Do Pivots Matter?

                                                              There’s a sign on the wall but she wants to be sure
                                                           Cause you know sometimes words have two meanings
                                                                           Led Zeppelin – Stairway to Heaven

In late 2013 Cowboy Ventures did an analysis of U.S.-based tech companies started in the last 10 years, now valued at $1 billion. They found 39 of these companies.  They called them the “Unicorn Club.”

The article summarized 10 key learnings from the Unicorn club. Surprisingly one of the “learnings” said that, “…the “big pivot” after starting with a different initial product is an outlier. Nearly 90 percent of companies are working on their original product vision. The four “pivots” after a different initial product were all in consumer companies (Groupon, Instagram, Pinterest and Fab).”

One of my students sent me the article and asked, “What does this mean?”  Good question.

Since the Pivot is one of the core concepts of the Lean Startup I was puzzled. Could I be wrong? Is it possible Pivots really don’t matter if you want to be a Unicorn?

Short answer – almost all the Unicorns pivoted. The authors of the article didn’t understand what a Pivot was.

What’s a pivot?
A pivot is a fundamental insight of the Lean Startup. It says on day one, all you have in your new venture is a series of untested hypothesis. Therefore you need to get outside of your building and rapidly test all your assumptions. The odds are that one or more of your hypotheses will be wrong. When you discover your error, rather than firing executives and/or creating a crisis, you simply change the hypotheses.

What was lacking in the article was a clear definition of a Pivot.  A Pivot is not just changing the product. A pivot can change any of nine different things in your business model. A pivot may mean you changed your customer segment, your channel, revenue model/pricing, resources, activities, costs, partners, customer acquisition – lots of other things than just the product.

Definition: “A pivot is a substantive change to one or more of the 9 business model canvas components.”

Business Model
Ok, but what is a business model?

Think of a business model as a drawing that shows all the flows between the different parts of your company’s strategy. Unlike an organization chart, which is a diagram of how  job positions and  functions of a company are related, a business model diagrams how a company makes money – without having to go into the complex details of all its strategy, processes, units, rules, hierarchies, workflows, and systems.

Alexander Osterwalder’s  Business Model canvas puts all the complicated strategies of your business in one simple diagram. Each of the 9 boxes in the canvas specifies details of your company’s strategy.  (The Business Model Canvas is one of the three components of the Lean Startup. See the HBR article here.)

So to answer my students question, I pointed out that the author of the article had too narrow a definition of what a pivot meant. If you went back and analyzed how many Unicorns pivoted on any of the 9 business model components you’d likely find that the majority did so.

Take a look at the Unicorn club and think about the changes in customer segments, revenue, pricing, channels, all those companies have made since they began: Facebook, LinkedIn – new customer segments, Meraki – new revenue models, new customer segments, Yelp – product pivot, etc. – then you’ll understand the power of the Pivot.

Lessons Learned

  • A Pivot is not just when you change the product
  • A pivot is a substantive change to one or more of the 9 business model canvascomponents
  • Almost all startups pivot on some part of their business model after founding
  • Startups focused on just product Pivots will limited their strategic choices – it’s like bringing a knife to a gunfight

About Steve Blank

Entrepreneur-turned-educator Steve Blank is credited with launching the Lean Startup movement. He’s changed how startups are built; how entrepreneurship is taught; how science is commercialized, and how companies and the government innovate. Steve is the author of The Four Steps to the Epiphany, The Startup Owner’s Manual -- and his May 2013 Harvard Business Review cover story defined the Lean Startup movement.  He teaches at Stanford, Columbia, Berkeley and NYU; and created the National Science Foundation Innovation Corps -- now the standard for science commercialization in the U.S. His Hacking for Defense class at Stanford is revolutionizing how the U.S. defense and intelligence community can deploy innovation with speed and urgency, and its sister class, Hacking for Diplomacy, is doing the same for foreign affairs challenges managed by the U.S. State Department. Steve blogs at www.steveblank.com.

Strategy is Not a To Do List

I had breakfast with two of my ex-students from Singapore who were building a really interesting startup. They were deep into Customer Discovery and presented a ton of customer data on the validity of their initial hypothesis – target customers, pricing, stickiness, etc. I was unprepared for what they said next. “We’re going to do a big launch of our product in three weeks.” I almost dropped my coffee. “Wait a minute, what about the rest of Customer Development? Aren’t you going to validate your hypotheses by first getting some customers?”

Without any sense of irony they said, “Oh, our investors convinced us to skip that part, because our customer feedback was all over the map and our schedule showed us launching in three weeks and they were worried that we’d run out of cash. They told us to stay on schedule.” Now I was confused, and I asked, “Well what do you guys believe – Customer Development or launch on a schedule?” Without missing a beat they said, “Oh, we believe both are right.”

