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If The Shoe Fits: Quantitative Data and Self-Deception

Friday, June 16th, 2017

A Friday series exploring Startups and the people who make them go. Read all If the Shoe Fits posts here.

5726760809_bf0bf0f558_mThe following post is reprinted in full with Wally’s blessings. I e-met Wally when we both blogged for b5 Media — I think. It’s so long ago I’m not sure, but over the years I’ve read and appreciated Wally for both his insights and independence from accepted leadership-speak. I highly recommend adding his blog to your reading list.

Quantitative Data and Self-Deception

If you need someone to blame this on, it might as well be Rene Descartes. The 23-year-old Descartes was serving in the army when was visited in a dream by the Spirit of Truth who told him that “Conquest of nature is to come through number and measure.”

Numbers were power. That effect was amplified during the Industrial Revolution. That’s when the engineers took charge, measuring and calculating. Soon, Frederick Taylor and the efficiency experts showed up with their stopwatches and clipboards. Now we’re in the Digital Age, where computers spit out numbers by the mountain load.

Today, companies trumpet the claim that they’re “data-driven.” The Economist proclaims that “data is the new oil.” If there is a golden calf to worship today, it’s probably digitized.

We love numbers so much that we don’t think about where they come from or how we’re using them. We can summon them from our vast databases, manipulate them, and turn them into equations that give us “answers. It makes us feel like we’re in control. We’re not, really. We’re only in control of the data.

The map is not the territory and data is not reality

Data is not reality. At best, data can only represent reality. Reality is complex and messy and we can use data to simplify parts of it so we can understand it better. To do that we must leave out part of reality, assign numbers to things that aren’t inherently quantifiable, and approximate relationships with equations.

If, after all that, we treat data like reality we commit what Alfred North Whitehead called “the fallacy of misplaced concreteness.” We get lost in the wonder of our calculations and think we’re describing the elephant, when we’ve only got hold of one leg.

It’s a good idea to apply George Box’s observation about models to our data. All are flawed, but some are useful.

Quantitative data is not objective

No matter what you or your boss thinks, quantitative data is no more objective than qualitative data. Someone, somewhere, sometime decided what would be counted and tracked and what would not. Someone, somewhere, sometime decided how and how often data would be gathered and how it would be presented.

That’s obvious when you talk about qualitative data. We usually get qualitative data in the form of a story. This happened when we observed it this way. With quantitative data, the questions, assumptions, and decisions that lie behind the data are usually behind the curtain and invisible to the people who receive and use the data.

Dig into the history of things to find out why you use certain measures and not others, how the raw data is gathered and manipulated, and why it is presented in the way that it is.

Quantitative data is not enough

Quantitative data is important, it’s just not enough for a successful business or a satisfying life. The most important things in life and business can’t be counted or calculated. Relationships drive much that happens in business. More than half a century ago, Mason Haire demonstrated that emotions influence buying decisions of all kinds. Knowledge workers trade in conversations and tacit knowledge.

There’s one more thing about quantitative data. It’s easy for us to manipulate and “understand” quickly, so we’re likely to pay attention to what we can count and ignore what we can’t. That’s part of the reason why the long term is often sacrificed to the short term and why numerical accounting data gets more attention than “soft” human stuff. As one friend of mine said years ago, “When the pressure’s on to make the numbers, people almost always take a hit.”

Bottom Line

Quantitative data is important. You can’t run a successful operation today without paying attention to it. Remember that quantitative data is always a flawed representation of reality. Look behind the curtain to discover the whys and hows behind the data. Remember that human choices drive quantitative data as much as qualitative data. And, please, remember that the most important things in life and business cannot be force-fit into a dataset.

Copyright © 2017 Wally Bock, All rights reserved.

Image credit: HikingArtist

Ducks in a Row: Make a Difference — in the US

Tuesday, August 23rd, 2016

https://www.flickr.com/photos/bonniesducks/4395202521

Is making a difference important to you?

It should be, since most workers are happier and more productive in companies that give back.

That holds true no matter the age of the worker or the size of the company.

Companies, departments, teams or individuals can choose to make a difference.

Some go far afield and seek to mitigate the problems and tragedies of less fortunate countries.

Others focus on local problems, which makes sense since companies are usually urban.

That said, you don’t have to go overseas to third-world countries to find third-world problems to solve.

Tech could start less than 200 miles from San Francisco in Fresno, CA.

While Facebook wanted to wire India, it isn’t interested in doing the same in the US.

