Tuesday, December 9, 2014

China: Looking for an opportunity offshore

I've been thinking about China more recently. It seems that every ~ 5-7 years the tone/direction changes and I feel that we are in the midst of one of those changes.

A recent article in the WSJ observed:

As China's investment-led economic model shows signs of sputtering, Beijing is looking for ways to turn its state sector into a driver, not a drag on growth. Companies that serve as vehicles of national and Communist party ambition and stand at the commanding heights of the economy are increasingly expected to be market-driven.

This aligns with some of my recent observations. I would assert that we have seen 4 phases of evolution in China over the past ~30 years:

Phase 1: Learning
China invited in multinational companies to the market. Some were burned by loose IP treatment. But, the Chinese market was able to understand how those businesses operated, gain knowledge, and contemplate future investments and moves.

Phase 2: Export
Learning in Phase 1 that the country did not possess an IP advantage that the moment, a strategy focused on China's unique value proposition was needed. At this point in time, that value proposition was low cost. Accordingly, export-driven GDP became the focus.

Phase 3: Nationalism
In Phase 3, the focus turned to building Chinese companies to serve the Chinese market and to participate in exports, if applicable. This led to the rise of companies like Haier, Alibaba, and Huawei to name a few. The tale end of this era included a move away from supporting and partnering with non-Chinese multinationals. It created a stand-off of sorts, that is yet to be fully resolved.

Phase 4: Multinational Chinese companies
I believe we are at the start of this era. This is about Chinese born and based companies, extending the operations offshore (off the mainland). Non-Chinese multinationals that aggressively partner with Chinese multinationals to enable this, will likely reap the benefits on the mainland via a quid-pro-quo of sorts.

Despite a host of structural issues, the future is bright on the mainland. There are opportunities in healthcare, data & analytics, and improving cities to name a few. Those rewards will likely go to those companies that are most aggressive in giving China what they want: an opportunity offshore.

Thursday, December 4, 2014

Big Data Revolution

My book is finally coming (looks like January). I shared a draft of the foreword here, and thought I would share Chapter 1 now, as we are getting down to final proofs. Patrick McSharry, my co-author, is a friend that I met on the journey. Note: the graphics and formatting will be cleaner/sharper in the book.

Blog subscribers (you can subscribe on the right side of this page) will receive a copy of Chapter 2: Why Doctors Will Have Math Degrees, once it's ready.

Chapter 1: Transforming Farms with Data


AS THE WHEELS came down on my cross-country flight, I prepared for our landing at San Francisco International Airport (SFO). Looking out the window,I could see the sprawl of Silicon Valley, the East Bay, and in the distance, the San Francisco skyline. It is hard to believe that I was here to explore agriculture in 2013, given that what I could see from the plane was mostly concrete, highways, and heavy construction.

Not too many miles away from SFO, I began to wind through the tight curves of back roads, making my way to the headquarters of a major agricultural producer. While I had never visited this company before, I had the opportunity to sit down with the executive team to explore the topic of big data in farming and agriculture.

I embraced the calm and serene scene, a far cry from the vibrancy of San Francisco and the rush of Silicon Valley. As we entered a conference room, the discussion turned to produce, as I asked, “Why is it that the strawberries that I bought last week taste so much better than the ones I bought the week before?” While I posed the question as a conversation starter, it became the crux of our discussion.

It seems that quality — and, more specifically, consistency of quality — is the foremost issue on the mind of major producers. I asked about the exquisite quality of produce in Japan. The executive team quickly noted that Japan achieves quality at the price of waste. Said another way, they keep only
10 percent of what a grower provides. This clarified the point in my mind that quality, consistency of quality, and eliminating waste create the three sides of a balanced triangle.

The conversation that followed revealed one significant consensus in the room: Weather alone impacts crop production and the consistency of crops. And since no one in the room knew how to change the weather, they believed that this was the way things would always be. I realized that by blaming the weather this team believed their future did not belong in their own hands but was controlled by the luck, or the misfortune, of each passing season.


The evolution of farming in the developed world provides context to much of the conventional wisdom about farming that exists today. Dating back to the 1700s, farming has been defined by four eras:

1700s (Subsistence Farming): Farmers produced the minimum amount of food necessary to feed their families and have some in reserve for the cold winter months.

1800s (Farming for Profit): This era marked the transition from subsistence farming to for-profit farming. This is when the widespread use of barns began, for the purpose of storing tools, crops, and related equipment. These were called pioneer farms.

