Data Intelligence, Cognitive Bias, and Emerging Tech
You don’t always realize at the moment of a new technology’s introduction that it was designed to take your job.
I remember my early career working as an analyst grunt on Wall Street. To learn my job, I would compete with other analysts on a fun game called merger practice. We’d be expected to create a fully merged Profit and Loss statement for two merged companies in 15 minutes, or less.
I had to work between machines. I’d look at the Bloomberg terminal’s company data, piped real time through some sort of non-Internet based system. I’d toggle my head over to my PC, where I’d copy the numbers into Excel to show how two companies would merge together. We’d issue reports fast, faster than other analysts. That was our edge.
Then one day, it was all connected. Market data piped right into Microsoft Excel. It was a true human-centered achievement. Hooray. Time saved. Lives better. I no longer had cramps from all of that neck rotating.
In fact, soon I would not be needed. Who needs a grunt to merge companies fast when that can now be done with a button?
I was lucky. I self-selected out of Wall Street and found myself in more creative and swashbuckling environments like tech startups and design firms and then my own companies after that. I do business modeling for a living, but insist on all of the fuzzy work that needs to happen with humans before we make spreadsheets. I stayed just ahead enough of technology to keep me from being replaced by a button.
Just this week, I saw some tech that called me back to those analyst days, and made me hopeful for data analysts, everywhere.
At Strata, everyone is an amateur behavioral economist. Humans have bias. Humans aren’t rational. Humans also don’t scale as fast as machines. In the tutorials and main stage shows, everyone is trying to learn how to use the tools of data science to design human fallibility out of the system.
Startups are focused on delivering automation, to scale faster. Reproducibility was a big theme, because of all of the pesky human error.
For example, Compellon, the startup who came in second place, seeks to overcome what it calls the trial and error approach to data analytics. The company’s analysis engine aims at eliminating the traditional analytics method of testing data against multiple statistical models. The promise from Compellon: “Not a statistician? Not a problem. Compellon 20|20 was built to deliver answers for business professionals with or without data science skills.”
At the Startup Showcase, a company called Virtual Cove is augmenting financial traders. Virtual Cove is creating mixed reality (augmented reality, virtual reality) to let you see thousands of data points at one time. “In contrast, Virtual Cove’s approach lets your mind absorb combinations simultaneously. This way, the lock simply opens, insight intuitively revealing itself.”
Once you put on the headset, you can see the entire Nasdaq stock market and 100 of the top companies, each with hundreds of data points. You can get a sense of the visualization in this 2-D image below – but the real benefit is being able to walk around and quickly take in all of that information.
The founder, Bob Levy, points out that that humans have skills that are hard to reproduce in machines. The role of the trader has been decimated by the rise in algorithmic trading. Code and software and data have replaced humans, because they move faster. But the ability to quickly take in sensory data in 3-D form and process all of that information visually could be our saving grace.
Where else could this go? Could we move beyond augmenting our analytical brains and tap into our human desire to feel, to express, to play?
Having had the pleasure of playing with Tilt Brush on the HTC Vive, I could envision a future virtual trading floor of traders hurling iridescent company stock sculptures at each other to make a trade.
I could see a future annual shareholders meeting, with community activists and eco-activists parading their data sculptures of impact in front of the company’s financial performance review.
What do you see as the future of data intelligence? Do you see machines gunning for your job? Are you at risk of being automated, or will you benefit from tech and data-driven augmentation? How are you playing with new technology make a better future?
There’s something social impact founders and design entrepreneurs have in common – a shared allergy/yuck factor when asked to make business models. We try to dispel that myth – business modeling as an iterative act of emergent and divergent discovery, pattern association, and everything fun.
From banking to biotech, retail to government, nonprofit to energy, every business sector is changing in the face of abundant data. Driven by competitive pressures and rising consumer expectations, firms are getting better at defining business problems and applying data solutions.
Companies like BBC, Walmart, GE, Merck and NGOs like Datakind and the DOT will share hard-won lessons, painful mistakes, and clever insights. We’re introducing a new Tutorial Day track packed with case studies, where you can hear from practitioners across a wide range of industries.
We call this track Data Case Studies. In a series of 12 half-hour talks aimed at a business audience, you’ll hear from household brands and global companies as they explain the challenges they wanted to tackle, the approaches they took, and the benefits—and drawbacks—of their solutions. If you want practical insights about applied data, look no further.
This course is about understanding the levers that drive business, and learning how to turn them into your favor.
