Maintain and extend or create something new - where do you want to be?

 One of my favorite questions when I work with software teams is this:  given a choice, would you rather work on existing systems in a support and maintenance role, or would you rather work on developing or implementing new systems with new technology?  The answers are always the same.

About 30% of the group I'll survey is comfortable with the existing systems and code and is happy extending it and maintaining it.  About 50% of the people surveyed will say they want to either build new systems or implement a new system.  There's almost always 20% who aren't sure.

When I was in software development, I always wanted to be working on the latest technology.  It often felt like working on a platform or programming language for too long would pigeon-hole me and my skills.  Of course, there are still demands for my rusy COBOL skills even today, since may mainframes still run on older technology.  

Some folks are comfortable with the things they know - the tech they've mastered - and they want to work with tools and technology that are familiar and comfortable.  Others want to try out new platforms or languages and have little interest in supporting, maintaining or extending what already exists.  This is a good thing - we need both people to maintain existing systems and technology AND people to explore and develop new platforms.

What this dichotomy fails to recognize is how rapidly the existing stuff becomes a commodity - no matter how comfortable you are with it, no matter how much expertise you have.  Except in pockets where companies or governments are simply unwilling to replace older technology (like COBOL), it is risky to bet your career or company on simply extending or maintaining current platforms.

The implication for innovation

So, why does it seem so different when we talk about creating new products or new services?  It's easy to see why technologists want to work on the new stuff - maintenance and support are boring and not overly challenging, and you can only hope to satisfy existing customers, never wow them.

People who develop or support products or services seem to have different characteristics.  In fact, I'd argue that the numbers are almost reversed.  Only 20% of the people I've worked with in large corporations want to risk working on new products and services.  At least 50% are confident in maintaining, extending and supporting existing products or services.  In this case, I'll attribute the remaining 30% to the "I don't know" category.  Far more people are focused on, and derive value from, extending and supporting existing products, than creating new products.

If you think about this for a second, this is really strange behavior.  Technology is for the most part a corporate COST - technology and IT don't drive revenue.  Therefore, even if new tech is sexy and interesting, there should be a greater risk of trying to work on new and emerging technology that can only represent a new cost to the business with the hope of achieving benefits later.  New products and services, on the other hand, have a short term cost but promise greater returns and increased revenue.  There should be more people betting on the future of new products and services, and willing to stake their careers on developing new products and services, but it simply isn't so.

Why the strange dichotomy?

There are several reasons for the strange dichotomy.

First, we all witness technological change, and see the benefits new technology introduces for society.  We are all capable witnesses to interpret just how much value new technology brings, and conversely we can see how quickly older technologies go out of fashion, and then out of support.  My recently acquired printer no longer has a driver for the latest Windows update.  Losing out on staying up to date on technology risks everything, even if technology has a significant cost and little impact on revenue.

Second, sticking with an existing product that drives revenue and profits, however, is almost always a safe bet,  Even a product that has declining sales and margin is still generating profits, and seems less risky than working on a new product or service that may not be accepted or perform well in the marketplace.

But this calculus is all wrong, because what seems safe (working on extending existing products) will become very risky as new competitors enter, new substitutions emerge.  Our corporate cultures have taught workers to value current, near term revenue and profits even when the medium term outlook is dire.  This is, of course, the fallacy of measuring a business in quarters rather than in years.

Jobs dictum

When Jobs recruited Scully to Apple, he reportedly asked if Scully wanted to sell sugar water or wanted to change the world.  I think this is a question all managers should ask themselves and their teams.  Do you want to maintain what exists, as it slowly declines, or do you want to grow something new?

Just as IT teams have "maintenance" teams and new project teams to focus on both aspects of IT, we increasingly need product "maintenance" teams to maintain and extend existing products and services, and a fully realized new product identification, development and launch team to bring new products and services to market faster.

Do you want to simply maintain and extend what exists, or do you want to be part of birthing something new and incredible?  We need to reframe the power and attractiveness of new product and service opportunity, definition, development and deployment.

You need a red team, not a red pill

 In the Matrix, Morpheus offers Neo the choice of a blue pill or a red pill.  Take one, and you remain as you are.  Take the other, and the scales fall from your eyes.  Those of us who watched the movie or have seen it on ubiquitous reruns, know what happens next.