Early 1900s (Power Farming): At this time, the “power” came in the form of 1,800-pound horses. The farmers used animals for plowing, planting, and transporting crops. The use of animal labor drove the first significant increase in crop productivity.

Mid-to-Late 1900s (Machine Farming): Sparked by the Industrial Revolution, this era’s farmers relied on the automation of many of the tasks formerly done by hand or animal. The addition of machinery created tremendous gains in productivity and quality.

Each era represented a significant step forward, based on the introduction of new and tangible innovations: barns, tools, horses, or machines. The progress was physical in nature, as you could easily see the change happening on the farms. In each era, production and productivity increased, with the most significant increases in the latter part of the 20th century.

Through these stages, farming became more productive, but not necessarily more intelligent.


The current era of farming is being driven by the application of data. It is less understood than previous eras because it is not necessarily physical in nature. It’s easy to look at a horse and understand quickly how it can make farm labor easier, but understanding how to use geospatial information is a different proposition. The advantage is driven by intangibles: knowledge, insight, decision making. Ultimately, data is the fertilizer for each of those intangibles.

A simple understanding of how a crop grows can aid in understanding the impact of data on farms. The basic idea is that a plant needs sunlight, nutrients from the soil, and water to grow into a healthy plant, through a process called photosynthesis. Healthy plants must keep cool through a process called transpiration (similar to how a human sweats when physically stressed). But, if a plant lacks the nutrients or conditioning to transpire, then its functions will start to break down, which leads to damage. Using data to improve farming is fundamentally about having the ability to monitor, control, and if necessary, alter these processes.

Today, according to the Environmental Protection Agency, there are 2.2 million farms in the United States and many more outside of the U.S. The average farm spends $110,000 per year on pest control, fertilizer, and related items to drive yield. The prescient way to improve profit and harvest yields across a vast territory requires better collection, use, and application of data.


Potato farming can be exceedingly difficult, especially when attempted at a large scale with the goal of near perfect quality. The problem with potato farming is that the crop you are interested in is underground; therefore, producing a high-quality and high-yield potato crop depends on agronomic management during the growing process.

At the Talking Data South West Conference in 2013, Dr. Robert Allen, a Senior GIS Analyst at Landmark Information Group, highlighted the importance of data in potato farming, in his talk titled, “Using Smartphones to Improve Agronomic Decision Making in Potato Crops.” Dr. Allen makes the case that leveraging data that describes the growth and the maturation of a crop during the growing season is instrumental to a successful yield. Continuous insight, delivered throughout the growing season, may have a material impact on the productivity of a crop.

One of the key variables required for yield prediction, and needed to manage irrigation, is groundcover. Groundcover, which calculates the percentage of ground covered by green leaf, provides critical input in the agronomic management of potato crops. Measuring groundcover is not as simple as pulling out a measuring tape; it requires capturing imagery of potato crops and large-scale collection of data related to the images (the water balance in soil, etc.), and the data must be put in the hands of farm managers and agronomists so that they can actually do something about what the data is telling them. The goal is not to collect data, but to act on it.

Dr. Allen describes four considerations in potato farming related to using data:

Time: Data needs to be collected at regular intervals and decisions need to be made in near-real-time.

Geography: These tend to be large-scale operations (10,000 to 20,000 acres), with fields distributed over large areas.

Man power: Data is often collected by farm field assistants (not scientists) and must be distributed because decision makers tend to be remote from the field.

Irrigation: Irrigation, while very expensive, is a primary factor in the maturation of a potato crop. Utilizing data to optimize the use of irrigation can lead to a productive crop, at the lowest possible cost.

These considerations led to a data collection and analysis solution called CanopyCheck. While it requires only a download from Apple’s App Store, it provides a rich data experience to compare groundcover and other related data to optimize the quality and yield of a potato crop.

The Landmark Information Group describes CanopyCheck (http:// download.cnet.com/ios/landmark-information-group/ 3260-20_4-10094055.html) as

This app is for potato growers, using the CanopyCheck ground- cover monitoring system, and captures accurate and reliable images of the potato crop which can be used to describe crop development. Each image is geo-located and labelled with farm and field information specified by the potato grower on the accompanying CanopyCheck website.

Conventional wisdom states that growing potatoes is easy: They don’t need sunlight, they do not need daily care, and by controlling the amount of water they receive, growing potatoes is a fairly simple process. However, as is often the case, conventional wisdom overlooks the art of the possible. In the case of potatoes, the application of data and agronomy can drive yield productivity up 30 to 50 percent, which is material in terms of the economics and the waste that is reduced.