Though Central Valley harvests most of the country’s crops, tech workers often forget their neighboring region exists. In the Bay Area map according to Urban Dictionary, the Central Valley is jokingly referred to as “unknown parts.”

And consider this.

According to a recent Pew survey, approximately five million students still lack access to high-speed Internet. Experts have taken to calling it the “homework gap.”

Or turn your gaze to the other coast and some of the most beautiful countryside in America — Appalachia — home to some of the most grinding poverty and third-world living conditions to be found in the US.

And while you’re gazing, check out what’s being done to change that.

Crunching all the data imaginable won’t always yield a solution, since anomalies do happen (for an in-depth understanding of that read Isaac Asimov’s Foundation series, still brilliant/viable after 60+ years).

Back when I lived in San Francisco, it was often termed “49 square miles surrounded by reality.”

That’s expanded to 7,000 square miles (contained in the nine-county Bay Area) surrounded by the reality of places like Fresno.

Tech needs to understand that technology in and of itself is not a solution.

Tech is digital, while the world and the humans who inhabit it are, and always will be, analog.

So while technology itself isn’t a solution, the ways it can be applied may be.

~~~~~~~~~~~~~~~~~

One more request.

School is starting soon and most kids are shopping, whether at Nordstrom or Walmart, while thousands of foster kids are facing school without even a backpack.

There are dozens of ways you can help them.

Skip a few Starbucks or Peets visits, choose a charity, check it out and donate the coffee money you saved.

Flickr image credit: Duck Lover

App Cost/Benefit Analysis

Wednesday, September 9th, 2015

https://www.flickr.com/photos/jasonahowie/7910370882/

A post I wrote after two researchers made headlines by hacking a Jeep and taking control of its vital functions focused on the idea that nothing would change until consumers voted with their wallets and demanded better security.

Until that hack, combined with several major data breeches in the last couple of years, the general public didn’t seem particularly concerned — and that nonchalance is especially prevalent in those who grew up wired.

In a comment on that post I wondered if consumers just didn’t care or didn’t understand, but there is another option.

I read a article about Conspire, a new site that helps find business emails and sent it to several people I thought could use it, including Ajo Fod, founder of QuantPrice and occasional contributor here.

Conspire uses your email account as the basis for a game of Six Degrees of Separation. Sign up, and it analyzes your email. Then enter the name of the person you want to search and it finds someone in your contact list to introduce you, examining that person’s social-media connections. It may even find multiple people to help introduce you. Then it will recommend the best choice.

Ajo joined and sent me an invitation. I haven’t accepted yet, because Conspire requires your email account information and password (plus my email uses POP3, not IMAP).

I asked Ajo if he was concerned about security and here is his answer.

Security is a concern,

… but benefits are a bigger.

… I’ve been hit before by a bad egg that decided to spam all my contacts.

… so, yes, I was worried when I gave out my email/password.

… In this case. I did some research and thinking and the potential seemed big.

I do worry about credit card numbers and identity.

… In my mind, the benefits outweigh costs.

People still send me phishing emails.

Perhaps, being an Indian security is a lesser concern to me than other people my age in the US.

Actually, Ajo gave it more thought than most people I ask no matter their age.

There is one more thing you should think about when doing a cost/benefit analysis.

Time.

What is the ROI for the time you will spend?

Is the new app a time saver or time waster?

Money can be replaced, but once time is spent it’s gone forever.

Flickr image credit: Jason Howie

Lean Startup Conference 2014: Metrics: The Data That Will Make or Break Your Business

Wednesday, December 10th, 2014

kg_charles-harris

KG Charles-Harris is once again attending the Lean Startup Conference and sharing his impressions and what he’s learning with you.

Tuesday

Metrics: The Data That Will Make or Break Your Business

Alistair Croll, Solve for Interesting, @Acroll

The first day at the Lean Startup Conference 2014 has been excellent!  I’ve been at an all-day seminar by Alistair Croll – the author of the book Lean Analytics.  A very boring sounding name, but really the essence of how to create a sustainable product market fit and scalable business.  How do I know that I’m on the right path with my products?  How do I know that the pricing is correct?  How do I find the factors that are influencing the growth of the company?  Etc.

I must say that every minute spent in the seminar (from 10 am to 5:30 pm) was worthwhile, even the time spent on the larger organizations, as he made it very useful by comparing to startups in every single part of the process.  Even for a startup guy from a tech startup, the part of the session that focused on innovation within large enterprise companies was fascinating.  Understanding the difficulties those intrapreneurs experience almost made the travails startups go through seem simple.  Alistair’s suggestions and advice for how to think around these issues and attain success.

The room was filled all day and I noticed that I wasn’t the only participant with rapt attention on the presentation – everyone else was very focused on what he was saying.  The sessions were very interactive with people feeling comfortable to ask questions and Alistair encouraging discussion.  Everyone I spoke with during lunch said they were captivated and that his lectures were transforming their thinking.