As an innovator, it would be awesome to pop into a completely different meta-world to understand the hidden workings of the metaverse I just left.  However, that isn't going to happen by taking a pill or wearing a VR headset.  The metaverses we create for ourselves merely build on what we already know - they don't show us the hidden hands and string pullers behind the scenes.  You don't need a pill, you need a team.

Red Team / Blue Team

The idea of a red team (attacker or hacker) versus the blue team (defender or good guy) has become a staple of cybersecurity, but it has an older history than that.  Red teams and blue teams originate from the military, where one team takes on the role of an attacker or proposes a strategy and another team seeks to disrupt or destroy the strategy.

What often happens in an innovation setting where new ideas are presented is that everyone not fully behind or read into a new idea becomes the red team, trying to discover reasons - valid and self-serving - that the idea won't succeed.  In other words, rather than a formal assessment of ideas, most organizations line up the idea to take fair and unfair shots at the idea and the team from every vantage point, making the idea almost impossible to defend.

Why you should consider a red team

Let's imagine, instead, that your innovation team, the people with the great new idea, are the blue team.  They've developed an idea based on a set of insights, voice of the customer work, great idea generation and a lot of testing.  The believe their idea solves an important problem or addresses an emerging opportunity that could create value for the company.  If they've done their job well, they should be able to define their scope, the need, the opportunity and the facts and assumptions they are basing their ideas on.

What should happen next, and rarely does, is the creation of a disinterested red team.  The red team should be presented with all the insights, facts, and assumptions that the innovation team used to develop their solutions.  Then the red team should look for missed signals, incorrect assumptions, optimistic interpretations and other mistakes or errors in the work.  But only using the defined scope, the research and insights, the same data and the list of assumptions from the blue team.

Where innovators go wrong

What a good red team investigation could do for innovation teams is to identify assumptions that are subject to a lot of variation, research that is a bit suspect or limited, unexpected competition or future shifts in customer needs or behavior that were ignored or overlooked.  When the red team operates with the same facts, but different interpretations of the insights, assumptions or understanding of future scenarios, it can create a range of likely outcomes that the blue team did not consider.

In some instances, the red team insights and discoveries will doom the blue team ideas, but not their work.  Instead, new ideas or opportunities will emerge.  In other instances, the red team will validate or even discover new opportunities the blue team missed.  

Running the gauntlet

A fair red team assessment not just of the ideas presented but of the information and scope that led to the ideas is what most ideas - especially transformative and disruptive ideas - really need.  Too often, ideas run a gauntlet of decision makers who have other priorities, leaders who have tight budgets, jealous co-workers who believe the ideas aren't really valid and corporate cultures which prefer safety over change.  Trying to fend off all of these individuals, teams and the corporate culture at large is a daunting task.  Yet doing a good job evaluating ideas and the markets and conditions they will be launched into is vital.

Today, most ideas run an unfair gauntlet of skeptical opponents lined up to knock ideas down rather than adequately test ideas and find issues or challenges.  These "evaluation" processes are often conducted by people who don't understand the original request, lack information on the process and who lack methods and processes for adequately reviewing the idea and discovering both weaknesses and strengths in the ideas.

A small investment creates enormous opportunity

According to a Harvard Business Review article from 2011, entitled Why most product launches fail, over 75% of consumer packaged goods products launched each year fail to achieve event a few million dollars in sales and are considered failures.  Think about the investment to create a new CPG product, develop it, manufacture it and place it into the fulfillment process, let alone find room for it on a retailer's shelf.  For 75% failure rate, you'd think someone would come up with an approach to cut these failure rates by 20-30% at a minimum.

The military uses red teams and blue teams to fight battles on paper, because the cost of a wrong decision in wartime means the loss of too many lives.  Cybersecurity experts use red teams and blue teams to determine how easy it is to steal data from a computer system, in order to better anticipate future attacks and improve defense.

Why can't we innovators borrow a great idea from these examples and dramatically improve the rate of success of new ideas?  After all, good artists borrow and great artists steal...

Implementing a red team review

If you'd like to know more about how to implement a red team review, contact me at innovateonpurpose@gmail.com.  We have used red teams to review, find missing information and to improve and harden ideas.  

The best job to have in the near future - data strategist

 As you know if you follow my blog, I generally write about the intersection of strategy and innovation.  Increasingly, however, we need to invite data into this mix.  As more and more data is generated, it creates new opportunities in the strategy realm and in the innovation realm.  This post will consider the importance of data in strategy development and execution, as well as in innovation.