Whether you strike up a conversation with a farmer in the 1800s, 1900s, or even in the early part of this century, they would highlight:

1) Their growing strategy evolves each year.

2) While the strategy evolves, their ability to execute improves each year,based on increased knowledge.

While this farming approach has been good enough for the better part of three centuries, the Data era ushers in the notion of precision farming. According to Tom Goddard, of the Conservation and Development Branch of Alberta Agriculture, Food and Rural Development, the key components of precision farming are:

Yield monitoring: Track crop yield by time or distance, as well as distance and bushels per load, number of loads, and fields.

Yield mapping: Global Positioning System (GPS) receivers, along with yield monitors, provide spatial coordinates, which can be used to map entire fields.

Variable-rate fertilizer: Managing the application of a variety of fertilizer materials.

Weed mapping: Mapping weeds using a computer connected to a GPS receiver while adjusting the planting strategy, as needed.

Variable spraying: Once you know weed locations from weed mapping, spot control can be practiced.

Topography and boundaries: Creating highly accurate topographic maps using a Differential Global Positioning System (DGPS). This data can be used to take action on yield maps.

Salinity mapping: This is valuable in interpreting yield maps and weed maps, as well as tracking the salinity over a period of time.

Guidance systems: Guidance systems, such as DGPS (accurate to a foot or less) are valuable for assessing fields.

Records and analyses: Large data collection is necessary to store pertinent data assets, along with images and geospatial information. It is important that this information can be archived and retrieved for future use.

The extensive insight that can be gained by collecting each of these data points is potentially revolutionary. It evolves a process from instinctual to data-driven — which, as seen in the potato example, has a fundamental impact on yields and productivity.

The underlying assumption is that the tools and methodology for capturing farm data are available and utilized efficiently. This is a big assumption because many farms today are not set up to actively collect and capitalize on new data assets. Accordingly, the ability to capture farm data becomes the source of competitive advantage.


It sounds easy. Collect data. Then use that data to deliver insights. But, for anyone who has been on a rural farm in the last decade, it is easier said than done. There are limitations that exist on many farms: lack of digital equip- ment, lack of skilled technology labor, poor distribution of electricity, and poorly defined processes. Because of these factors, each farmer must establish a new order of doing things to take advantage of the Data era. The data landscape for farming consists of three primary inputs.

Sensing equipment: Mounted devices on machinery, in fields, or anywhere near crops could be designed to collect/stream data or to control the application of water, pesticides, etc. This could range from instrumented tractors for harvesting to devices to monitor crop transpiration. The evolution of machines to collect data on crops and soil has been dramatic. In the last decade alone, equipment has evolved from mechanical-only to a combination of mechanical and digital technology. This change has been expedited by early insights that even small adjustments in planting depth or spacing can have huge impact on yields. So, while today the sensing equipment is largely a digitized version of common farm machines, the future will see a marked advancement in machines. Drones, driverless tractors, and other innovations will become commonplace.

Global Positioning System (GPS): GPS provides the ability to pinpoint location accuracy within one meter. While GPS first emerged for automobiles in the early 1990s in places like Japan, it has just now become common in all automobiles. Farming equipment, as you may expect, has been even a step further behind, with the wide use of GPS just accelerating in the last decade.

Geographic Information System (GIS): GIS assesses changes in the environment, tracks the spread of disease, as well understanding where soil is moist, eroded, or has experienced similar changes in condition. Once you know weed locations from weed mapping, spot control can be implemented. Topography and geology are important considerations in the practice of farming. Both are well accounted for with modern-day Geographic Information Systems.

By combining these three inputs, farmers will be able to accurately pinpoint machinery on their farms, send and receive data on their crops, and know which areas need immediate attention.


John Deere founded Deere & Company in 1836, when he moved to Grand Detour, Illinois to open a repair shop for farming tools. Deere eventually moved beyond tools and into the production of plows, which became a mainstay in the Farming for Profit and Power Farming eras. In 1848, Deere relocated to its still-current home in Moline, Illinois, and after his death in 1886, he passed the presidency of the company to Charles Deere.

Charles led the company into the 20th century, where the company pioneered the move to gasoline tractors, which became the defining product of not only the company, but of farming and agriculture in this time. The dominance of the company was ensured by continuous innovations in their tractors, innovation in their business model (a robust dealer network), and their defining image: John Deere green. As of 2010, the company employed 55,000 people and was operating in 30 countries worldwide. A shoe-in for continued dominance, right?

