Author: christopherskinner4136

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Why does historic data often fail to see the future?

Another way to describe it: Making predictions when data fails you.

The really fast answer: when the rules are static and well described, the machine gets it.  Example: IBM winning chess matches.  When the rules change or even when the game changes, good luck.  What do smart people do that allow them to survive and some thrive in this environment?

Another example of fails: elections.  Often wrong because so many factors that are poorly described are not understood.

Historic data is great and when the rules are clear, you can predict.  For example, if I buy a printer, within so many ink cycles, someone can and should predict when I should order (in my best interests).  Recently, I got an email from CarFax predicting the need for a change right at 2% oil life remaining AND the car is NOT connected.  Is this useful? Yes.  Is this a real prediction? I don’t think so.  

When flawed or incorrect historic data exist, turning the tasks over to AI or ML will not solve the problem.  Fitting models or collecting more data is not the answer.  

What does work is creating data based on theories that are causal to outcome.  Even if you don’t have the actual data to prove it, a theory that is causal is likely more valuable.  When that theory based data is connected to historic data AND you have the right math to connect the two, you got it.

Some people use a concept called transfer learning, which attempts to connect one domain to learning to another.  I think that is very useful.  The idea is to identify a set of learnings from one domain to another.  That is what I did to create a hypothesis of personality traits for people where I have no real time data.  Once you have this causal relationship mapped, you can form a connection and identify “proof points” to help the concept work.

One example might be polling for elections. Pollers should look at things besides voluntary requests for who you voted for.  We are well past that.  When will brands and commerce realize the same problem exists in their world.  Hard wired, collelative data is not going to keep them afloat.

We have an increased need for new ways to adjust the quantity and quality of data within the organization.  The math is also well overdue for revision.  So, as a business leader, ask yourself, are you relying on historical data?  If you are you may be ignoring the future.

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When getting your business ready for change where do you start?

Here’s some thoughts that might make sense.

Step 1: Figure out who your leaders are and figure out what their mission and vision is. A lot of times we ‘hear words’ but they don’t reflect the true meaning and desire of the leadership of the organization. Is the mission and vision of the organization properly reflected? Often, I find not. The leadership sometimes has a hard time explaining themselves. By analyzing word usage, you reveal the true personality of the leader and can adjust language.  People can read words and tell you if a person is honest and sincere. Can they trust in respect you through language? Yes it’s possible.  

I had one case where a letter had gone out to potential customers. It did terrible. It turns out that psychologically it was inward. It was all about them.  Another letter went out and it spoke to the customers needs. It resulted in 20 times the profitability of the first letter. Significant numbers to. Did anyone in the organization read this ahead of time? No it was not possible. The letters looked similar in tone and voice to people within the company but obviously not to those on the outside.

Step 2:  Figure out the three circles what is the how, what, and why?

Why do you want to do something versus what do you need. Most companies spend a lot of time on the how and the what but they don’t offer the deep psychological reasons ‘why’ people buy.  Once you crack this code of the 3 circles, you have a great recipe for understanding the purpose of the organization. Now it’s time to execute.

Step 3:  Create a total addressable audience that’s based on the mission and vision of leadership and the organization. What is the deep reasons why people buy from you whether it’s B2B or B2C, Identify a total addressable audience based on functional need AND psychology of choice.  This can be done and quantified. This is what I do best.

Step 4:  Create a one-to-one marketing engine. This is where it’s difficult. A lot of media is put in place for you to ‘over buy’ or under serve and to focus on the wrong KPIs.   For example, why is your conversion rates so low?  it’s because you’re over buying. there are tools and capabilities in place that profoundly changed media-buying. the closer you can get to reaching an exact audience by manipulating media tools in a different way the closer you can reach the best customers only. 

Step 5:  Lead, nurture, close. Built in the system that finds people, reaches out and measures the results. Don’t be shy about this step.  This is a rather easy step because it’s already well defined and there’s no need to recreate the wheel here.

If you ever need help with completing these steps, feel free to reach out.  I’m always happy to talk shop.  Making sure your business model matches the customer value proposition through the psychological needs of people is critical.  It often does not take much to break in a process that will work and grow a company. We often create great products that just need some fine-tuning to reach the right people.  By orienting yourself customer psychology first, you work backwards and build an organization designed for growing towards that total addressable audience. 

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Combining Innovation with psychology

There is a tremendous amount of documentation about Innovation and Product Market fit. What else can be said? For one thing, the customer.  This is an area that is under leveraged and poorly understood.  Why do?