You will learn through experience and work in teams to develop a concept from the generation of an idea to launch or market test.
Warning: the course involves a field work commitment of 5-6 hours per team per week. Much of the work of business model innovation is done outside of the classroom, in direct observation and conversation with your potential customers. The primary focus of the course is the work of developing your network capital – building connections with potential customers, partners, investors, and subject matter experts to help define opportunities that the concept is designed to solve, and early stage product development. A strong component of individual leadership development is built into the course- for students to identify your core values, and to work in teams to co-create a vision for your project, or your business.
We’ll bring the best thinking and methods from MBA school, Lean Startup, Design Thinking, Business Model Canvas, Innovation Accounting, Social Impact Entrepreneurship, Leadership Development, and Agile Methodology.
Excited to teach a revised and redesigned version of Lean at Parsons The New School for Design’s BBA program.
Here’s the syllabus:
BUSINESS MODELS AND ENTREPRENEURIAL STRATEGY
Course Code: PUDM4322 CRN: 7370 | Section: A
Instructor: Jen van der Meer
Fall / 2016
Monday / 9:00 AM
Location: 6 East 16th Street, Room 1108
This course prepares students with a hypothesis-driven approach to company formation. Students will work in teams to generate a business concept, and then validate business model risks in direct collaboration with customers. This course is offered in conjunction with the Senior Project studios and allows the students to compare and analyze different business models and strategies for their Senior Project concepts. Students develop storytelling and financial skills to lead early stage companies from concept through launch.
Open To: Open to: BBA in Strategic Design and Management students; Seniors only; others by permission of BBA in Strategic Design and Management program.
By the successful completion of this course, students will be able, at an introductory level, to:
DEMONSTRATE FAMILIARITY WITH hypothesis-driven innovation methodologies practiced in “real world” startup environments (Lean Startup, Business Model Canvas development, Minimum Viable Product/Proposition).
DEMONSTRATE FAMILIARITY WITH presentation and storytelling skills necessary for early stage startup strategy, team formation, and capital raising.
DEMONSTRATE FAMILIARITY WITH financial literacy, learning the basic building blocks of innovation accounting, generating financial assumptions and forecasts, marketing sizing, term sheets, and capitalization tables.
DEMONSTRATE COMPETENCE IN developing realistic business model evolution scenarios, and ability to create, analyze, combine business model archetypes.
DEMONSTRATE COMPETENCE IN business model validation: the practical strategy of identifying unique customer segment(s) and an early stage value proposition through real world customer discovery interviews and early stage prototype tests.
Class Theme and Activities
Class intro / concept formation
Team formation, intro to the Business Model Canvas (BMC) and customer discovery
Early stage company concepts
Customer discovery, customer validation, Market Size Analysis (Total Addressable Market, Served Addressable Market, Target Market or TAM, SAM, TM)
Company BMC analysis results
1 Business model archetype analysis
Value, value propositions, and the purpose of business, team forms initial BMC hypothesis v 1.0, team develops customer interview plan
Team BMC 1.0, TAM, SAM,TM
1 Business model archetype analysis
No Classes – Rosh Hashanah
Personal value, motivation, vision, and team, team continues to plan customer interviews
Customer discovery interview results, BMC 2.0
2nd Business model archetype analysis
Customer relationships, channels, initial value proposition test
Midterm: validated “front stage” of the business model, competitive analysis, initial value proposition
Midterm presentations, including BMC 5.0
“Back stage” of the business model: Resources, Activities, Partners
Customer discovery interview results, BMC 6.0
5th Business model archetype analysis
The money: revenues, costs, how to create financial scenarios 3 years out
Business model scenarios
3 year financial assumptions
7th Business model archetype analysis
Investment strategy, cap tables, term sheets
Validated unit economics
8th Business model archetype analysis
Turning customer discovery insights into a Minimum Viable Product
Draft cap table, term sheet, investment plan
9th Business model archetype analysis
Storytelling and pitch clinic, how to create a “teaser” presentation and a longer form presentation for investors, employees, partners
Short form presentation
Lessons Learned – Final
Long form presentation
The students will work in self-formed teams to simulate the experience of developing a startup from scratch.
Key tasks, all as group work:
Presentations: weekly presentation of lessons learned, updated Business Model Canvas versions based on customer interview findings, formulation of new hypotheses to test (over 10 weeks).
Field research: customer discovery interviews (at least 30 interviews per team or until key business model hypotheses are sufficiently validated).
Financial analysis and industry analysis: market sizing (total addressable market, served addressable market, target market estimations.