Monsanto, founded in 1901, took a bit longer to come into its defining moment. Moving into detergents and pesticides, Monsanto eventually became the pioneer in applying biotechnology to farming and agriculture. With biotechnology at its core, Monsanto applies data and insight to solve problems. Accordingly, Monsanto was a data-first company in its birth, which continued to drive its innovation and relevance. But sometimes, it takes time for an industry to catch up to its innovative leaders, and the first major evidence of how Monsanto would lead a change in the landscape was seen around 2010. That is when you see the fortunes of Deere & Company and Monsanto start to go in different directions.

Monsanto had one critical insight: Establishing data-driven planting advice could increase worldwide crop production by 30 percent, which would deliver an estimated $20-billion economic impact — all through the use and application of data. As Monsanto bet the company on the Data era, the stock market began to realize the value of the decision, leading to a period of substantial stock appreciation.

Data is disrupting farming, and we are starting to see that in the business performance of companies driving innovation in the industry. Gone are the days in which a better gasoline tractor will drive business performance. Instead, farmers demand data and analytics from their suppliers, as they know that data will drive productivity.


Monsanto calls their approach to farming in the Data era, Integrated Farming Systems (IFS). Their platform provides farmers with field-by-field recommendations for their farm, including ways to increase yield, optimize inputs, and enhance sustainability. Listening to the data and making small adjustments to planting depth or the spacing between rows makes a vast difference in production. As Monsanto says, this is “Leveraging Science- Based Analytics to Drive a Step Change in Yield and Reduced Risk.”

Monsanto’s prescribed process for Integrated Farming Systems involves six steps:

1. Data backbone: Seed-by-environment testing to produce on-farm prescriptions
2. Variable rate fertility: Adjusting prescriptions, based on conditions.
3. Precision seeding: Optimal spacing between rows
4. Fertility and disease management: Custom applications, as needed
5. Yield monitor: Delivering higher resolution data
6. Breeding: Increase data points collection to increase genetic gain

FieldScripts became the first commercial product to be made available as a component of Monsanto’s overall IFS platform. FieldScripts provides accurate seeding prescriptions for each farmer and each field.

Monsanto, through its seed dealer network, engages directly with farmers to optimize two variables: planting and seeding technology data. The seeding technology, which is primarily data about seeding, is the differentiating factor. Applying that insight to a personalized planting plan enables Monsanto to deliver personalized prescriptions for every field.

FieldScripts, delivered via iPad, utilizes a custom application called Field- View. FieldView, deployed to farmers, while leveraging the data acquired throughout the years, equips farmers with the tools and insights needed to make adjustments for optimal yields.

Deere & Company and Monsanto both have bright futures. According to Jeremy Grantham, chief investment strategist of Grantham Mayo Van Otterloo (GMO), with the world’s population forecasted to reach almost 10 billion by 2050, the current approach cannot sustainably feed the world’s population. The demand presented by population growth creates an oppor- tunity for all companies that service the industry. For the moment, Monsanto has leaped ahead in this new era of data-farming over the past five years, forcing Deere & Company to play catch-up.


Data is starting to prevail in agriculture. This is evident not only in the changing practices of farmers, but also in the ecosystem. New companies are being built, focused on exploiting the application of data.


Monsanto’s aggressive move into the Data era was perhaps punctuated in October 2013 with their announced acquisition of the Climate Corporation for $930 million. Why would a firm with its roots in fertilizers and pesticides spend nearly $1 billion on an information technology (IT) company? This aggressive acquisition demonstrates the evolution of the industry. “The Climate Corporation is focused on unlocking new value for the farm through data science,” commented Hugh Grant, the chairman and chief executive officer for Monsanto. Founded in 2006, the Climate Corporation employs a team unlike any other in the agriculture industry. The team is composed of many former Google employees, along with other elite technology minds from the Silicon Valley scene. The tools they develop help farmers boost productivity, improve yields, and manage risks, all based on data.

At the heart of this acquisition lies the core belief that every farmer has an unrealized opportunity of around 50 bushels of crop (corn, potatoes, etc.)in each of their fields. The key to unlocking these additional bushels lies in the data.

While the leaders of the past would provide better machines, Monsanto focuses on providing better data. By combining a variety of data sources (historical yield data, satellite imagery, information on soil/moisture, best practices around planting and fertility), this information equips the farmers with the information they need to drive productivity.


