaling relationships exist; an account that draws upon research in complexity theory. The book is very readable so far and there appears be virtually no math equations on display but appreciating this book will require you to master some basic mathematical concepts like what a linear, logarithmic, exponential, and power law relationship is. If you are rusty on these important mathematical concepts then reading the book to brush up on this stuff would be one reason to read it because he explains them well in the context of lots of examples and interesting discussion. Ultimately, where Geoffrey wants to get to is a "science of cities" that might consist of a fundamental theory that organizes alot of this scaling data.
I'm not that far into the book yet to give any final review.
Verne argues that companies need to "conquer complexity" (p. 24) in order to scale up and that "complexity generates three fundamental barriers to scaling up a venture" (p. 25):
Leadership: The inability to staffgrow enough leaders throughout the organization who have the capabilities to delegate and predict.
Scalable Infrastructure: The lack of systems and structures (physical and organizational) to handle the complexities in communication and decisions that come with growth.
Marketing: The failure to scaleup an effective marketing function to both attract new relationships (customers, talent, etc.) to the business and address the increased competitive pressures (and eroded margins) as you scale.
Verne argues that you have to keep solving these same problems, often in different ways, at different levels of growth (e.g., < $1 million, > $ 1 million, > $10 million, > $50 million) if you want to keep on growing.
I am looking forward to reading what Geoffrey West has to say about scaling up and the "science of cities" and how that might relate to what Verne Harnish, Toby Hemenway (The Permaculture City, 2015), and Richard T.T. Forman (Urban Ecology: Science of Cities, 2014) have to say about these topics.
Another person who is busy scaling up is the Sweden-based farming entepreneur Richard Perkins who shares alot of useful information in his YouTube channel. He has a recent two part video series on how he intends to use lean thinking to help him double revenue while also reducing his workload. I think they offer a useful case study on the type of planning one might engage in to "conquer complexity" to enable more growth and more free time.
Posted on October 11, 2017 @ 01:03:00 PM by Paul Meagher
I've been enjoying a YouTube video series of a young couple renovating an old farm house. The name of their YouTube channel is Wabi Sab-e. It is a well done, fun and instructive video series. This is the latest installment.
Their process of renovating the old house seems to be driven by taking out walls, flooring, and ceilings to expose the older character of the building. Then they set about trying to improve upon the original character in a direction more consistent with the original style. Some of the blemishes are left to add character.
Me and my wife are also engaged in renovating the upstairs hallway in an old farm house property.
The big improvement here is to level the ceiling by raising it couple of inches halfway down the hallway. Not sure if you want to call the end product Wabi-Sabi but it is a Wabi-Sabi renovation process - semi-planned, opportunistic, and one-off for the most part.
Posted on October 3, 2017 @ 09:09:00 AM by Paul Meagher
A major pre-occupation for me lately is gaining experience with blueberry winemaking.
Over the weekend I crushed six 5 gallon pails of blueberries at my farm property. This yield was added to four 5 gallon pails that were already crushed. Total yield was 45 gallons of blueberry pulp and juice. Plus 5 gallons of plum juice and pulp from a plum tree on the farm property. I will be harvesting grapes from my vineyard in about 3 weeks so this gives me some early winemaking practice.
The video below shows my process for crushing and preparing blueberries for wine making. I do a double crushing of the
blueberries because the berries are smaller than a grape berry which the crusher is more adapted to. Small scale winemaking can be a heavy lifting workout as I demonstrate in the video. You might notice that I don't remove leaves and grass from the blueberries (unscreened). It would be alot of extra work and it is mostly leaves (and a small amount of rye grass) which could be considered a herb flavoring.
I expect the 6 pails I crushed to convert to 7 or 8 pails of fermentable wine once I remove some must from each pail so I can add sugar to create a wine or port style.
There are advantages and disadvantages to the small scale winemaking that I am practicing right now. The main advantage is that because I am making small 5 gallon batches of wine I can experiment with different variables to try to figure out an optimal set of conditions for producing a blueberry cooler, wine or port (e.g., add acid blend or not, add oak shavings or not, control the starting specific gravity through sugar addition or not, etc...). The number of possible permutations is exponential. The disadvantage is that with so many different experiments going on at such a small scale it is hard to guarantee consistency of your product. If I dumped all my berries into a great big vat that is temperature controlled with proper air headspace then I might be able to create a consistent offering from year to year.