I am lucky to have been able to participate in this seminar – it is clear that it will have a strong effect on how I execute within my startup as we begin interacting with customers on a broader scale.

If the Shoe Fits: Breaking Trust, an Industry Standard

Friday, February 17th, 2012

A Friday series exploring Startups and the people who make them go. Read all If the Shoe Fits posts here

5726760809_bf0bf0f558_mMost people consider it wrong to take something, whether tangible or intangible, from someone’s home without asking—it’s called stealing.

Most people will be highly offended, if not downright pissed off, if someone goes through their cell phone, contacts their friends or reads their texts and emails.

Companies, on the other hand, see nothing wrong with it—unless they are caught.

I’m not referring to sleazy porn sites, but to the biggest names in mobile and social, the ones that are role models; names like Google Android, Twitter, Foursquare, Apple i-Whatever (Apple claims they prohibit it, but Yelp, Gowalla, Hipster and Foodspotting all do it) and a host of startups and app makers.

The address book in smartphones — where some of the user’s most personal data is carried — is free for app developers to take at will, often without the phone owner’s knowledge.

Heck, appropriating data was actually industry standard, until they were caught, that is.

Now they all claim to be changing their practice and giving users notice when they take personal data.

Does that give you a warm feeling or do you still feel violated the way you would if your home was broken into? (Most people spend more time with their phone than their home.)

Do you trust them to be upfront/authentic/transparent/honest in the future?

Or do you wonder what else they are doing that they haven’t mentioned and probably won’t unless/until they are caught.

Trust is fragile and difficult to fix once it’s broken.

Even oblivious Americans are starting to notice.

Option Sanity™  is trustworthy.

Come visit Option Sanity for an easy-to-understand, simple-to-implement stock allocation process; so easy a CEO can do it.

Warning.

Do not attempt to use Option Sanity™ without a strong commitment to business planning, financial controls, honesty, ethics, and “doing the right thing.”
Use only as directed.
Users of Option Sanity may experience sudden increases in team cohesion and worker satisfaction. In cases where team productivity, retention and company success is greater than typical, expect media interest and invitations as keynote speaker.

Flickr image credit: HikingArtist

Barrett’s Briefing: The New Recipe for Business Success

Tuesday, June 9th, 2009

Recipes have changed over the years, with the biggest change being the elimination of fat. Ingredients for business success have similarly changed—no fat. Now it’s content and communities—not capital

Recessions have traditionally been good times to start new ventures and to expand SMBs (small and mid-size businesses). Larger competitors retrench, leaving some market niches exposed and unprotected. Workers are available, often at reduced rates.

Recessions loosen long-time business relationships and create brand-new opportunities. Recessions are Joseph Schumpeter’s “creative destruction” on steroids.

This recession is exceeding all expectations for creative destruction; but with a few substantial differences.

First, while risk capital was available for emerging ventures in previous recessions, it has simply vanished in this recession.

Second, the need for risk capital has dropped dramatically for certain types of businesses, particularly those focused on information services.

The New “New Business Model”—Everything You Need is Free.

OK, “free” is a little bit of an exaggeration. But the cost of business expansion is dramatically lower than in the past. For instance:

  • You don’t need an extensive network of offices. Most knowledge workers already have home offices. They work at a customer site, at home, or with co-workers at a coffee shop.
  • You don’t need a sophisticated telecommunications system. Virtual PBX’s, portable telephone numbers, internet-based telephone service, and conference call services are inexpensive and readily available.
  • You don’t need a big advertising budget. With Google Ad Words, you can pay only for results. Better yet, create your own promotion with social networks, blogs and email communication.
  • You don’t need production equipment, raw materials, or inventory. The data is the business.
  • You don’t need a computer facility to host your information database. Google, Amazon, Microsoft, Salesforce and others offer cloud computing for free.
  • You don’t need any back office. You can outsource accounting, HR, IT, CRM, and almost every other internal business function.
  • You don’t even need employees. You do need a team, but new business models use clusters of associates.

If everything is free, then what do you need to build your business?

You need content and communities.

You don’t need capital!

This is an over-simplification, but allow me to make the point.

You Need Content

Your business needs something of value to provide to customers.

In the information age, this is content—not just entertainment content, but a cluster of information, typically housed in a set of inter-connected databases. In previous posts we discussed Google, Jigsaw, and Alexa.

Another example is deCODE Genetics. For only $195 and a sample of your DNA, deCODE will map your genes, identify a collection of your genetic risk factors, and map your genetic ancestors. This business model combines a proprietary database with a physical connection to each customer.