GrowSafe Systems began studying cattle in 1990. This was not a group of former cattle hands, but a team of engineers and scientists who foresaw data science as playing a role in cattle raising. In 2013, the GrowSafe team won the Ingenious Award from the Information Technology Association of Canada for best innovation. This was the first time that this organization gave an innovation award to anyone in the world of cattle.

GrowSafe developed a proprietary way of collecting data through the use of sensors in water troughs and feedlots. With these sensors, they track every movement of cattle, including specifics about the cattle themselves: con- sumption, weight, movement, behaviors, and health. Each night, the data is collected and then compared against a larger corpus of historical data. The goal is to look for outliers. GrowSafe knows that the data reveals information that cattle farmers often cannot detect. This innovative approach enables farmers to prevent a disease before it begins.


The mainstays of today’s farms are people, fertilizers, irrigation, gas machines, trucks and carts for transport, and local knowledge. It is a craft, and typically the only person that can run a certain farm is the person that started it. This is why so many farms fold after the head of the operation retires. The success is in their hands — it’s their craft.

Farms in 2020 will have a completely different feel from today’s farms. In fact, they may be unrecognizable to a farmer of the early 21st century. Approaches that seem futuristic today will be common to all farmers in 2020:

Digital machines: Digital machines, acting as sensors, will be the norm. The days of simple gas machines will be far in the past. In fact, by 2020, many farm machines will be battery- or solar-powered, with gas itself becoming a rarity. The digital machines will be much more than Internet-enabled tractors. There will be drones. Many drones. In fact, drones will become the most cost-effective and precise mechanism for managing many chores that farmers do via hand or by tractor today. With the sprawl of digital machines, device management will become the “cattle herding of the future,” as all devices will have to be managed and maintained appropriately.

IT back office: Every farm will have an information technology (IT) back office. Some will manage it themselves, while many will rely on a third party. The IT office will be responsible for the aforementioned device management, as well as remote monitoring and, ultimately, data-driven decision making. The IT back office will be the modern-day farm hand, responding to the farmers’ every need and ultimately ensuring that everything operates as programmed.

Asset optimization: With the sprawl of new devices and machines, asset optimization will be at the forefront. Maximizing the useful life of machines, optimizing location, and managing tasks (workloads) will be key inputs into determining the productivity of a farm.

Preventative maintenance: Digital machines, like gas machines, break. It is a reality of complex systems. This fact places the burden on preventing or minimizing outages because of maintenance and repairs. Many of the digital machines and devices will be designed to predict and prevent failures, but ultimately, this must become a core compe- tence of the farmer or his IT back office. Given that each farm will use the machines differently, the maintenance needs will likely be unique.

Predictable productivity: In today’s farms, the yield and productivity of crops vary significantly. Whether it is the weather, impacts of deforestation, or the impact of certain pesticides and fertilizers, it is an often-unpredictable environment. By 2020, productivity will be more predictable. Given all of the sources of data, GIS and GPS capabilities, and the intensive learning that will happen over the next five years, yields will become predictable, creating greater flexibility in the financial model for a farmer.

Risk management: In 2020, instead of being a key determinant of success, weather will simply be another variable in the overall risk management profile of an asset (in this case, a farm). Given the predictable productivity, risk management will be more about managing catastrophic outliers and, in some cases, sharing that risk with counterparties. For example, index-based insurance offers great potential in this area.

Real-time decision-making: Decisions will be made in the moment. With the growth of streaming data, farms will be analyzed as variables are collected and acted upon immediately. Issues will be remediated in 2020 faster than they will be identified in 2014. This is part of what drives the predictable productivity.

Production variability: Farms will no longer produce a single crop or focus on a subset. Instead, they will produce whatever will drive the greatest yield and productivity based on their pre-planting-season analysis. Farms will also begin to factor in external data sources (supply and demand) and optimize their asset for the products in greatest demand. This will completely change the variability that we see in commodities and food prices today.


As I left the headquarters of the agricultural company outside of San Francisco, I was amazed that a belief persists, in some places, that weather is the major force impacting our ability to grow consistent and productive crops. That does not seem much different from the pioneer farms of the 1800s, where the weather determined not only their business, but also their livelihoods.

Perhaps, as postulated before, that is the easy answer, as opposed to the real answer. The innovations that we’ve seen with precision farming, using data to transform potato crops, and the emergence of leaders like Monsanto, makes it evident that the weather is merely one variable that could impact crops in the future.