Past, Present and Future

In the past, data was an afterthought, if we are being honest.  Until the era of big systems like ERP and CRM, most data was recorded manually in ledgers.  Since it was compiled manually, data basically took up space in three ring binders in shelves around the office.  Data was occasionally consulted for reporting or historical evidence, but rarely drove decisions.  Data was really more of a hassle to manage than a benefit to the business.

When larger, integrated systems like ERP entered the business world, this unlocked data from the paper ledgers and placed it in computer systems which often had reporting solutions attached.  It is interesting to note that many of the ERP systems called (and some still call) these functions ledgers.  What these electronic ledgers and the associated databases and reporting applications created was the ability to capture and report data much more easily.  However, a lot of this data was stove piped - the manufacturing floor might have its view of the data, and the marketing team it's view of the data, but the organization lacked good integrated data to report on.

So, data warehouses were created to combine and pre-process data and make it more readily available to people who wanted to combine shop floor data and marketing data into a report or KPI.  That's great, but data warehouses are really only great with structured data, and just as data warehouses became really capable, unstructured data became more important.  I've seen statistics that indicate that 80% of the data companies ingest is unstructured data, which is harder to parse and interpret.  Also seen statistics that suggest that most companies have the ability to access, interpret and report on about 15-20% of the data they possess.  A lot of the data being captured and stored is virtually useless, because it cannot be interpreted or understood by current systems and people.

It's about here that people began to realize that, like the California mountains the 1840s, there was gold in there somewhere.  Data became, and is still becoming, a source of value rather than a problem to be solved.  Now, we need to learn to access data, unlock it, and have it tell it's story to all of us.

Water, Water everywhere

As we move into the future of data as a source of value, we'll need to understand a few things:

 - Where it is coming from

 - How we can best manage it

 - Most importantly, how to extract the value it contains

First, where is it coming from?  Honestly, everywhere.  The digital transformation that everyone was talking about before COVID is arriving.  The Internet of Things that seemed like such a futuristic opportunity is happening.  Billions of devices generating data, some of it interesting and useful, some of it not so much.  Consumers are generating data on social platforms, and if businesses are smart they'll find ways to get consumers to build relationships and exchange data with products and brands.    In the near future, robotics and automation will create data about processes and products.  Finally, and we are nearing this threshold, the data will start generating data about itself.

Second, how can we manage it?  Today, most firms are fortunate if they can adequately manage and interpret 15-20% of their data, and the data volumes and varieties are exploding.  Companies need to start with a data strategy, to understand what insights they need and which data streams can provide the supporting evidence.  What companies need to do is develop a data strategy that supports and enables the business strategy, then put the requisite systems in place to capture, manage and interpret that data.

Timing is also important.  Our traditional way of interpreting data is in hindsight - reports that tell us what we did yesterday, last week or last month and compare to previous periods.  This information is helpful but does not fully illuminate future activities.  Corporations need data about the present and indications about the future as well.  We have to analyze and interpret the data in real time, but also allow the data to predict what is going to happen next.

But what's most important is to extract the value the data contains.  We need to move from being content with reporting last week's sales, or even yesterday's revenue, and move toward what the data tells us might happen and use that insight to take proactive actions.  Some companies talk about being data-driven, I like to think about being led by the data to new opportunities, new markets and new needs.  Most companies are fortunate if they can report on old data, and the data scientists they are hiring are working to create real-time interpretation and some prediction capabilities.  This is where we need to be spending our IT dollars.

What's this got to do with strategy?

So, if you are still with me at this point, you may say - this is all interesting, but what's all this got to do with strategy?  This is an interesting question.  Companies in the past wrote a three or five year strategy and, if the company was lucky, communicated it out to the leadership.  Then the business went on its merry way, mostly adhering to the strategy.  These businesses often did not have data to indicate if the market was moving in a different direction than their strategy indicated.  If there were gaps between the strategy and reality in the market, this was usually discovered two or three quarters later.

Today, we need our strategies to be more dynamic, and based on what data about markets, economies, currencies and other internal and external factors are telling us now, and signalling about the future.  We need to write strategies informed by data, and create strategies that are course corrected by data, and that are regularly testing new hypotheses about the future direction of strategy.  In other words, we need to reject the old view that the world is static and data belongs in ledgers, and adopt the thinking that the world and the markets in it are exceptionally dynamic and data should be used to tell us what's new and what's next.  Companies and executives need to be led by data, not informed or "driven" by data.