It is what it is. Each batch will be unique. For now, I've got to make lemonade out of that lemon reality.
The blueberry cooler style (6% alcohol) is something I will approach from two directions to see which one turns out best. The first approach is to not add sugar, or add very little, to the juice and when it is done fermenting backsweeten with a blueberry jam type fruit pack made from the blueberries. The second approach is to dilute a blueberry wine or port that is done fermenting with water and then back sweeten with the fruit pack. Usually when you make a cooler from a kit you back sweeten with a fruit pack so that is why I think this might work. Here is the preparation process for the blueberry fruit pack that I made by simmering the blueberries for a couple of hours and adding some sugar to taste. Willy Wonka this fruitpack has flavor!
I am ramping up again tonight to process more blueberries into cooler, wine and port styles that I will be fermenting in my garage mini-winery.
It would have been nice to go to wine school to learn winemaking skills, but I'm hoping that deliberate practice over the long term will eventually make up for this lack of formal instruction. Anders Ericsson and Robert Pool's book Peak: Secrets from the New Science of Expertise (2016) offer motivational research on the power of extended deliberate practice to deliver expertise in any skill area.
Posted on September 26, 2017 @ 10:50:00 AM by Paul Meagher
How do economies develop over time?
A common approach to answering this question is to divide the economy into three sectors - primary (extraction), secondary (manufacturing), tertiary (services) - and track the relative number of people employed in these sectors over time. Wikipedia's entry on the three sector economy offers these statistics:
First phase: Traditional civilizations
Primary sector: 65%
Secondary sector: 20%
Tertiary sector: 15%
Second phase: Transitional period
Primary sector: 40%
Secondary sector: 40%
Tertiary sector: 20%
Third phase: Tertiary civilization
Primary sector: 10%
Secondary sector: 20%
Tertiary sector: 70%
The economist Colin Clark was an early theorist on economic development. He created a nice system dynamics diagram to illustrate how the size of each sector changed over time. He tracked 4 sectors in his diagram.
James Beringer in his book The Control Revolution (1986) proposes a 5 sector model of the economy based on the role each sector plays in controlling a significant dimension of the material economy.
As we might expect, an economy's major sectors, as delineated by Clark (1940), Hatt and Foote (1953), and Bell (1973), correspond
to major stages in the essential life process. The primary sector - agriculture, fishing, lumber, mining, oil and gas - represents
the extraction of matter from the environment to produce energy, including the calories to sustain individual organisms. The secondary
sector - processing primary goods, as in construction and manufacturing - represents the synthesis of matter and energy into more organized
forms (negentrophy). The tertiary sector, including transportation and utilities, represents the infrastructure for distributing matter
and energy about the system, while the quaternary sector - trade, finance, insurance, and real estate - constitutes a parallel infrastructure for the collection, processing, and distribution of information that is necessary in all living systems for the control of material flows. Finally,
the "highest" of all sectors in its remove from the physical environment is the quinary sector, including government, law, and education, representing the societal programming - socialization, education, law making - and collective or representative decision making to effect control. ~p. 179.
When thinking about how sectors evolve over time you should avoid thinking that growth in, say, the Secondary sector depends upon growth in the Primary Sector. Growth in the Secondary or Tertiary sectors can in fact drive growth in the Primary Sector. For example, where I come from the prices for blueberries per lb is so low that some growers are not harvesting this year. As an amateur winemaker I felt it was incumbent upon me to see if some greater value can be created by converting the blue berry juice to a cooler, a wine, or port style. Yesterday 40 gallons of blueberries were harvested and today there were crushed into pulp and juice to begin the maceration process. The juice is coming in at 8 to 9 Brix (percent sugar). I have 20 gallons of pulp and juice to work with. My role as a winemaker would be a job in the secondary sector of the economy (manufacturing) and if I was successful it might create more demand and higher prices in primary sector production. Just having an excellent product to sell locally would not be enough to move the needle on demand without also having a higher volume distribution network. Setting up a distribution network would involve working with people in the tertiary sector (transportation and utilities) and above to extend the distribution network.
So how many sectors are there? I don't think the question requires one answer. There are as many sectors as are required to adequately answer the types of questions you are asking. In alot of situations a 3 sector model might be useful (e.g., economic growth in the private sector) whereas trying to understand some finer details of how industrial economies evolve over time required 5 sectors in Beringer's model.