Value proposition test and test results for midterm
Financial scenario development, calculating and validating unit economics, investment strategy, cap table, term sheet
Pitch development and delivery.
Final lessons learned presentation.
Final Grade Calculation
10% participation in class, giving constructive feedback to your peers
30% progress in customer validation, customer interviews
20% midterm validation test and presentation
20% financial analysis, scenarios, and projections
20% final pitch and lessons learned
Extra Credit Policy
No extra credit
Textbooks may be purchased (new or used), rented, or downloaded through standard sources such as Amazon, Barnes & Noble, or Chegg. Be sure to use the ISBN number in order to ensure that you are ordering the correct edition.
Book available on directly from the publisher:
Lean Analytics, Alistair Croll and Ben Yoskovitz, 2013
Steven Spielberg’s 2002 movie Minority Report was for many dark and dystopian. Tom Cruise’s character walks through an invasive screen-lined lobby bombarded by ads. When a camera identifies him with a retinal scan, a dancing 3-D video calls out to him, “John Anderton! You could use a Guinness right about now.”
Some would say that future is already here, but will advertising keep encroaching on our lives like that?
Here are six signals that show a potential future without advertising and one giant reason we should celebrate.
1/ Ad Blockers on the Rise
In her her 2016 Internet Trends report, KPCB Partner Mary Meeker reported that ad spending is at all time highs, but ad blocker use is growing, faster. Ad blocker users grew to 420 million, up 94% from last year. Growth is global, and the leading ad blocking countries are China, India, and Indonesia.
Music, TV, and movie subscription streaming services continue to grow. 46% of all US households have access to a streaming video on demand service,according to Nielsen.IFPIfound that there were 68 million streaming music subscribers in 2015, up 45% from 2014. The most popular streaming services, Netflix and Amazon Prime, both offer completely ad-free experiences.
3/ Fraud is Big Business in Digital Ads
Have you bought digital ads for your latest campaign, and wondered why performance was so low? One culprit could be fraud in digital ads. In the most recent Bot Baseline Report predicts that advertisers will lose $7.2 billion globally to fraud bots in 2016. The study deployed detection tags to measure “bot fraud,” or non-human traffic. While direct media buys had lower fraud, ad formats such as programmatic video ads had 73% more non-human traffic than the study average.
4/ Media Companies Hunt for Models Old and New
The decline in print advertising has decimated the newspaper and magazine industry. The companies that survive are shifting their focus to the future, or back to the subscription model of the past.
The New York Times’s new Public Editor, Liz Spayd described the company’s shift to focus building an audience of paying subscribers, who already generate more than half of the company’s revenue.
The NYC Media Lab is on the hunt for new business models made possible by new technology. Justin Hendrix, the Lab’s Executive Director, says, “The rise of defensive user behaviors like installing ad blockers has created a context for experiments with business models for media that look beyond advertising.”
5/ Advertising Forces a Tradeoff
If you live inside of a company dependent on advertising for revenues, then you know the perils of a business model with inherent trade-offs and frictions. You are constantly having to balance the needs of your audience with the needs of your advertisers, and if you make one side too happy, the other side is not happy. This is true for any advertising-driven company, from Google to The New York Times to a YouTube vlogger.
The young and hungry entrepreneurs of tomorrow are favoring other business models over advertising. In the early days of the internet, the idea was to build an audience first, monetize later. Monetize later typically meant earn money through advertising.
Why We Should Celebrate a Future Without Advertising
If the company founders of Silicon Valley can’t see advertising in their future, maybe this is the strongest signal of all. We’ll live in a science fiction future fantasy of a calm, focused life, free from the distractions of advertising.
Better yet, perhaps this hunt for the better business model will direct more innovation to better alignment between customer needs and value created. 100% focus on pure customer engagement, with no advertiser trade-off, may be the strongest position in the long run.
So what do you do if you’re dependent on advertising in your business model? Start thinking of business modeling as a verb, not a noun. Don’t fret, or bury your head in the sand. Begin the path towards business model innovation. Try to envision new models, experiment new ways to create and capture value, and co-create with your current and future customers. You may just find out that other models out there are better for your business.
Here’s a roundup of one page strategy tools our opinion of which tools work best.
The idea of the one page strategy tool has been around since the 1880s when French managers sought to see the world beyond mere financial and accounting metrics. The rise of Business Model Canvas and other tools like it take visual strategy out of the wonky heads of MBAs and into the hands and sketches of teams with diverse skills and perspectives. The tools are most popular in organizations faced with uncertainty and complexity. If you need to tap the diverse skills and expertise in a team-based approach to define the future, try a strategy canvas tool on for size.