Granted, the actual consumer service is a “nice to have,” but the business model is powerful. Your business generates a continuous stream of data. Package it and build a data business.

You Need Communities

Communities are more than just a collection of customers, suppliers or employees. Communities have common interests.

Your business is only the conduit, or the meeting place for your communities. The most effective communities have some structure. Online games are excellent models for your communities. Provide enough structure and rewards to stimulate the community, but then let it grow.

You Don’t Need Capital—You Do Need a Cash Business Model

This may be one of the biggest surprises of the new century. The internet, low-cost communications, and the availability of low-cost support services have dramatically leveled the playing field for new businesses competing with established organizations. You don’t need huge capital investment to build an information business.

With no investment capital, you need a business model that generates cash quickly.

Here again, technology and the internet have conspired to meet your needs. Credit card payment systems eliminate the collection hassle. Internet delivery and prepayment terms shorten the cash cycle.

All you have to do is provide compelling value for your customers.

Go do it.

Barrett’s Briefing: Building YOUR Data Business

Tuesday, April 7th, 2009

Data: Salt for the Information Age

Roman soldiers were often paid in salt; this was so common that the Latin root for “salt” and “salary” is the same – sal.

As important as salt was in ancient ages, just so is data in the information age. Data is the raw material for information. Just as salt improves food, today data enhances the value of products and services.

In the two previous posts we explored how “the data is the business.” For many information age businesses, the collection, maintenance and distribution of data is, in fact, the primary revenue source.

But, based on questions from readers, I’m not getting through, so let me spell it out.

Every business collects, maintains, and distributes data.

The better businesses use data to enhance the value of their products and service.

The smartest businesses use it to generate revenue directly.

There are only two types of Databases…

At a high level, databases collect information about only two things – population identities or activity trails.

For instance, the company accounting system may be the original business database.

  • The balance sheet is a database of population identities – how many dollars in cash, accounts receivable, inventory, accounts payable, bank debt, equipment, and owner’s equity.
  • The income statement is a database of activity trails – what was the activity in sales, in collections, in payments.

The accounting system integrates these two databases into a unified view of the entire financial situation for the company.

The Census Bureau is the granddaddy of population identity databases; others include Monster.com (resumes), Dun & Bradstreet (small companies), Hoovers (public companies), MarketWatch.com (mutual funds), Google (websites and search words), to name just a few.

Databases of activity trails are just as common: stock price websites (stock price activity over time). FedEx, UPS and other shipping companies offer activity trail databases for every package they ship.

Of course, just like the accounting system integrates population identities and activity (audit) trails, the most powerful databases integrate population identities and activity trails. See if you can think of five or ten more.

There is really only one type of Database that really matters—yours

This is the key point. Your company already collects population data and activity trails for every product and service you sell. You have a database of all the products and services for sale (the sales catalog) and a number of databases that support those products—bills of material, inventories, historical demand, price histories, revisions, replacements, and a cluster of support products and services.

Your company also has a natural user and customer base for the data you collect. Customers, suppliers, service partners, and competitors all have a great interest in that data. So here already are the beginnings of a data business—a database and potential customers for that data.

A Few Small Bumps

Externalizing a database can be a significant challenge. It’s worth investing some time and even a few dollars in developing strategies for these key issues before rolling out your new business. A little planning and caution in building a good foundation will pay handsome rewards later.

Operational Concerns

Who owns the data? Does your organization have clear, unambiguous title to the data? For instance, are prices negotiated as confidential in certain supply and delivery contracts? If ownership is not clear, then how can you anonymize the data to honor the agreements? Can you change the agreements so that your ownership is clear?

How is the data refreshed? Data gets old. As the database grows data maintenance rapidly grows and soon exceeds data collection as the primary challenge. Some companies, such as D & B and Hoovers, use an army of employee agents to check and update the data.

Historically this approach worked, but the scale of modern databases has rendered the “internal data army” impractical. Consider two other approaches

  • automation and a
  • user community.