I'll end this blog with a tribute to primary sector workers in the Oil & Gas industry. I had an opportunity last friday to see the rock/blues/reggae band Big Sugar whose song accompanies this video showing some Well Testing work being done in Alberta, Canada.
Jason Calacanis recently released a book called Angel: How to Invest in Technology Startups (2017).
Jason runs a site called This Week In Startups where he interviews leading entrepreneurs and investors. He also made around 100 million in tech investing. Here is a recent discussion at Google Talks occasioned by the release of his book.
The book is named after a diagram that Kate originally developed in a policy document she wrote for Oxfam. She argues that the proper task for a new economics is to develop policies and ideas that ensure that we stay within the light green middle layer of the doughnut by avoiding overshoot and shortfalls.
The diagram is meant to replace the limited goal of increasing Gross Domestic Product (GDP) that most economists are obsessed with. Kate wants to replace the goal of increasing GDP with a broader picture of the many other aspects of our existence that we need to manage better. Kate argues that economics needs new foundational diagrams and pictures and the doughnut diagram is the foundational one for a new economics.
The subtitle of the book is "Seven Ways to Think Like a 21st-Century Economist" and there are seven chapters devoted to the different ways of thinking. The table of contents is reproduced below because it offers a nice brief summary of the 7 ways of thinking that a 21st century economist must master:
Change the Goal from GDP to the Doughnut
See the Big Picture from self-contained market to embedded economy
Nurture Human Nature from rational economic man to social adaptable humans
Get Savvy with Systems from mechanical equilibrium to dynamic complexity
Design to Distribute from 'growth will even it up again' to distributive by design
Create to Regenerate from 'growth will clean it up again' to regenerative by design
Be Agnostic about Growth from growth addicted to growth agnostic
The book does not offer a simple set of solutions to the problems depicted in the doughnut diagram. Rather it encourages us to adopt a different mindset about these problems so that we might find new and better solutions to these problems. Kate discusses interesting recent research, ideas and examples in support of each way of thinking along with ample links to more research you can do on your own if you are so inclined. The seven ways of thinking are not independent of each other and are most powerful when combined to formulate a solution.
This is probably not a book to read if you are looking for a business book that encourages you to make more money or grow your business. There are enough of those books anyway. While that is not Kate's goal in writing the book, the problems she cites are not going away and the power of current economic thinking to solve them are counterproductive in so far is they mostly focus on ever increasing growth as the solution (which is causing many of the problems). I believe there are significant opportunities to create new businesses that arise from thinking like a 21st century economist. The book offers lots of useful ideas and examples to get you started.
She offers an interesting new take on how economics should be structured to remain relevant and useful. I hope to blog about the new economics that Kate envisions but before that I intend to explore some
relevant background material that I will share with you in this blog.
Kate's critique of economics as currently taught and practiced builds upon the shoulders of giants, and one of the main giants is Donella Meadows who is pictured with the Limits to Growth all-star modelling team.
A new economics might also consist of material contained in the free online textbook called The Economy. It will be useful to compare some of what Kate says to what it presented in this site as the core of what should be taught in economics.
Posted on September 5, 2017 @ 06:29:00 AM by Paul Meagher
One often cited classic of aglit (agriculture literature) is Maurice Grenville Kains' book Five Acres And Independence first published in 1935
and revised in 1940. The fact that it is still in print and easily purchased is a testament to its ongoing usefulness.
The book consists of 51 short chapters on a variety of critical areas of farm management from growing crops to managing finances. If you can't read the book, reading the table of contents alone (use Amazon's "Look inside" feature) is worthwhile because it is a masterful summary of the books contents.
The book contains lots of diagrams and figures because it is meant to provide practical instruction on a variety of farm matters. Again, if you don't have time to read the book cover to cover, simply browsing some of the diagrams would be a good way to quickly assimilate some useful content. For example, in the days before electric pumps, an hydraulic ram system was a way to use water to pump water. Here he shows how to setup an hydraulic ram system for use in the field:
Or in the home:
If you do have time to read the book, then you can consult the sections that are most relevant to you. The information does not seem too dated and it is useful to hear the perspective of a successful farmer from 80 years ago to see how they solved many of the same problems that farmers face today.