I realized I was listening to them treat Customer Development as an item on their To Do list.

Suddenly, I had a massive case of déjà vu.

Can You Pull This Off
I was VP of marketing at Ardent, a supercomputer company where a year earlier I had a painful and permanent lesson about Customer Discovery. I was smart, aggressive, young and a very tactical marketer who really hadn’t a clue about what strategy actually meant.

One day the CEO called me into his office and asked, “Steve I’ve been thinking about this as our strategy going forward. What do you think?” And he proceeded to lay out a fairly complex and innovative sales and marketing strategy for our next 18 months. “Yeah, that sounds great,” I said. He nodded and then offered up, “Well what do you think of this other strategy?” I listened intently as he spun an equally complex alternative strategy. “Can you pull both of these off?” he asked looking right at me. By the angelic look on his face I should have known that I was being set up. I replied naively, “Sure, I’ll get right on it.”

Ambushed
25 years later I still remember what happened next. All of sudden the air temperature in the room dropped by about 40 degrees. Out of nowhere the CEO started screaming at me, “You stupid x?!x. These strategies are mutually exclusive. Executing both of them would put us out of business. You don’t have a clue about what the purpose of marketing is because all you are doing is executing a series of tasks like they’re like a big To Do list. Without understanding why you’re doing them, you’re dangerous as the VP of Marketing, in fact you’re just a glorified head of marketing communications.”

I left in daze angry and confused. There was no doubt my boss was a jerk, but unlike the other time I got my butt kicked, I didn’t immediately understand the point. I was a great marketer. I was getting feedback from customers, and I’d pass on every list of what customers wanted to engineering and tell them that’s the features our customers needed. I could implement any marketing plan sales handed to me regardless of how complex. In fact I was implementing three different ones. Oh…hmm… perhaps I was missing something.

I was doing a lot of marketing “things” but why was I doing them? I had approached my activities as simply as a task-list to get through. With my tail between my legs I was left to ponder; what was the function of marketing in a startup?

Strategy is Not a To Do List, It Drives a To Do List
It took me awhile, but I began to realize that the strategic part of my job was two-fold. First, (in today’s jargon) we were still searching for a scalable and repeatable business model. My job was to test our hypotheses about who were potential customers, what problems they had and what their needs were. Second, when we found these customers, marketing’s job was to put together the tactical marketing programs (ads, pr, tradeshows, white papers, data sheets) to drive end user demand into our direct sales channel and to educate our channel about how to sell our product.

Once I understood the strategy, the To Do list became clear. It allowed me to prioritize what I did, when I did it and instantly understand what would be mutually exclusive.

Good Luck and Thanks For the Fish
My students were going through the motions of Customer Development rather than understanding the purpose behind it. It was trendy, they had read my book and to them it was just another step on the list of things they had to do. They had no deep understanding of why they were doing it. So they were at a crossroads. Since their investors had asked them to launch now, what happened if their initial assumptions were wrong?

As they left I hoped they would be really lucky.

Lessons Learned

  • Entrepreneurs get lots of great advice.
  • Most of it is mutually exclusive.
  • Don’t do it if you can’t explain why you’re doing it.
  • Or else it all becomes a To Do list.

About Steve Blank

Entrepreneur-turned-educator Steve Blank is credited with launching the Lean Startup movement. He’s changed how startups are built; how entrepreneurship is taught; how science is commercialized, and how companies and the government innovate. Steve is the author of The Four Steps to the Epiphany, The Startup Owner’s Manual -- and his May 2013 Harvard Business Review cover story defined the Lean Startup movement.  He teaches at Stanford, Columbia, Berkeley and NYU; and created the National Science Foundation Innovation Corps -- now the standard for science commercialization in the U.S. His Hacking for Defense class at Stanford is revolutionizing how the U.S. defense and intelligence community can deploy innovation with speed and urgency, and its sister class, Hacking for Diplomacy, is doing the same for foreign affairs challenges managed by the U.S. State Department. Steve blogs at www.steveblank.com.

Funding Basics: Customer Development

Entrepreneurs take note. More startups fail from a lack of customers than from a failure of product development. That’s why I believe strongly that every new product company should have a methodology for developing customers.

I’m a proponent of Steve Blank’s startup stack methodology for customer development, which features the following steps:

  • Customer Discovery – Begin with a business model canvas, a summary of how you’re going to serve customers and earn money

  • Customer Validation – Make assumptions, then test them to develop a repeatable and scalable sales process

  • Execution –  Fine tune your model to get to a market fit that is tight and profitable; pivot, as needed

As an Alchemist Accelerator mentor, I recently had an opportunity to share some perspective about the customer development process and how to maximize success. The first thing I told the group in front of me—a large percentage of whom were engineers—was that they should focus everything on finding the right customer segment, rather than building or modifying a new product concept to fit initial discussions. I think I heard a collective sigh of relief before I began my presentation.