Data trumps weather. Farming and agriculture will be transformed by making the leap of acknowledging this truth.


Copyright 2014 Rob Thomas.
All Rights Reserved.

Thursday, September 11, 2014

Legendary Product Development

“Brand will not save you, marketing will not save you, and account control will not save you. It’s the products.”
– Marc Andreessen

I believe there is a recipe for winning in product development. It requires a delicate balance between pragmatism in planning, efficient execution, and the ability to see around corners (into the future). I’ve written this post to share some ideas on how to become legendary in product development.


Idea #1: Usage First

Products must be built with a ‘usage first’ mindset. Clients need to be attracted to products by their experience with the product. Clients should be begging for more, because they are so delighted with the experience and outcomes. If you build great products, clients will tell each other. The best way to make a product available for usage is through demos, freemium versions, downloads, and easy access via the cloud.

“The people with really great products never say they're great. They don't have to. Show, don't tell..” – Unknown

“In the old world, you devoted 30% of your time to building a great service and 70% of your time to shouting about it. In the new world, that inverts. If I build a great product or service, my customers will tell each other.” – Jeff Bezos

Idea #2: Simplicity and Design

Although this is related to Idea #1 and is in fact a pre-requisite to #1, it has some subtle differences. This is about tapping into how a client feels when they use your product. Do they find it shockingly simple, yet highly functional, leading to an ‘ah-hah’ moment? They should.

I read once that people don’t buy products; they buy better versions of themselves. When you’re trying to win customers, are you listing the attributes of a product or can you vividly describe how it will improve their lives? Clients will be attracted to the latter.

“Taking a design-centric approach to product development is becoming the default. Designers, at last, have their seat at the table.”- Unknown

Idea #3 Speed, Accountability, And Relentless Execution

Speed drives exponential improvements and outcomes in any organization. If you complete a task in 1 hour, instead of 1 day, your mean time to a positive outcome is 500% faster. In product development, accelerating cycle times is an under-estimated force in determining winners and losers.

Pixar has a company principle that states, “We start from the presumption that our people are talented and want to contribute. We accept that, without meaning to, our company is stifling that talent in myriad unseen ways. Finally, we try to identify those impediments and fix them. “

That principle really resonates with me. A product organization has to break down its own barriers, to achieve its potential.

“Life is like a ten speed bicycle. Most of us have gears we never use.” – Charles Schulz

Idea #4: Open Source

Open source is one the most important phenomena in enterprise software. Legendary product teams will shift their approach to an overt embrace and incorporation of open source into their product development processes. The best business model in software today is utilizing open source and effectively surrounding it with proprietary solutions and features. This drives the cycle time improvements alluded to above.

“There are no silver bullets for this, only lead bullets.” – Ben Horowitz

Idea #5: Product Management

Product management, and its interplay with development, is a critical function in a product organization. Development must work with product management to develop forward-looking, client-based insights, and use that insight to push clients faster than they may normally want to move. If you want to learn about product management and how product development should play a role, I recommend 2 things: 1) read every Amazon.com Annual Report and 2) read “Good Product Manager, Bad Product Manager” (you can find it on the web).

Great product organizations obsess over feedback and ideas from all constituents. They prefer feedback that challenges their views, instead of reinforcing their views. That enables you to reach the best answer as an organization.

“If you’re doing things right, something will always be a little bit broken.” - Unknown

Idea #6: D-Teams

I believe legendary product development teams need D-teams in the organization. The D stands for Disruption. The role of the D-teams is to disrupt from within. D-teams assess what the organization is working on, identify opportunities, rapidly assemble a team and disrupt. This type of competitive fire will makes the whole team better.

Idea #7: Resources
One of the most common refrains in every organization today is, “We don’t have enough resources.” Or, “We know what to do, but don’t have the time or money.” This is a choice, not an issue. If something does not have the right resourcing, it is because the organization is choosing that. If you are asking for resources and not getting them, its because you have not prepared a convincing argument. Sometimes, this means you have to “Take the Horse off The Chart”.

“Deciding what not to do, is as important as deciding what to do.” – Steve Jobs

Idea #8: Client Satisfaction

Quality is the taste you leave in a client’s mouth. Most organizations underestimate the negative impact of quality on their business. Its underestimated because it’s hard to quantify. Clients no longer have to buy inferior goods and services since information and alternatives are so easy to obtain. It’s that simple.