People are complex and they deserve to be treated properly and with great respect for parting with their money to buy your products. It’s not just a spreadsheet exercise and it’s definitely not a media exercise.  You have to start embracing the concept of quantifying qualitative aspects of the customer.  While it is tempting to see the customer through the eyes of media KPIs, it’s best to look in a different way. 

Understanding people at a deep level can be discovered through computational linguistics. By understanding people and quantifying how they think through language psychology, you can help solve their needs. Whether you call that unmet needs as product-market fit people call it or jobs to be done. Anyway you look at it, quantifying the needs of people and how your product fits in their life is paramount to growing a business and satisfying people at the same time.  

Disruptive innovation is a subset of innovation and I look at it as the exercise of freeing up resources to execute change. The foundation of disruptive innovation is understanding customer needs through jobs-to-be-done Theory as well as a number of other methods to discover the deep reasons people buy and what is lacking with the current solutions in their life.

I look at product-market fit as the creativity of market design combined with the creativity needed to build the right product and how to balance both of these efforts.

Customer psychology whether it’s B2B or B2C, can be uncovered why people buy but not for the purposes of manipulation.  Your goal should be to satisfy unmet needs and balance customer equity with customer delight.  Both equity and Delight are well known and well understood kpi that lack data about why the customer buys.

This is my passion and when organizations focus, you solve great problems while delivering quality products people need.  The first step is to reach out and let’s discuss your customer especially the prospective ones that are so hard to discover. 

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Measured performance in an uncertain world

In reference to the above, when you’re going through this cycle the goal should be to learn more, have clear ideas that are based on quantifiable expectations of underserved needs. This allows you to build precisely. By doing these things ahead of time you will speed up the process. The code will go a lot faster because it has clarity. You will measure based on a precise definition of an audience.

One of the most interesting reads I have seen in a long time is from Ash Maurya. He has a book and process called ‘Running Lean’ which you can find at runningleanhq.com

Ash clarifies a product-market fit process in a simple yet intuitive way. It’s a pleasure to read his work and I suggest it.

Because he makes things so clear I found it useful to comment on some of his slides as the technology we invented fits neatly into his process.

To start with, his clarity around problem-solution fit and it’s conversion into product-market fit is well explained.

His clarity around the process of requirements to release is well done. During the requirement step his claim is only some learning takes place and most learning occurs after release. The technology we invented improves the ability to learn quite a bit in the requirements stage. Some of the learning that takes place only after you have a customer or a user can actually be done in the requirement stage. You end up saving development, QA, and release.

Segmenting customers before they’re ever customers by people traits and ‘why they make decisions’, ultimately figuring out the underserved needs helps define the requirements, the development and ultimately improves the expectations from the release.

Quantitative data can be introduced into the qualitative stage.

Our technology inserts well over 350 data points about segmented groups of customers based on their underserved needs during the qualitative stage. As Peter Drucker once said, ‘What’s measured gets improved’… something like that, right?.

If you’re measuring underserved needs in a quantitative way from the very beginning, you will seek to improve these things and not guess down the road.

What you are ultimately going to validate is the qualitative theories using trait calculations, which represent the underserved needs of people.

Mixing up things, having a foggy picture of why people want something creates confusion which is the enemy of trust.

At Stealth Dog Labs we are confident product-market fit can be improved by doing a few more things upfront. Ash delivers a great document that we fully support. He is right, life’s too short to build something nobody wants.

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How can the balanced scorecard be better with a new and improved product Market fit software

A well-run balanced scorecard process enables product-market fit to thrive. How?

From Harvard Business School:

What you measure is what you get. Senior executives understand that their organization’s measurement system strongly affects the behavior of managers and employees. Executives also understand that traditional financial accounting measures like return-on-investment and earnings-per-share can give misleading signals for continuous improvement and innovation—activities today’s competitive environment demands.

Clearly measuring the right amount of things the right way drives the business forward. If you include an understanding of the product-market fit process, you can easily integrate a balanced scorecard into that process. One of the clear issues with running a business is how to allocate the right money in the right places. You have external demands as well as internal.

The balanced scorecard (from http://www.free-management-ebooks.com/news/balanced-business-scorecard/)

 Make product-market fit work better, having some effort put into understanding the customer is critical. Our way of thinking makes understanding the underserved needs simple and affordable and accessible to many. That creates a targeted customer base. Recently, we’ve helped a company understand its Target customer in a precise way, enabling investment in the company. Otherwise, it did not look good for its future.