Some of the chapters that I read about first are his chapters on finance, capital, and accounting. In his chapter on Farm Finance I came across the idea of "hiring money". In the quote below, the masculinity of the pronouns dates the writing and the culture of farming that existed then but the points are still valid:
To determine ways to make money in farming the annual budget and the annual inventory are of prime importance. When the farmer starts business and at the beginning of each of his business years (which may be calendar or his own fiscal year, say March 1) he makes his inventory, then estimates his probable gross expenses and income for each month and for each crop or department so as to determine in advance at what time he is likely to be pinched for money, when he will have surplus, when he must borrow and when he can repay. Knowledge of business methods teaches him that hiring money is the same as hiring labor. [Emphasis mine] So he shows both his budget and his inventory to the cashier of his local bank and arranges for loans perhaps months before he will actually need to borrow. ~ p. 57
I think the notion of "hiring" money is an interesting one that potentially allows us to think more clearly about the role of capital than the notion of "borrowing" money. When a business needs money to startup, expand or as working capital that money is not borrowed but rather hired for a specific job that will ideally return an amount greater than the borrowed amount. We hire labor because their labor generates more revenue than it costs. Likewise, we hire money when we see an opportunity to generate more revenue than it costs.
The metaphor of hiring money encourages us to think about treating any money we might require to finance operations in the same way we would treat money used to hire labor. It needs to generate similar returns to be worth hiring. The metaphor of borrowing money is unhelpful in this regards - you are just putting it back into the original storage without any suggestion that it needs to generate a good ROI for the employer of the capital.
One other aspect of the book that intrigues me is the value assigned to "independence" in the title of the book. In these days of social media, I'm not sure you would be successful promoting the virtues of independence, but there was obviously a time when independence was highly valued, perhaps in the same way that resilience is valued today.
Posted on August 15, 2017 @ 07:44:00 AM by Paul Meagher
In David Perkin's book Making Learning Whole (2009) he has a chapter called "Working on the Hard Parts" in which he stresses the importance of mastering difficult skills and knowledge in order to get to the next level of performance. One of the exercises he has his students (teachers-in-training) do is to devise a Theory of Difficulty (TOD) for a given domain of skill/knowledge. The TOD is supposed to help these teachers-in-training to come up with a better curriculum for learning that skill/knowledge.
It may be useful to think about the TOD associated with successfully starting a particular line of business.
Imagine that instead of you starting your business, you have to teach someone else about how to start your business. Your TOD might
start with these two questions:
What makes starting my particular line of business difficult?
What would the person have to learn in order to overcome those difficulties and be successful?
If I am starting a bike rental business the difficulties I would face in doing so are different than if I am starting a software development company. There are different things I have to be good at and master. A TOD for starting a business can't really be specified in abstract terms. David Perkins is critical of TODs that are overly general and often gives his students this feedback:
Please think about this some more and give us a theory of difficulty that is more specific to your topic. Give us one that doesn't sound like something that could be said for a hundred other topics. There are alot of topics that are complicated or commonly boring or initially unfamiliar or packed with points to remember. Please get specific! You see, theories of difficulty afford much more leverage if they target the particular learning challenges for that particular thing.
It is arguably much easier to come up with a TOD when there is established knowledge for the domain. In the case of starting up a
particular line of business in a particular place, there may be no rulebook unless you are starting a franchise that provides ample guidance on these matters. Your TOD is subject to revision as you learn more about how to succeed in your particular line of business. You may learn, for example, that alot of your bike rental clients are coming from tourist accommodation owners advising tourists on what they can do. Now your marketing approach needs to change to target these accommodation owners. The particulars of what makes marketing your business challenging has changed.
When an entrepreneur starts a business they probably already have an implicit TOD about the challenges of starting that business. Perhaps it would help to be more explicit so that assumptions about where the difficulties lie are clearer and more subject to testing, revision, and hopefully mastery.
The book won the 1986 award for the Most Outstanding Book in the Social and Behavioral Sciences by the American Association of Publishers and NY Times notable paperback in 1989.
In this book Beniger argues that:
... society is currently experiencing a revolutionary transformation on a global scale. Unlike most of the other writers, however, I do not conclude that the crest of change is either recent, current, or imminent. Instead, I trace the causes of change back to the middle and late nineteenth century, to a set of problems - in effect a crisis of control - generated by the industrial revolution in manufacturing and transportation. The response to this crisis, at least in the technological innovation and restructuring of the economy, occurred most rapidly around the turn of the century and amounted to nothing less, I argue, than a revolution in societal control. ~ p. 6
So part of his argument is that a control revolution hit us around the turn of the 19th century (1870 to 1930) with the development of a host control technologies like telegraphs, railroads, bureaucracy, primitive computing, electricity, etc... The revolution however is by no means over - it is neither "recent, current, or imminent" - which I take to mean it is ongoing - it keeps (r)evolving. When Beniger wrote the book sometime before 1986, control technologies associated with new computing and networking hardware/software (aka "information technology") was becoming pervasive and was causing another "revolutionary transformation on a global scale".