Completing Your Canvas

Research has proven effective customer discovery begins with a business model canvas, so the first part of our discussion, framed in that context was designed for them to hear one thing: You are making a best-guess at first. There will be plenty of time for refinement, when you know more.

A strategic management and lean startup template, your canvas should reflect initial assumptions. To begin, you must understand the market you’re targeting—total addressable, served available, and/or target market. You’ll also need to define the type of market you’re hoping to penetrate. Is it existing with incumbents, but a known problem; new with no competition, but steep education requirements; re-segmented where you’re offering a lower cost or niche alternative; or are you cloning a concept from somewhere else?

Your canvas should also identify key value propositions. What is the job your customers are hiring you to do? How will you do it, and most important, what one-to-three benefits will customers get from using your product or service?

In the customer relationships section of your canvas, you’ll need to outline how you plan to

  • Get customers

  • Keep customers

  • Grow customers

In addition, your canvas should highlight any other key activities, resources (e.g. required equipment), partners and costs (fixed and variable), as well as your anticipated revenue model (e.g., one-time scale, subscription, etc.).

Finding Your Fit

A completed business model canvas ensures your team has fully immersed itself in the customer problem. As such, it can serve as a foundation as you define tests for customer validation.

Testing can begin once you’ve identified subjects. Who are they—end users, influencers, recommenders, decision makers, or others? What do they do all day, and can you create an organizational or influencer map around them? Plus, don’t forget to acknowledge any saboteurs because they have no interest in your success.   

Next, only founders should conduct customer validation meetings, and they should be face-to-face for added visual cues. Don’t outsource the job. Ask open-ended questions and avoid trying to convince someone he or she needs your solution. Test your theories to determine if you’re on the right track. If you don’t get a good signal, reframe the problem. Test again.

In general, ask questions that help you learn more. Lead with

  • Tell me more about…

  • What do you mean by…

  • How so…

  • Why is that…

  • What are your thoughts on…

  • How would you quantify…

  • How did you measure…

  • How did you come up with that…

  • What was your thinking behind…

The goal of every customer validation meeting should be the same: To understand the problem space and the current solutions available.

Pivoting and Execution

During customer validation, your team may uncover some startling truths. Your product doesn’t fit the market it was intended to serve. Prospects already have a solution for x, but have you considered this other opportunity, y? Do not panic.

Instead, apply your development methodology to your customer discovery process. Be agile. Don’t build a new product. Find a new set of customers. Pivot into a new space and test again.

By following a customer development process, you have a tremendous opportunity to deliver what people will pay for, improving your product along the way. Moreover, you’ll have high-quality data to answer the question “who is your customer?” when potential investors ask.

About Alan Chiu

Alan Chiu is a Partner at XSeed Capital, with a strong background in enterprise software startups. His investment areas include mobile enterprise applications, data analytics platforms, enterprise infrastructure, and fintech startups. He serves on the Board of Directors of Breakaway and previously served on the board of StackStorm (acquired by Brocade – NASDAQ:BRCD). He has provided support to other portfolio companies including Lex Machina (acquired by LexisNexis of the RELX Group – NYSE:RELX), AtScale, Dispatcher, Teapot (acquired by Stripe), Pixlee, SIPX (acquired by ProQuest), Zooz, BrainofT, Mines.io, Inklo, and My90. Alan is currently Co-President for Stanford Angels & Entrepreneurs, an alumni association that seeks to strengthen Stanford’s startup community by fostering relationships among entrepreneurs and alumni investors.

About the Alchemist Accelerator

Alchemist is a venture-backed initiative focused on accelerating the development of seed-stage ventures that monetize from enterprises (not consumers). The accelerator’s primary screening criteria is on teams, with primacy placed on having distinctive technical co-founders. We give companies around $36K, and run them through a structured 6-month program heavily focused on sales, customer development, and fundraising. Our backers include many of the top corporate and VC funds in the Valley -- including Khosla Ventures, DFJ, Cisco, and Salesforce, among others. CB Insights has rated Alchemist the top program based on median funding rates of its grads (YC was #2), and Alchemist is perennially in the top of various Accelerator rankings. The accelerator seeds around 75 enterprise-monetizing ventures / year. Learn more about applying today.

This blog is the second in a financing series with topics designed to help entrepreneurs be better prepared for venture capital conversations.