What's this got to do with innovation?

Another good question.  What impact will all this data have on innovation?  In my opinion, it may radically change what we innovate and the products and services we create.  First, more data about customers and their needs will allow companies to make better decisions about the products and services they create.  Hopefully it will not mean they abandon Voice of the Customer activities and engaging with customers and prospects to learn their needs.  Data is valuable but we cannot be overly reliant on it in all circumstances.  Further, all this data and our emerging ability to manage it will lead to new products that the data suggest or new services or solutions that are purely informational.

Whereas the light bulb has been the classic symbol for innovation in the past, a symbol for data and how it is put into use and converted into revenue may be the emerging symbol for innovation in the future.  How we develop new products and services may shift from a mostly creative, manual and emergent process to a more automated, still creative but directed process - directed by insights and data.

If all of this is true...

So, if my analysis is true, the best job to have in the future will be a position that makes sense of all the data that is generated, finds the data that really matters and converts that data into information or knowledge that speeds the business up or helps position a business for opportunities as they emerge.  In other words, some form of data scientist or data strategist.  I distinguish these terms because in my experience many people who frame themselves as data scientists are too close to the data - they see trees and not the forest.  What we need are data strategists - people who see the data and understand its implications but have the ability to pull back and see the bigger picture.  People with these skills and capabilities will be able to dictate their salaries and will be in high demand in the coming years, because they will impact the strategy of a business and its product lines or service lines, as well as direct new product development.

Book Review: A new way to think by Roger Martin

 I'm lucky to have the opportunity to read and review a number of books in the innovation and strategy space, and I find many of the books have interesting insights or promote new ideas but often aren't overly actionable.  However, I've always found the insights of Roger Martin useful.

His book - Opposable Mind - is a great book about capturing and merging two disparate ideas or opinions to form new viewpoints, products or services.  New managers need the skills introduced in the Opposable Mind to learn to think more broadly and to combine what may seem disparate or opposing ideas.  It should be a book that all managers read.

A New Way to Think

But I'm here to review his latest book - A New Way to Think.  The book is positioned as a more holistic way to think about and build strategy.  Martin argues in many of the chapters that a number of our closely held beliefs about management are flawed.  He targets a number of key components and attributes in a business and helps illustrate how we should rethink our approach to concepts like culture, knowledge work, talent and more.  The question he asks is:  do your models and frameworks work, or are they limiting your thinking?  His assertion is that if an existing model or framework doesn't work, executives assume it wasn't fully or appropriately applied, and then they attempt to apply the same framework again, only with greater emphasis.  He notes that often, it's not the effort behind the model, but the model itself that is not effective.

Strategy - what's important is what will be true

For example, when writing about strategy, he remarks that "In strategy, what counts is what would have to be true - not what is true".  In other words, we often analyze strategy based on what the current market conditions are, who the current competitors are and so forth.  As a person who works a lot on trend spotting and scenario planning, I can't agree more.  When developing strategy, we forecast the company in the future and need to understand the operating conditions then - in other words deciding what must be true for success in the future, not what is currently true today.  Yet, most executives are very comfortable and well-read on existing conditions and competition and are much less comfortable with future conditions and competition, so the debate over strategy is about current conditions, which are less likely to impact the development and eventual roll out of a new strategy.

Knowledge Work - focus on projects, not jobs

Martin has another chapter on knowledge work, in which he points out that the vast majority of work today is knowledge work.  This of course is not new news, but the way he thinks about it is.  He points out that knowledge work is primarily project based - we create new knowledge and package or use new knowledge, almost always as a definitive project.  Therefore, we should organize around projects rather than functions or permanent jobs.  It's an interesting and valuable idea, if perhaps difficult to implement.

A compilation with great chapters

This book, as it is, is really a compilation of a number of HBR articles Martin has written over the years, and as such has some really great points and chapters, and some that in my mind miss the mark a bit.  The chapters on stakeholders, strategy and knowledge work are outstanding and have great insights and recommendations, while the chapter on innovation I found a bit unfocused and less valuable.

What the book does well is call into question a number of the management philosophies and theories that define how companies are structured, how they go to market and how and where they create value.  The ideas are very useful and coming out of the COVID pandemic and faced with new competition, unfamiliar market conditions (inflation) and other issues, it is probably time for a rethink of corporate strategy and structure.  I'd highly recommend the book and its insights and look forward to using it as a guide with my own clients.