One industry where the evolution of control technologies is having a profound effect is agriculture. Many current developments in control technologies are discussed in the recent book Precision Agriculture Technology For Crop Farming (2016) edited by Qin Zhang.
In the first chapter, "A History of Precision Agriculture", David Franzen and David Mulla itemize some of the innovations that had to happen before we could get to the stage of commercially available precision agriculture. These innovations include the development of a Global Satellite Positioning (GPS) network, advances in computing power for mapping, variable rate spreaders to control how much nutrient is provided in a specific area, robotics so that tractors can drive themselves, drones so that mapping can be combined with ariel sensing, developments in sensing technology for all agriculturally important soil characteristics, and the list goes on. There are no signs that precision agriculture will be a fad and there is evidence that it is being adopted faster in some areas like tractor driving before other areas like nutrient management.
It seems that Beniger's book is a good lens for understanding our current state of technological innovation and what might be expected in the future. Alot of innovation is associated with improving control, distributing control, localizing control, centralizing control, and sharing control so the control perspective might be used to evaluate the potential impact of new innovations on society (economically, environmentally, socially).
Recent advances in Artificial Intelligence (AI) are spawning a new revolution in societal control. To understand these issues the control perspective that Beniger offers is useful.
Posted on July 18, 2017 @ 10:56:00 AM by Paul Meagher
The landscape that we see around us today is the result of processes that have taken place at various timescales. There are cycles
of annual growth, cycles of perrenial growth, animal cycles, hydrological cycles, geological cycles and generational human disturbances that can be used to account for why the landscape is the way it is today. Those who are skilled at reading a landscape can tell an interesting story about why the current landscape has the form it has today and the forces that led to its present form. Most of us are not that good at reading the landscape as we don't spend enough time in nature in quiet contemplation of what the landscape is telling us about how it came to be that way. Books help, but there is no substitute for extended direct observation as Permaculture co-founder David Holmgren argues in this video (skip ahead to the 8:30 mark if you want to focus on his landscape reading thoughts):
The urban landscape has many forces operating over different timescales that determine its present form. Perhaps it would repay the effort to sit in quiet contemplation in front of a successful business and imagine all the forces that came together to make it successful. You can also be more interactive and ask the owners what factors have contributed to their success, although they alone cannot determine their fate - the forces within the larger landscape are major determining factors.
Books help in informing our observation as they might direct our observation towards aspects that we might be missing. A big influence on urban landscapes are the modes of transport that its residents typically use to get around. Do they typically walk, bike, take public transport, or drive to where they need to go? This can determine how traffic interacts with buildings and how cities are laid out. In the excellent textbook Urban Ecology: The Science of Cities (2014) Richard Forman
offers up this interesting but somewhat vague set of comparisons (p. 286):
Bicycling: San Jose, Portland, Sacramento, Seattle.
Public Transit: Newark, Seattle, Portland, Pittsburgh, Miami, Denver.
Walking: Orlando, Fort Lauderdale, Kansas City, Fort Worth, Indianapolis, San Jose.
Bicycling: Kansas City, Pittsburgh, Cincinnati, San Antonio, Fort Worth, Newark, Indianapolis.
Public Transit: Fort Worth, Kansas City, Indianapolis, Orlando, Norfolk, Fort Lauderdale.
Perhaps in a city where people walk and bike more often, successful buildings are more likely to be clumped together than in cities that mostly use motorized vehicles to get around? Factors like this may be
behind the patterning we see. Perhaps it would repay the effort to engage in direct observation of traffic patterns around locations to understand what type of transport passes in front of it, and interacts with it, and use that information in your design and thinking.
Some skills we can be acquired quickly, but as David points out some skills cannot be rushed and require extended periods of direct observation and interaction informed by past observations and current understandings. The ability to read the urban landscape is one of those skills. We all have the ability to some extent but it can be improved.
Posted on July 7, 2017 @ 09:03:00 AM by Paul Meagher
Busy on the farm property doing construction work. I'm getting ready to remove and install a window in the 170 year old farm house.