Funding Basics: Adopting the Best Business Model

The culture of nearly every business-to-business software startup centers on products. Everyone talks about product innovation and disruptive technology, but I think today’s founders need more than great product ideas to launch successful companies.

In my role as Managing Director of Hummer Winblad and also as an Alchemist Accelerator mentor, I share this advice with new entrepreneurs: Get as comfortable with your spreadsheets as you are with your product. By that I mean that your financial models show potential investors you’ll be a metrics-driven organization and that you understand you are building a business not just a product. I also believe that only metrics-driven companies can operate high-velocity business models.

A New, Emerging Approach

If success is 10 percent idea and 90 percent execution, deep thinking is required of teams pulling together new business models. For example, are you going to sell direct or through a channel?  Will you have a subscription or a perpetual model? Do you envision a “land and expand” model where you encourage a smaller, initial buy that increases over time? Does your business model reflect the way customers want to buy?

Teams developing enterprise software traditionally have had to factor in a 9-to-12-month sales cycle on top of the year or more it takes to deliver product. Both development and expensive sales professionals operating in this model require significant runway—and thus funding.

Fortunately, times are changing.

Taking a cue from evolving consumer models, I now encourage enterprise software founders to more precisely consider cost of sales (including customer acquisition costs relative to pricing and hiring) together with product decisions.

Our team members and other venture firms ask them to think about how they can achieve operational and growth targets from two perspectives:

  • The old model – Costly, large account-focused, in-person sales teams operating on a quarterly rhythm

  • The new model – High-velocity, mid-market-focused, inside sales teams operating on a weekly rhythm

The new, high-velocity model optimizes sales and marketing processes by measuring the end-to-end effectiveness of all touchpoints. With metrics, teams can determine what is and what isn’t delivering results. I created two blog posts a few years ago explaining the high-velocity business model and the metrics for a high-velocity business model—based on the success of teams that Hummer Winblad invested in early.

High-Velocity Benefits

For a startup pricing products in the USD$150,000 and up range, leveraging the traditional, enterprise sales model may still be practical and even preferred. For everyone else, here’s why a high-velocity model makes more sense:

  • Faster time to revenue – The combination of an assertive inside sales professional (who can reach 80 to 100 prospects a day) and a web purchasing model speeds sales, which enables the company to run on monthly recurring revenue.

  • Greater accountability – When your product team’s responsibilities expand beyond building the solution to the entire lifecycle (from first customer touch to download to using), teams are more collaborative and can achieve greater success faster.

  • Complete visibility – Companies operating high-velocity models are highly automated and instrumented, so individuals and teams are always aware of their goals and progress toward reaching them—from calls and demos to trials, seats, and monthly volumes.

Does Your Business Have the DNA?

In a high-velocity business model, leadership, product, sales and marketing teams all shoulder responsibility for success. We see entrepreneurs embracing this new approach taking a similar journey, learning from others that have succeeded already about how to ramp up fast.

My tips for them include the following:

  1. Hire consumer experts to run your enterprise marketing model, so it’s firing on all cylinders

  2. Simplify the sales process by adding a free or low-cost download feature

  3. Add insides sales professionals to follow up on every lead and upsell from the download

  4. Run everyone in the company through your sales process—from start to finish—to ensure everyone understands it

  5. Test online pricing and trial models by dividing traffic

  6. Test your social media and web flows, counting the number of clicks at each step

  7. If you choose to work with channels, hire someone that has previously built them

  8. Bet on mid-market customers to start, but establish a sales value that when exceeded, makes sense to add enterprise sales

For founding teams seeking funding, business models matter. Remember your ability to explain the thinking behind your business model is as important as explaining the product you’re going to bring to market—and sometimes, more important.

About Me

As Managing Director at Hummer Winblad, I oversee investments in SaaS, virtualization, cloud and mobile technologies. Prior to joining Hummer Winblad Venture Partners in 2006, I was involved in founding and operational roles at start-up companies. I was a co-founder of AutoFarm (now Novariant), a company focused on GPS and robotics. Although I spend less time programming now, I started my technical career coding and hacking computer games. I have a Master of Science (Engineering) degree from Stanford University, an M.B.A. from the Stanford Graduate School of Business, and an Engineering Physics degree from Queen’s University.

About the Alchemist Accelerator

Alchemist is a venture-backed initiative focused on accelerating the development of seed-stage ventures that monetize from enterprises (not consumers). The accelerator’s primary screening criteria is on teams, with primacy placed on having distinctive technical co-founders. We give companies around $36K, and run them through a structured 6-month program heavily focused on sales, customer development, and fundraising. Our backers include many of the top corporate and VC funds in the Valley -- including Khosla Ventures, DFJ, Cisco, and Salesforce, among others. CB Insights has rated Alchemist the top program based on median funding rates of its grads (YC was #2), and Alchemist is perennially in the top of various Accelerator rankings. The accelerator seeds around 75 enterprise-monetizing ventures / year. Learn more about applying today.