We start with the Business Model Canvas and conduct a roundup of other tools we’ve seen in startup, non profit, and corporate innovation settings. We’ve eliminated any tools with paywalls under the assumption that a paywall is a bad business model for strategic thought leadership!
Business model innovation is a fairly recent concept in strategy circles, going back 20+ years ago in sync with the Netscape IPO. Suddenly, seeing the future potential of a fast growing company became more complex, with more options, combinations, and possibilities.
Back then, it didn’t make sense to invest the time and effort to develop a full business plan for every possible combination. We tended to choose one directional path, write a long form plan, and march forward. Often, founders would end up marching to their quick demise following the illusion that a plan was a roadmap, or playbook.
Fast forward to the present day. Business model innovation is popular in startup circles, but also in corporate innovation, nonprofits, and social impact entrepreneurship. The magical tool: The Business Model Canvas, by Alexander Osterwalder and Yves Pigneur.
The Business Model Canvas Canvas includes all 9 building blocks and is based on Osterwalder’s PhD thesis – Business Model Ontologies (don’t click on the PhD thesis link unless you are an extreme business model geek with hours to spare).
The Canvas enables you to see your business model potential as something sketchable, involving sticky notes, and Sharpie pens. Design thinking meets a whole company view. Osterwalder encourages a sketch and prototype approach, and to use the Canvas in group meetings to create a shared language and understanding about business model options.
The Business Model Canvas is best used as an iterative tool, to create shared understanding and document team learning. Osterwalder’s strategy firm, named Strategyzer, and Steve Blank’s Lean LaunchPad curriculum both use the Canvas to test and validate assumptions over time.
In Silicon Valley, failure is “accepted, even encouraged.”
Not according to my sample size of Uber drivers.
I’m in San Francisco today, where Uber drivers are the new bartenders, and represent potential bellweather for what’s really going on in the Bay Area. From a sample size of 4 Uber drivers, representing an average of 200 rides each, I learned that the primary themes discussed with their rides were bankruptcy, lack of funding, or fear of running out of cash. If you can’t tell the truth to your investor or fellow co-working-space co-workers, then maybe the dark confessional of the Toyota Camry is your only outlet.
Let’s face it, we really don’t want to fail, but we do want to learn.
Perhaps we just need a few more words to describe failure, so that we know what we’re talking about.
The Failure Learning Curve:
Failure of Not Trying
Let’s start with a true form of failure: the failure to not even try. All would agree that there is cowardice in not showing up.
Did you make an oops? A clumsy blunder? Did you swing, and miss? Well then fear not – we all do, and in fact this is the kind of mistake we should celebrate. See Ben Zander coaching a young cellist to say “how fascinating!” with each flub rather than wince and shut down emotionally.
Starting at the 11 minute mark in this video:
Did you try something, expecting a specific outcome, but you found out you were wrong? Well that’s reason to celebrate. You have invalidated your assumptions. The next time you present your results to your team, make sure to include all of the assumptions you have dutifully disqualified – proof that you are saving time and focusing your energy on more promising paths. Answer the most important question – what insights do you have now that you didn’t before, and what did you learn?
“An inventor fails 999 times, and if he succeeds once, he’s in. He treats his failures simply as practice shots.” ~Charles F. Kettering
Did you uncover a big opportunity, an opening to go big or go home? But then did you swing big and strike out? This is the kind of failure embraced by many in Silicon Valley. Investors are taking big risks, and are willing to let nine out of ten porfolio companies fail in order to see one company get exponentially substantial returns.
When you play on this particular game board, you will be asked to speed up your product timelines, spend more on marketing and sales, and go for the ultimate prize: being the winner that takes all in the category you are creating. If you strike out under these conditions, well they were worth the effort.
The Epic Failure
Did you build a giant business plan, model out five year financials, and burn through millions or even billions of dollars without vetting the risks? Did you march your team forward refusing to listen to your customer or to market signals? Did it take you many months to get your first version to market, only to attract few customers at launch? Well then, that is failure. It’s epic failure. Feel the shame.
If you are recovering from a major failure and get back on that learning curve as you try again. You will have to shift from the false comforts of planning through Powerpoint, and learn how to cultivate new business models. Allow yourself a few more moments of “oops” this time, focus your efforts and disqualify bad ideas, and hunt down the bigger opportunities. And you’ll have much more fun.