“What can a sales person say to somebody to get them to buy a product that they already use every day if they don’t like it? Nothing.” -Larry Ellison

Idea #9: Clients, Developers, and Users

Some product development organizations spend most of their time focused internally. Some take a reprieve from that and think about clients (which is great). But clients are only one of the three constituents that should drive thinking and behavior. Product development organizations will live and die by how they treat, communicate with, and interact with their constituents. They are:

1) Clients
2) Developers
3) Users

They are all equally important.

How do you make it easy for each of them to work with your products and with you? The organization should obsess over answering that question. With each new product idea, you must be able to articulate the “must have” experience and the target of that experience (clients, users, or developers), before debating how and why a product or feature would be useful. This requires a rigorous process for identifying the most passionate stakeholders and getting their unstructured feedback.

Idea #10: At the Service of the Sales Team

If a product development team spends all their time in the field, then they lose focus on developing outstanding products. On the other hand, a product development team cannot build outstanding products without an intimate understanding of clients, developers, and users. This is the paradox that every product development team faces. It is incumbent upon each team to figure out how to balance this, with a priority placed on being at the service of sales and constituents.

“The key is not spending time, but in investing it.’ –Stephen Covey

Idea #11: Innovation on the Edge

You cannot be a leader in innovation without dedicating resources to explore and try things that, by definition, are likely to fail. In strategy speak; this would be a Horizon 3 project.

There are many other areas to explore. Identifying the important waves to ride is important. It’s equally important to actually ride the wave (i.e. execute on it).

“If you only do things where you know the answer in advance, your company goes away.” –Jeff Bezos

Idea #12: Product Releases

Per Benedict Evans, there is a distinct pattern in Apple’s product releases and announcements. In almost every case, they are sure to have:

a) Cool, incremental improvements, which cater to existing users
b) ‘Tent-pole’ features, which become focus points for marketing campaigns
c) Fundamental strategic moves that widen the moat around their competitive advantage

This is a very thoughtful approach to product releases. Every organization can learn something from this.


Leading in product development is much more about culture, than it is about management and hierarchy. At times, management and hierarchy encumber product development teams. Sometimes the best way to understand how you need to change is by looking at companies or organizations on the other end of the spectrum. GitHub is one of those companies. GitHub has no managers. The sole focus of the organizational design is on developer productivity.

Steve Jobs once said, ‘you have to be run by ideas, not hierarchy.” There is latent talent and creativity in every development organization. Being Legendary is about finding a way to unleash that talent.

Wednesday, July 23, 2014

The Complete Product

William Davidow wrote Marketing High Technology in 1986. While we have seen many phases in technology since then, its a timeless piece of work on how to think about building great products. The fundamental message of the book is that a product development organization has to think about building a 'complete product', not a product. A product is something that a client can buy. Whereas, a 'complete product' addresses all the things around and related to the product: market fit, distribution channels, sales, service, marketing, and positioning.

His wisdom includes things like:

-Marketing must invent complete products and drive them to commanding positions in defensible market segments.
-The cost of creating a complete product is often many times the cost of developing the product.
-Serviceability must be designed into a product
-Great products make great salespeople.
-It's not a product without a distribution channel.
-Great products need a soul.
-Companies fail because they are incapable of delivering total customer satisfaction.

I believe in timeless advice. Davidow's work on a complete product certainly is.

Wednesday, July 16, 2014

Leadership in the Era of Distraction

Herman Melville wrote Moby Dick in 1851. It's a story about the whaling industry in the 19th century, capturing the intricacies of a life at sea. In one part of the book, Melville describes a lantern that hangs from the ceiling in the Captain's quarter. No matter how rough the seas are, that lantern stays perpendicular to the center of the earth. The lantern and it's inherent stability, reveals the faults of everything around it. It is the lone symbol of stability, always perpendicular to the earth. Leadership has to provide stability, in the current era of distraction.


Danny Meyer, the increasingly well known restaurateur (Gramercy Tavern, Union Square Cafe, and others), addresses the challenge with communicating consistent messages to his staff members, about his expectations for standards of excellence. He mentions that many of the waiters and managers in his restaurants are constantly testing him, as they push the limits of the standards he believes in. An excerpt from Meyer's book, 'Setting the Table':

"If you choose to get upset about this, you are missing the boat", Pat Cetta (Meyer's friend) noted. Pat pointed to the set table next to us. "First," he said, "I want you to take everything off that table except for the saltshaker. Go ahead! Get rid of the plates, the silverware, the napkins, even the pepper mill. I just want you to leave the saltshaker by itself in the middle." I did as he said, and he asked, "Where is the saltshaker now?"