This blog is the first in a financing series with topics designed to help entrepreneurs be better prepared for venture capital conversations.

Not BI, AI

A product business can double its revenue and quadruple its margins by moving to a service business. What is service? It's information, personal and relevant to you.  

Amazon delivers information that is personal and relevant to you, for example, with its recommendations: customers like you bought this book, or customers like you like this music. Now think about your favorite banking site and log in. I will contend that there’s very little personal and relevant information. The only reason you’re being asked to log in is for security reasons. After that you are really looking at a big shopping cart to move money from savings to checking, buy stocks, sell a bond, etc. 

Could the bank deliver information that’s personal or relevant to you? Could they say that people like you bought this stock, or people like you re-financed their mortgage? Yes, they could, so why don’t they? Well, you probably never thought about this, but the consumer Internet that Google and Bing let you see through search is believed to only be about 100 or 200 terabytes. That’s it. Now, I’ll guarantee your current IT systems have 10, 100, or 1,000 times that amount of information; so why can’t they deliver information that is personal and relevant to you? Well, I say they are held hostage by the SQL monster. So let’s just have a little fun here.

It’s the late ‘90s and I have several SQL engineers in the room. I come in with a brilliant business idea. My idea is that we are going to index the consumer Internet and we’re going to monetize it with ads. We’re going to be billionaires! Just guess what the SQL engineers would do?

The first thing they’re going to do is design a master, global-data schema to index all information on the planet. The second thing they’re going to do is write ETL and data cleansing tools to import all that information into this master, global-data schema. And the last thing they are going to do is write reports, for instance, the best place to camp in France or great places to eat in San Francisco.

Any of you who are technical are probably laughing right now thinking, “Well that’s a completely stupid thing to do.” But if you try and attack the problem using SQL and BI tools, you’re also going to fail.  

Furthermore, as you connect your machines, you have the opportunity to bring in large amounts of time-series data. Modern wind turbines have 500 sensors and the ability to transmit those sensor readings once a second. Most analytic techniques depend on the idea that the data scientist can try and visualize the data, but how is that possible if I have a 1,000 wind turbines and data for 12, 24 or 36 months?  How can we learn from that?

Artificial Intelligence (AI) has been increasingly in the news. Google’s DeepMind made headlines when the machine, AlphaGo, programmed to play Go, defeated Lee Sedol, one of the best players in the world, by 4 - 1. Amazon’s Echo and voice assistant Alexa is being widely praised for its voice recognition capabilities, and many people remember how Watson handily beat the best Jeopardy players in the world.

Things have been changing quickly and here is a great example. ImageNet is a database of millions of images. Beginning in 2010 the ImageNet Challenge was established to see how well a machine would do at object recognition. As a point of reference an average person will be able to achieve 95% accuracy. In 2010, the winning machine could correctly label an image 72% of the time. By 2012, accuracy had improved to 85%, and in 2015 the machine achieved 96% accuracy.

So why have things been changing so quickly?

First, we’re continuing to get more computing and more storage for lower and lower prices. Next generation compute and storage cloud services can provide thousands of computers for an hour or a day. AI and machine learning software require lots of computing during the learning phase. The second reason is the emergence of neural network algorithms. Third, it’s not possible to apply these advanced AI technologies without data, and lots of it. Consumer Internet companies like Facebook are able to use billions of photos to train facial recognition systems. AlphaGo learned from millions of games of Go and Alexa learned from millions of voice patterns.

While we’ll continue to see progress in replicating what humans do, we have the opportunity to apply these AI technologies to even more important challenges. Today, many of the machines that generate electricity, transport goods, farm food, or sequence genes have large amounts of data. If we were able to connect these machines and collect the sensor data from them, we would have the opportunity to use AI and machine learning technologies to operate a more precise planet. Imagine a future farm that can use fewer pesticides, which not only reduces the cost of the food, but also makes it healthier. A future power utility could be based on a vast array of solar panels, wind turbines, small hydro generators and batteries to generate more power, much more efficiently. A pediatric hospital could share the results of millions of MRI scans and diagnose patients far faster.

Next-generation machine companies could not only double their revenues and quadruple their margins, but build a better planet in the process.

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Timothy Chou, Ph.D.