We finished getting the old rock basement ready to store some wine from last year's harvest and this morning I built a pad and loaded the wine cases onto it. This area stays humid and cool over the summer which is great for storing wine. I blended all of my red wine with a liter or two of plum port and will need to allow it settle for a few months to get a good gauge on the taste it will ultimately have. I needed to sweeten the wine as the grapes do not develop as much sugar content in this climate and the unadjusted wine is too sour. I used some plum port I made from a plum tree on the property to sweeten (after the red wine was fermented to completion).
My brother is spreading rock behind the barn to get the floor of a lean to shed ready for cement. Might be the future home of the winery.
I did manage to frame in the new window and temporarily screwed it into the frame. I'll have to rebuild the header (need more height), double up the thickness of the outer frame (to get proper alignment with exterior siding), and weather proof it tomorrow. The window is wider and taller than what was there before so lots of tweaking to get it right.
Posted on June 29, 2017 @ 12:04:00 PM by Paul Meagher
Lean Startup Theory advocates the use of ongoing experimentation to find out if customers value your product or not. The use of A/B testing is often used determine if some feature is having a significant positive influence on customers or not. The popularity of A/B testing derives from the fact that it is easy to change some minor feature of a website to see if some success measure is improved or not relative to the control/existing version of the website. The technique is easy and the math is easy (but check this out).
A/B testing is only one experimental technique that might be used and it has some limitations. One limitation is that it is often used to test only one factor or version at a time to see if the factor/version improves success metrics or not. Optimal performance is often a function of the interaction of two or more factors that can not determined by testing one factor at a time. Chemical reactions can occur optimally at a combination of temperature and pressure that is not predicted by studying each factor separately.
Today I want to mention a methodology that is not that well known but which is used in industry to find the factors and the levels of each factor that produces optimal outcomes. That methodology is called Response Surface Methodology (RSM) and is commonly used in chemical industries to find the optimal operating conditions (temp, pressure, catalytic agents, reactants, pH, etc..) for producing a chemical reaction.
Response Surface Methodology begins by listing all the factors that might contribute to the response. It also examine the levels
that each of these factors might take on. When you do this you quickly run into a combinatorial explosion of factor levels to
test. Where Response Surface Methodology comes in is to help guide you towards a reduced set of factors/levels to interatively test to arrive at an estimate of the optimal factor level settings.
All I can hope to do in this blog is mention a couple of ideas from response surface methods that I found interesting and am still exploring.
If you have, say, 3 factors (temperature, pressure, pH) with 5 levels then to run a full factorial design requires that you measure responses under each of the possible 125 conditions. This is generally not economically feasible so the question becomes whether you can find the optimal condition by studying some subset of conditions, often called a fractional factorial design. One such design that is popular in RSM is called Central Composite Rotable Design. That is an intimidating phrase for a neat idea. Basically you reduce the number of levels by only testing the extreme levels of each factor along with the median level of each factor and interpolating all the values that would fall in between.
So if you wanted to test the growth of a plant as a function of nitrogen and moisture instead of studying all the levels of each factor you would only test the response for the median levels of each factor and the extreme levels of each factor and try to interpolate what the response would be between these levels. Other fractional designs are possible.
The second idea from RSM that is worth thinking about is to plot the levels of your factors on each axis to generate a response surface that depicts our how the variables interact. The combination of moisture and temperature levels will generate a growth response in the plant that can be plotted as a response surface that an educated eye can read to better grasp what the optimal factor levels might be, or what tradeoff might might be best to make. We are all familiar with drawing and interpreting graphs consisting of curves, but not so familiar with drawing and interpreting surfaces and contours so as to understand the interaction of 2 variables. Being able to visualize the interaction of 2 variables as response surfaces can allow our visual system to process the information more thoroughly than a set of numbers would.
I have found that a good starting point for understanding response surfaces is Khan Academy's tutorials on
Multivariate Calculus. You don't have to know
calculus to learn some useful multivariate skills from the first few tutorials.
I hope this blog has helped to convince you that there are experimental methodologies besides A/B testing that might be
applied to discovering the right combination of factors for your product or service. One at a time testing does not provide any insight into the potential interactions of that factor with other factors. For that you need a factorial design and to administer it efficiently you may want to consider response surface methodologies.