"Right where you told me, in the center of the table."

"Are you sure that's where you want it?" I looked closely. The shaker was actually about a quarter inch off of center. "Go ahead. Put it where you really want it," he said. I moved it very slightly to what looked to be smack-dab in the center. As soon as I removed my hand, Pat pushed the saltshaker three inches off center.

"Now put it back where you want it," he said. I returned it to dead center. This time he moved the shaker another six inches off center, asking again, "Now where do you want it?"

I slid it back. Then he explained his point. 'Listen. Your staff and your guests are always moving your saltshaker off center. That's their job. It is the job of life. It's the law of entropy! Until you understand that, you're going to get pissed off every time someone moves the saltshaker off center. It is not your job to get upset. You just need to understand: that's what they do. Your job is just to move the shaker back each time and let them know exactly what you stand for. Let them know what excellence looks like to you.

Cetta is encouraging Meyer to provide the constant stability of the lantern on Melville's ship. And, he is suggesting that he accept the fact that there will always be instability around his attempts to do so.


A leader has to know where their center lies. They have to know it, talk about it, and never lose sight of it.

In our current era of distraction, where everyone is moving the saltshaker or being coaxed to do so, the only constant is the leader and their knowledge of what is important. The great leaders in this era, like the lantern in Melville's book, are stubbornly consistent, adhering to their center, despite the storms around them.

Wednesday, June 25, 2014

Acquisitions in Enterprise Technology

I've spent enough of my career in Mergers & Acquisitions in technology to have a sense for why companies, particularly in enterprise software, acquire (or choose not to). There are a variety of reasons that tend to have much more to do with the acquirer than the acquired company. (Note: most acquisition targets misunderstand this point)

There are typically 3 drivers of an acquisition in enterprise technology:

1) Revenue growth. Typically, a company will not acquire with this as a sole purpose. Because if the strategic fit is lacking, then the revenue will soon dissipate.

2) New Customers. An acquisition target could bring new clients to the acquirer, either in terms of the geography or buyer (think Chief Marketing Officer vs. Chief Information Officer)or industry.

3) Synergy with existing products. This means that the acquirer will have a broader opportunity to sell their existing products, due to the customers, footprint, or route to market from the acquired company. Note: this factor alone is typically most important in justifying an acquisition.

In my view, all three of these drives must exist for an acquisition to make sense. Number three is probably most important, followed by number two. The two of those together ensures that number one (revenue growth) can sustain itself. I rarely see enterprise acquisitions for the purpose of talent alone (i.e. acqui-hires).


This brings us to Oracle's recently announced acquisition of Micros Systems (MCRS). In their 10-K filing, Micros describes themselves as:

MICROS Systems, Inc. is a leading worldwide designer, manufacturer, marketer, and servicer of enterprise applications solutions for the global food and beverage, hotel and retail industries...Our enterprise application information solutions comprise three major areas: (1) food and beverage information systems, (2) hotel information systems, and (3) retail information systems. The food and beverage information systems consist of hardware and software for point-of-sale and operational applications, ecommerce, back office applications, including inventory, labor and financial management, gift cards, and certain centrally hosted enterprise applications.

Simplified, Micros is a combination of hardware and software, servicing the hospitality industry. Let's look at this versus the acquisition criteria I cited above:

1) Revenue growth. At $1.3B in revenue, Micros will increase Oracle's top line from $38B to $39.3B (~3%), even if Micros does not grow organically. So, it hits that check box.

2) New Customers. I'm skeptical this brings Oracle any new customers. The hospitality industry as typically used alot of Oracle database, and their acquisition of ATG awhile back filled out their retail penetration.

3) Synergy with existing products. I don't see any obvious synergy here, for the reasons I alluded to in #2.

It would appear that Oracle is buying Micros, simply for the top-line revenue growth. They only had to pay 4x revenue for Micros due to its poor relative profitability (50% gross margins vs. the 90% that Oracle is accustomed to on software).


I believe Oracle is trying to solve the revenue problem that is created by the opex vs. capex problem that I alluded to here. But, this is short sighted. To go back to where I started, I don't believe that an acquisition creates shareholder value, unless it checks the box on revenue growth, new customers, and product synergy. Then again, has Oracle every really cared?

It is interesting to note that what IBM is divesting (commodity hardware and retail store systems), Oracle is acquiring.