Timothy Chou has lectured at Stanford University for over twenty-five years and is the Alchemist Accelerator IoT Chair.  Not only does he have academic credentials, but also he's served as President of Oracle's cloud business and today is a board member at both Blackbaud and Teradata. He began his career at one of the first Kleiner Perkins startups, Tandem Computers, and today is working with several Silicon Valley startups including as the Executive Chairman of Lecida, which is building precision assistants for the IoT using AI technologies. Timothy has published a few landmark books including, The End of Software, and Precision: Principals, Practices and Solutions for the Internet of Things, which was recently named one of the top ten books for CIOs.  He's lectured at over twenty universities and delivered keynotes on all six continents.

Service is Not Break-Fix

As a student of business, you may have come to realize that with a recurring-service-revenue business, you can not only double the revenues of the company, but also quadruple the margins. I recently spoke with an executive of a large European company who has a 50/50 business; 50% of their revenue is selling machines and 50% is service on those machines. He said, “In 2008 our revenues went down, but our margins went up.”

But what is service? Is it answering the phone nicely from Bangalore? Is it flipping burgers at McDonald’s? No. Service is the delivery of information that is personal and relevant to you. That could be the hotel concierge giving you directions to the best Szechuan Chinese restaurant in town, or your doctor telling you that, based on your genome and lifestyle, you should be on a specific medication. Service is personal and relevant information.

I’ve heard many executives of companies that make machines say, “Our customers won’t pay for service.” Well of course, if you think that service is just fixing broken things, then your customers will think you should be building a more reliable product.

Service is information. In 2004, the Oracle Support organization studied 100 million support requests and found that over 99.9% of them had been answered with already known information.

Aggregating information for thousands of different uses of the software, even in a disconnected state, represents huge value over the knowledge of a single person in a single location. Real service is not break-fix, but rather information about how to maintain or optimize the availability, performance or security of the product.

Above is my Amazon home page. Every time you log in, Amazon attempts to deliver information that is personal and relevant to you. For instance, people like you bought this book. If you look closely at the image, you might guess who uses my Amazon account. Now, let’s point something else out, namely the little shopping cart in the upper right hand corner. That’s the transactions processing system. It has to operate securely with scalability, but how important is it?  Not very.  Instead, most of the real estate of the page, and therefore of the company, is dedicated to delivering information that is personal and relevant.  

Service is information.

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Timothy Chou, Ph.D.

Timothy Chou has lectured at Stanford University for over twenty-five years and is the Alchemist Accelerator IoT Chair.  Not only does he have academic credentials, but also he's served as President of Oracle's cloud business and today is a board member at both Blackbaud and Teradata. He began his career at one of the first Kleiner Perkins startups, Tandem Computers, and today is working with several Silicon Valley startups in roles from investor to executive chairman. Timothy has published a few landmark books including, The End of Software, and Precision: Principals, Practices and Solutions for the Internet of Things, which was recently named one of the top ten books for CIOs.  He's lectured at over twenty universities and delivered keynotes on all six continents.

Not Machines, It’s the Service

If your company builds agricultural, power, construction, healthcare, oil, gas or mining machines you’ve probably heard about the Internet of Things.  All of us in the tech community are excited to tell you about our cool technology to run on your machine, connect it to the Internet, collect data from it, and then make predictions from that data using advanced machine learning technology.

But maybe the question you’re asking as the CEO of one of these companies is why should I care?  Isn’t this just stuff my geeky R&D staff cares about? How can it be meaningful to my business?  

I’ll be making the case that with IoT software; you can not only double the size of your business but also create a barrier that your competition will find difficult to cross.

Next generation machines are increasingly powered by software.  Porsche’s latest Panamera has 100 million lines of code (a measure of the amount of software) up from only 2 million lines in the previous generation.  Tesla owners have come to expect new features delivered through software updates to their vehicles.  Healthcare machines are also becoming more software defined. A drug-infusion pump may have more than 200,000 lines of code and an MRI scanner more than 7,000,000 lines. On a construction site a modern boom lift has 40 sensors and 3,000,000 lines of code and on the farm a combine-harvester has over 5,000,000 lines of code.  Of course we can debate if this is a good measure of software, but I think you get the point.  Software is beginning to define machines.

So if machines are becoming more software defined, then maybe the business models that applied to the world of software will also apply to the world of machines. Early in the software product industry we created products and sold them on a CD; if you wanted the next product, you’d have to buy the next CD. As software products became more complex, companies like Oracle moved to a business model where you bought the product (e.g. ERP or database) together with a service contract. That service contract was priced at a derivative of the product purchase price. Over time, this became the largest and most profitable component of many enterprise software product companies.  In the year before Oracle bought Sun (whilst they were still a pure software business) they had revenues of approximately $15B, only $3B of which was product revenue, the other $12B, over 80%, was high margin, recurring service revenue.