The definitive text on RSM is by George Box and Norman Draper with the title Response Surfaces, Mixtures, and Ridge Analyses (2nd, 2007). Not an easy read but worth scanning for ideas and probably very useful if you want to use RSM to optimize your product or service.
Posted on June 22, 2017 @ 10:47:00 AM by Paul Meagher
Jean Martin Fortier, in his excellent book The Market Gardener (2014), explained and illustrated how he and his wife make 100,000$ per acre. There farm is an example of a very high yielding enterprise measured by the quantity of produce grown or income generated.
A critical aspect of their argument as to why the farm was high yielding was because he did not use a standard tractor and its accompanying implements to cultivate the land. Instead he relied on smaller scale equipment that was appropriate to the permanent bed system he setup on his 1.5 acre gardening area. He argued that this helped also with the financial yield of the system because he did not have associated machinery debt and maintenance costs. He was not afraid to spend money on tools that improved his productivity, he just made the decision that he didn't see a role for a standard tractor in maximizing yield.
The metaphor of the market gardener is that there are alot of potentially good paying niches our there were our focus might turn to improving quality and getting better at production, rather than getting bigger. Investments into quality and efficiency can still increase yield without dedicating more physical area to production. By focusing on quality and efficiency, we might increase yield by getting more production using less work and inputs and higher prices for better quality. Fortier's argument is that getting bigger in physical scale is not the best route to increasing yield.
That being said, Jean Martin had a generous benefactor invest alot of money into scaling up the market gardening approach to more than 1.5 acres (to 8 acres). This latest video shows how he is scaling up in a way that remains true to many of his market gardening practices, but he now has the room to incorporate new animal and permaculture systems to potentially produce even greater per-acre yields. That is still to be determined. As far as his benefactor is concerned, the most important yield of the system might be the trained market gardeners that the larger scale operation can foster.
There are multiple types of yield a business can try to optimize for and which defines what the enterprise considers success.
Posted on June 13, 2017 @ 07:47:00 AM by Paul Meagher
In previous blogs (part 1, part 2, part 3), I have argued that the term yield is most useful as a measure of productivity per unit area. Some usages of the term yield are simply productivity measures without any accounting of the area involved (e.g., stock and bond yields). Here we will delve deeper into the spatial aspect of yield and talk about yield mapping. Yield maps are visual depictions of how yield varies as a function of GPS coordinates.
There is a convergence of technology in agriculture that enables on-the-fly calculation of yield as an operator is harvesting a field.
Yield mapping technology is built into some combine harvesters now so the operator can gauge or verify that a certain part of a field is yielding more than others and to compare to historical yields from that area.
The 4 ft x 8 ft garden I planted in my cold frame exhibits a similar variability in productivity per unit area with yield being quite high in most areas, but with a noticeable gap in one area where I have planted basil (at the same time as the other crops).
The power of yield mapping comes from comparing it with other maps that contain information about the presence of other variables.
A combine harvester might also contain sampling tools that record the level of nitrogen or moisture in the soil as it progresses through the
field enabling the operator to see how the yield map might be explained by the levels of nitrogen and moisture in those areas. The
yield maps might also be compared with maps produced by flyover drones doing multi-spectral imaging as a basis for measuring different
field characteristics. The point is that to increase yield we can't just measure yield itself, we also have to measure other characteristics that might explain the yield patterns and, in the case of farming, would allow us to make precise interventions to improve yield.
So the concept of yield mapping includes not just mapping the levels of productivity over an area but can also be extended to mapping associated variables that might be used to explain and improve yield (e.g., where it might be lacking in, say, nitrogen in a certain part of the field).
In a store front, we could measure yield per square foot or cubic foot of space. We could do yield mapping of each shelf in the store and
compute the relative yield derived from the different locations of the store. We might measure yield by computing the amount of income generated by a given area of shelf space. Perhaps we could optimize store front yield by co-relating the yield map to the presence of other variables that might co-vary with such yield. Yield in agriculture is also affected by ambient conditions like the weather. Similarly, yield in a store front would be affected by factors such as types and levels of traffic, socioeconomic status of the catchment area, and the competitive landscape. Something like yield mapping might be useful to do in bricks and mortar establishments.