Also feeding the right amount of data into the product is a learning and growth process. It feeds the right information to the people that are building the widget for sale.

A major part of the balanced scorecard is the learning and growth process. Funding this properly allows for resource allocation appropriately spent in the right areas.

Both will work well together but I must say the balanced scorecard is a little bit more of a mature business process. It’s also difficult for companies to understand product-market fit as a process. While it’s quite logical, getting everybody in an agreement can be challenging. The two separate sections of product Market fit are very different talents sets.

By understanding the reason to execute each section gives your organization the best chance to succeed.

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Building products with uncertainty – Do’s and Don’ts

Most projects I have worked on were successful because of Product-Market Fit was achieved. PMF worked because a great business operating system is in place.

Performing product-market fit as a framework or methodology alone is not enough. Having an underlying technology is critical to achieving and sustaining disruptive innovation and Product-Market Fit. I invented PMF technology because I could not find something to help me when i work at growth organizations. When the loudest mouths in the room drowns out the truth, bring data, lots of it.  I wanted a ‘source of truth’ that would remove as much organizational bias from decision making. By letting the voice of the customer come forward, you have a real chance to winning Product-Market Fit.

If you’re an organization building a product and you’re living in a world of hunches, you’re suffering from extreme uncertainties. Below is a list of the do’s and don’ts when operating under extreme uncertainty.

Do no Do
Rely on intuition alone Remove bias, use people-centric predictive technology. Solve the underserved needs of customers.
Rely on expertise alone Require deep understanding of people to test assumptions. Drive predictive, data driven thinking.
Rely on money and media to find your customer It was once possible to Media your way into finding your customer. The future is about a deep understanding so you can create Customer Delight.
Rely on Time to iterate The one thing no one can buy. Limit guessing by time.
Experiment Experiment with expectations of the results that are time-boxed. Become predictive. Better yet, be prescriptive. Expectations should be based on qualifying the customer at a deep level. Predict why people buy.
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Avoiding economic winter – allocation issues at the right time or wrong time?

Businesses that spin-off value, whether it is in the form of investment stages or revenue have the terrible task of budget prioritization.

This is a very delicate stage. Allocating funds based on the wrong expectations can result in bad allocation likely to be focused on the wrong things. The wrong things, wrong time or whatever the case, this can create an economic winter –  think of it as a dry season. Nothing is going to grow because you’re not funding the right activities.

In the tourism business, many cities allocate hotel taxes when times are great. Instead, the math should allocate money during slow times.  What are you doing to create a better allocation system?

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Does geography & profession impact personality?

Whenever you’re  researching a market by geography, there will likely be a limited set personality traits based on functional characteristics of your Market.

For example, imagine doctors that live in a certain region of the United States. I found that in discrete areas there were three primary traits of doctors in that area.  Lets say, this was limited to a 4 State area. The area tends to be a bit on the poor side.  There was an absence of core drivers and needs. These people were not willing to build a business and snuff out competition, which could be too close for comfort. If you’re going to have that dominant approach in a small market, you might not have many friends (or customers) left. There’s a bit of a get-along factor that takes place. The larger the town, the more drive.

I discovered a) social orientation, b) family orientation and c) a lot of anxiety.  There was clearly a dominant family orientation in certain regions as opposed to others. Likewise, for social and anxiety. To geographically market without recognizing the trait variation would mean incredible inefficiencies being absorbed into the media plan.  For example, to build out a family-oriented marketing plan for the state of Iowa would automatically create three times or more inefficiencies through Google AdWords and social platforms.

The product is another aspect.  Once you identify the core traits and how these doctors are oriented, in these areas, the product needs to be adaptive to the job to be done. For example the doctor who is very socially oriented, wants to be connected to their customers even if there is no need for their services. This is part of their personality. Any product that would have an integrated or even modular capability to help connect customers outside of immediate need would be a win for these doctors.

There are a lot of doctors in these particular regions that are family-oriented. They went through all this schooling not to get rich (they are not) but to provide for a family in the environment they desire. They live well and focus on their family.  Any product that is oriented towards helping them with their family would be seen as a win. Imagine a partnership with care.com or some way to help transport, care for or organized life while at work. 

People are diverse in thoughts and needs.  Geography plays a part and when the media is geo-centric it creates massive inefficiencies that can be solved by hyper focusing on the needs, 1:1 media, and building products are can be dynamically modified to need psychological needs.