In the world of machines, you might wonder why General Electric is running ads on Saturday Night Live talking about the Industrial Internet.  Why are they doing this?  All you need to do is download the 2016 10-K (http://www.ge.com/ar2016/assets/pdf/GE_2016_Form_10K.pdf) and look on page 36.  Out of $113B in revenue they recognized $52B, or nearly 50%, as service revenue.  Imagine if GE could move to 80% service revenue, not only would the company be tens of billions of dollars larger, but also margins for the overall business could easily double. And let me remind you this is all done without connecting the product (software or machine).  Once connecte you can provide even more service and ultimately deliver your product as a service.  As we have already seen in high tech software and hardware moving to product-as-a-service is transformative.

So if you’re an executive at a power, transportation, construction, agriculture, oil & gas, life science, or healthcare machine company, how big is your service business?

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Timothy Chou, Ph.D.

Timothy Chou has lectured at Stanford University for over twenty-five years and is the Alchemist Accelerator IoT Chair.  Not only does he have academic credentials, but also he's served as President of Oracle's cloud business and today is a board member at both Blackbaud and Teradata. He began his career at one of the first Kleiner Perkins startups, Tandem Computers, and today is working with several Silicon Valley startups in roles from investor to executive chairman. Timothy has published a few landmark books including, The End of Software, and Precision: Principals, Practices and Solutions for the Internet of Things, which was recently named one of the top ten books for CIOs.  He's lectured at over twenty universities and delivered keynotes on all six continents.


CANDID CONVOS: Angel Fundraising with Ahryun Moon, CEO at Goodtime.io

Introduction


 Ahryun Moon is CEO and Co-founder at GoodTime.io, a recruiting enablement platform that automates interview scheduling for companies like Airbnb, Stripe, Yelp, Thumbtack and more. She is a financial professional turned engineer! She taught herself how to code while building her first enterprise software at Freescale Semiconductor, Inc., at which time she was a financial analyst. The software got adopted company wide.

Some interesting things about her:

1. She caught a thief using Twitter (check out http://bit.ly/2gmr5P4) - gone viral on Hacker News, Reddit, Facebook, Twitter and Youtube

2. Her team at GoodTime.io won 3 hackathons - Salesforce $1M, Toyota and Launch hackathons

3. Her team built Etch Keyboard which was featured on the App Store for 3 weeks.

4. She still has a CPA license in good standing


The Convo


Interviewer (ZP): What was the size of your first check?

Ahryun Moon (AM): $100 was the first check. What happened was right before Alchemist, I was down and depressed and going to a bunch of people asking for advice and feedback and money. I then went to Edith and she, after hearing me out, said, “Hey I'll be your first investor, here's your hundred dollar check. You can put me on Angel list.” With investors the very first check is important so you can put someone's name on your angellist. That’s hard to get. The very first person that wants to be on your investor roster is always challenging. She said to just use her name she’d give us the one hundred dollars. I have kept our hundred dollars even today. So that $100 is still on my cap table, as I really love the fact that she believed in me when no one did. So my first check was $100, and then the second check was 10k.

ZP: What about the first check over 25k or more?

AM: Oh 25k or more. The first time that a check was larger than 25K was 50k.

ZP: And when was the closing date you received it.

AM: We closed the check on the day of the demo day.

ZP: And it was just that simple?.

AM: He came up to me and said he was just ready to write the check.

ZP: What industry is your company in.

AM: HR and Recruiting.

ZP: Tell me about the process of closing that check and from start to finish. How you were introduced all the way through to actually having a check in hand or money in the bank.

AM: For the 50k check, he was in the audience at the demo day. He loved it. He came up to us and he was literally ready to write the check. I think we got the check within a few days or a week or so. He didn't have any other references. He just saw us at demo day and liked us. Sometimes you can really run into someone that just believes in you and gives you unconditional love for the product that you're making. So I am lucky with that. But I think you just get lucky sometimes.

ZP: So what was it like doing that to the first 10k check.

AM: The 10k check was when we were going negative, negative, negative, and we were about to break our 401k. It was one of the Alchemist Mentors and he liked our product from the beginning. We were so afraid of asking for money at the time.

ZP: How did you meet him?

AM: He was one of the mentors that we paired up with at one of the events, the CEO mentor event. We did speed dating, he was one of the three people there we met. He liked the idea and we never asked for money. We didn't know to ask for money at the time. We invited him over to our office and we talked for another hour or so after the event. That was after a month or two after we met for the first time. And then we mentioned, “Hey we are looking for investors”. And he simply said “How much”. We told him we were looking for 10k. And he's said, “OK. I don't have a check with me. I'll wire you the money as soon as I get back to my office.” He wired it within a few days.

ZP: Wow. Was there any back and forth between you or was it pretty straightforward?