Automate the data collection and refresh. Google uses automation to refresh its database of websites. By some estimates Google has several million computers (really just CPU data blades) crawling the web to update its website database. Many other databases receive data feeds periodically from their sources. For instance, foreclosures.com gets feeds of foreclosure information from almost every county in the United States. The conversion and translation must be a nightmare, but the resulting database is incredibly powerful and a great business.

Motivate the user community to collect and refresh the data. With the emergence of web 2.0 and social networks, many companies are creating and using a user community to do data collection and refresh. YouTube.com, MySpace.com, Facebook.com, and LinkedIn.com are good examples of social network databases created and refreshed by user communities. Wikipedia.org, Jigsaw.com, and credit reporting agencies have created or adapted user communities specifically to provide business data. Travel websites such as Expedia.com use both automated data collection and business user communities to collect and present their databases of airline and hotel prices.

How do users access the data? Online access is rapidly emerging as the only method to sell data. Intermediated purchases, which require you to process the purchase request, are simply too expensive. Customers want instant access. Put the database online and develop search/selection capabilities that allow customers to find exactly what they want.

How do users pay for the data? A la carte or by subscription. Subscription is emerging as the preferred approach, both for data suppliers and data consumers. Tiered subscription access appears to be acceptable, so long as it is not too complicated.

Legal Concerns

The law on ownership and distribution of data is under construction. Quite simply, these are brand new businesses—often there are no regulations, limited historical precedents and even more limited applicable case law. And since the web is global, multiple national laws may apply. It’s complicated, so invest heavily in the two basic legal agreements—Purchaser Agreement and Contributor Agreement – to protect your company and your data. Limit your liability and do not compromise on your exclusive ownership. Others have found that shared ownership is simply an invitation to an ongoing dispute.

There is Wisdom in Metadata

If the data is the salt for the information age, then metadata is the spice. “Best selling, fastest growing, most popular, most expensive, Top Ten and cheapest” are all metadata lists generated from databases.  What trends are hidden in your databases? What trends do your customers and suppliers track?

Track the trends in database businesses to identify the best opportunities for your company.

Again, please feel free to call me at 925.858.9017 or email rbarrett@one-one.net for clarification on any points.

Hope to see you in the Top Ten New Database businesses soon!

Barrett’s Briefing: Eyeballs Or Money?

Tuesday, March 31st, 2009

Back in the late 20th century the business model for dot-com businesses was “Attract the eyeballs (website visitors), and the business will follow.”

Many businesses executed that model, such as AOL, FlyFishing and an embarrassing host of others, almost all gone by now.

Over time the model of attracting eyeballs simplified to Google—just Google.

Since then Google has created an effective advertising model for websites that attract eyeballs. It’s called AdSense, and the model is very simple.

Attract a large number of visitors (eyeballs) and Google will monetize those visitors through its AdSense advertising program. Google selects ads that match the profile of visitors to your website, posts the ads on your site and shares a portion of the ad revenue with you.

Google keeps all the control and can limit your revenue.

Social networks and blogs are perhaps the poster children for this Adsense business. Social networks such as LinkedIn, Facebook, and MySpace generate revenue primarily from advertising.

The community creates the content that attracts the eyeballs, and the eyeballs attract the advertisers.

Blogs are only a little different. For a blog the author creates the content, rather than the community. But after this, the model is the same. The content attracts the eyeballs, and the eyeballs attract the advertisers.

Write a compelling blog and the eyeballs/advertisers will come.

Unfortunately this is a model for a lifestyle business, not a long-term business. Over time the competition increases and Google lowers the payout, so the revenue decreases.

Is there an alternative to the model of ever-declining revenue from Google Adsense?

Yes, create some old-fashioned value from the data itself.

The Data is the Business

Last week I discussed the concept of creating business value by collecting and selling data. That is a good alternative to the Adsense advertising model:

Create value in the data.

The benefits of a data sales business model are compelling:

  • Low start-up costs. Use the cloud for your computing and storage. Google and others offer free access for applications with small bandwidth demand.
  • Easily scalable. Add storage as the database grows. Add bandwidth as customer demand grows.
  • No delivery cost – the user shops and selects and takes delivery online.
  • Minimal cost of goods sold (COGS). This really depends upon your data collection model.
  • Immediate global access and delivery.
  • Captures the value of the “long tail.”
  • Relatively easy to protect. Compared with code, a database is easy to protect.
  • Even the meta-data (data about the data in the database, e.g. statistics) has value. Think of the top 10 lists, such as the “most popular search phrases” that Google publishes.

But if this business model is so good, why isn’t everyone starting a data sales business? Maybe they are…

Join me next week when we discuss what type of data sells.

See you all then.

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