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Figuring out who buys your product

The best way to figure out who buys your product is to go through the exercise of ‘jobs to be done’. This predicts why the customer buys in great detail.  Front ending JTBD methodology with my approach, creates speed and agility.  By combining, you also have the ability to track prediction to Performance.

It is said that every job has a finite set of functional, social and emotional components and that these elements are often viewed as irrational and hard to quantify.

At the heart of disruptive innovation, jobs-to-be-done and Product Market fit is understanding the core motivations of the buyer. After years of research, I can state that every job has a functional and psychological dimension that can be quantified and predicted.  It can also be mapped back to a predicted total addressable audience and a media plan that is a fraction of the cost of the old ways of doing things.

The next step in the process is to create the experiences. I translate this to fitting the mission and vision of the organization to the psychology of the buyer. The better the fit, the greater the growth opportunities.

Aligning the product and the job to be done: When the job is attached a purpose brand you have balanced Customer Equity with Customer Delight.  We live in a time where the opportunity to make this work and improve the odds of success are better than ever. There’s no better time than to start now.

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The future of manufacturing, distribution sales and marketing in the age of disruptive innovation

Inspired by some of the conversations I’ve recently had, I thought I would share some insights related to this case study and how manufacturers are thinking about 2 problems they are facing:

  1. Disruption and their innovation falling into the hands of cheap competitors
  2. The disappearance of the old school distribution channels

Both of these things (and others) at once spells doom for those who can’t adjust.

What’s hard to reverse engineer by competitors may be a means to prevent disruption from them.  Understanding that certain places and types of organizations cant follow you in certain areas.  For example, brand, social and tribe building is not well understood in certain places.

Manufacturing and marketing often don’t go hand-in-hand. Manufacturers are very good at building things and locating distribution channels, calling it a day but what if the product never really ‘leaves’ the factory so to speak.

Rory M McDonald The esteemed Harvard professor recently completed an exceptional case study on this subject matter which should be inspiring and telling to manufacturers everywhere.

In 2018, Henri Seydoux, CEO and Founder of Parrot, believed that his company was at an inflection point in its history. Parrot had been a European leader in consumer electronics since the 1990s, first developing Bluetooth kits for cars before moving on to electronic toys and, significantly, the AR Drone in 2010—a remote-controlled quadcopter that was way ahead of its time. In the years that followed, Parrot’s sales volumes and popularity quickly increased. But new players were entering the market. Giant Chinese rival DJI, in particular, aggressively lowered its prices, forcing weaker companies out of the market. If Parrot was to survive the shakeout, Seydoux would have to figure out how to compete in an industry where even well-capitalized companies were collapsing. The questions that he faced were both strategic and urgent. Where to compete and how to win?

https://www.hbs.edu/faculty/Pages/item.aspx?num=56303

Manufacturing is a very difficult endeavor but integrating modern ways to create a tribe or marketplace around your product creates a defensible layer that is hard to prevent.

Here’s an example. Let’s pretend we have a retail product that is used to look for things. I’ll leave it at that.  When you think about the jobs to be done it’s not really looking for things, it’s creating the opportunity for people to socialize with one another, compete and form relationships about the unified concepts of hunting for objects. This particular piece of hardware is almost like a real world way of doing Pokemon Go combined with hardware and a marketplace. Now imagine that if you would integrate an app with the product itself and then further establish a way for a marketplace to thrive.  Hunting for things takes a) a place to hunt (sell side) and a hunter (buy side) that is integrated by the hardware itself (no, this is not about hunting animals). Now you have built a tribe that’s connected to the hardware, to your way of distributing that hardware, back to the manufacturer. You know everything about how the products used, how to facilitate further usage, how to make that usage a lot more entertaining and remove a lot of the friction from how all of that happens. Why would you not want to do that?

Often the problem is manufacturers think to just extend the product through app development, not socially connect the product to the customers and adjacent markets.  If you can do this, you create brand value that can be monetized. 

In the example of the Parrot drone case study, drone manufacturers should think about their tribe and how to integrate that tribe to the product, back to the manufacturer.  If you’re looking for multiples, for true growth, and you don’t want to put up constant innovation that is just torn apart by ruthless competitors, you better get innovative beyond the obvious categories. If you’re looking for incremental efficiencies from the world you know, it’s just a matter of time before those competitors outmaneuver you at a cheaper cost. That’s not innovation and it’s not the future.