AM: It was really straightforward. People who argue with you and nitpick on this or that and say “I want to see more proof”, they never work out. Investors that ended up giving us money, you can tell from the first meeting that they believe in you and will give you support. So I'll say my advice is this: it's the ones that give you bullshit excuses and say you’re too early, you're too late in the stage, you're pre-revenue you or your team is too small, move on to the next person. They will not give you money. They never gave me any money. People who said those things never gave me money.

ZP: Those things were just an afterthought when they just believe you.

AM: Yes. I think I took them extremely personally in the beginning and that made me really, really depressed. Whenever I get that kind of excuse next time I wouldn't too depressed. I will just say, “Ok fine. Next person.”

ZP: Is there anything else you'd like to share? Maybe something that stuck out with a new kind of angel fundraising process in general or specifically with all the checks that you're trying to close.

AM: Yeah. Everyone told me not to cold email. Everyone told me not to cold call investors. But I did. I closed our last 100k check with a cold call. So I wouldn't say cold calling is the worst thing you can do. Once you run out of referrals you have to cold call and sometimes you really meet the right person while doing that. So I would not advise against cold calling.

ZP: That's good advice. cold call. OK. Well that's really good thank you.

PRESS RELEASE: ALCHEMIST ACCELERATOR ADDS JUNIPER NETWORKS AS BACKER

Contact: Danielle D’Agostaro                                                                                                   RELEASE: May 23, 2017

Email: danielle@alchemistaccelerator.com


                                     ALCHEMIST ACCELERATOR ADDS JUNIPER NETWORKS AS BACKER

                             Juniper Networks Joins Alchemist Accelerator’s Second Round Fund as Backer


San Francisco, May 23, 2017 – Alchemist Accelerator, an accelerator dedicated to enterprise start-ups, today announced that Juniper Networks has joined Analog Devices, Cisco, Ericsson, GE, and Johnson Controls as a backer in the accelerator’s second fund. This brings the total fund to $6.5 million.

Alchemist Accelerator is a six-month program, accepting about 20 companies every four months. On average, accepted companies receive $36,000 in seed funding. Alchemist structures the program around mentorship, sales and fundraising to help early-stage companies raise their seed or series A round and secure their first few customers.

Many founders who have gone through the program would agree that a major perk of joining Alchemist comes from the large network of high-caliber experts and coaches who mentor Alchemist founders.

“We are thrilled to have Juniper Networks join as a backer of Alchemist. Few companies think as deeply about next gen trends in AI, cloud, analytics, and networking – all core areas to Alchemist – as Juniper does. We are excited to have Juniper join the Alchemist family,” said Ravi Belani, Founder and Managing Director of Alchemist.

Since the debut of Alchemist’s first class in January 2013, 14 Alchemist companies have been acquired (including Cisco’s acquisition of Assemblage and Dropbox’s acquisition of Mobilespan). More than 50 percent of its graduates have gone on to raise significant seed or institutional funding rounds. The average raise of these companies is $2.6 million. Many of these are from the top venture capital firms in the valley, including Andreessen Horowitz, Bessemer Venture Partners, Draper Fisher Jurvetson, Foundation Capital, Founders Fund, Greylock Ventures, Menlo Ventures, Redpoint Ventures, Social + Capital Partnership and True Ventures. The complete list is provided here.

“At Juniper Networks, we believe that venture investment is an integral part of our innovation engine. Alchemist fills a gap in our portfolio strategy, acting as a vehicle to invest in seed-stage companies, a stage we are eager to participate in,” said Rita Waite, Investment Manager at Juniper Networks. “We are thrilled to be joining Alchemist Accelerator as a backer and look forward to working with Alchemist start-ups and its network.”

Today, Alchemist held its 15th Demo Day at Juniper Networks in Sunnyvale in conjunction with the announcement. They were joined by more than 200 customers, partners and investors. The event debuted 18 companies.

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Learn More

Anyone interested in getting involved as a mentor, investor or customer or members of the press, should fill out this form: https://vault.alchemistaccelerator.com/register-profile.

For more information on the accelerator, please visit http://www.alchemistaccelerator.com/.

About Alchemist Accelerator
The Alchemist Accelerator is a new venture-backed initiative focused on accelerating the development of seed-stage ventures that monetize from enterprises (not consumers). The accelerator’s primary screening criteria is on teams, with primacy placed on having distinctive technical co-founders. The accelerator seeds around 60 enterprise-monetizing ventures / year. Over 50% close institutional rounds within 12 months of their Alchemist Demo Day[LM1] . 


 [LM1]I removed our boiler plate and media contacts. This is a third party release distributed by Alchemist without our ticker or a classified joint release.