The term yield mapping was briefly mentioned in the interesting book Push Button Agriculture: Robotics, Drones, Satellite-Guided Soil and Crop Management (2016) by K.R.Krishna. The author argues that the next level of productivity improvement in industrial agriculture is now happening but will become more pronounced as robotics, drones, and gps technology makes further inroads into farming. The level of productivity per unit area of land will increase because we have more precise control over what needs to be done to maintain or increase yields (via maps created using drones, gps, and onboard sensors) but also because robotic innovation will continue to reduce the need for repetitive work to be done by humans. A lesson from industrial agriculture is that precision and robotics are two major factors that are now being targeted to increase yields even further.
Posted on June 6, 2017 @ 08:23:00 AM by Paul Meagher
I had some additional thoughts on increasing yield this weekend that will be the focus of today's blog (earlier thoughts at part 1 and part 2).
Just to refresh, I use the term yield to refer to a measure of productivity per unit area. Productivity might be measured in dollars or
in bushels of corn. Often dollars are used as a surrogate measure of yield but it is not perfectly correlated with physical yield because the
yield in dollars is also affected by supply and demand. That being said, we are often interested in yield measured both in dollars and bushels
as they both provide useful information.
The calculation of yield is also affected by two major complicating factors.
One complicating factor is that yield is a multidimensional concept. You can increase yield across several dimensions at the same time and
a good designer often is.
In 2011 Ethan Roland & Gregory Landua wrote an influential essay called
The 8 forms of capital. This diagram gives you a
quick overview of the categories they posited.
Where Ethan and Gregory use the term "Capital" I might use the phrase "Types of Yield" and regard each of these as types of yeild a project
Another complicating factor is that yield can be hard to assign. For example, I sell square bales of hay from my barn to clients consisting
mostly of horse owners. One horse owner confided to me today that she keeps her horses in the barn during the hot part of the day when the
flies are bad. She likes to have some hay available for them to eat. The hay that we sell to such horse owners is stored in the barn and sold from there.
What is the yield of the barn measured in dollars? Besides the tricky, but interesting math involved, we also have the problem of deciding what percentage of the final price obtained should be attributed to the storage aspect. There were also the costs of mowing, teddering, raking, baling, moving it into the barn, and beer to quench the workers. You can assign a percentage but to find solid grounds for doing so may also be tricky.
Ultimately, we always have to come back to the fact that yield is meant to be a practical concept that we might use to assess performance on a per unit area basis. These complications make the calculation of yield more difficult but possibly also more meaningful and relevant.
Posted on May 26, 2017 @ 10:00:00 AM by Paul Meagher
One of the things I love about gardening is the experimental nature of it. It is a great venue for applying experimental methods to the world. Every time you plant a seed you have the opportunity to plant a similar seed under a different condition and see if that matters. For example, I just
finished planting some tomato and pepper seeds that I will start under some grow lights. I have some left over seeds from the packets that I can also plant outside in my backyard greenhouse. I can then observe what benefit there is to starting seeds under grow lights versus direct seeding into greenhouse soil. I can potentially observe germination rates, the relative mortality of germinated plants, the effects of hardening off/transplanting for seedlings started under grow lights, days to harvest for the differently grown plants, etc...
Experimentation also means trying something out that may be kind of bizaare to see if it works or not. In this regards, I built a cold frame this year and started different varies of lettuce, carrots, kale, sweet basil and chives in it this spring. I also planted something else. In the late fall of last year I processed some plums into plum wine. I dumped the extracted plum seeds into the soil where I built my new cold frame. Instead of removing the plum seeds before I planted, I decided to spread them around and covered them with 3 to 4 inches of new soil. I planted my veggies into the top layers of this soil in the early spring. Yesterday I observed what I believe is the first plum seedling sprouting up amidst the lettuce.
This can perhaps be viewed as an example of vertical stacking; but instead of stacking one row of veggies above another row of veggies to maximize growing space; I am stacking seeds in the soil at different
layers to grow quite different types of plants in the same growing area - veggies and plum trees.
Bill Mollison, the father of Permaculture, famously said:
The yield of a system is theoretically unlimited, or, limited only by the information and imagination of the designer.
He often enjoyed showing how you could keep stacking functions within the same limited area to get more and more yield out of that area. An important goal for alot of (sub)urban gardeners is arguably to maximize the yield of their growing area. It requires experimentation in both the methodical and crazy senses to find new methods to reliably increase yield.
Last night, I started watching Elon Musk's recent Ted Talk where he talks about ways to increase mining, traffic and energy yield (among other topics). Perhaps one of the secrets to Elon's thinking is his ability to see how yield can be increased beyond what others can imagine.