I interviewed Marv Patterson who discussed How Innovation Investment Drives Financial Success in a Business.

 

 

 

 

 

 

Well, it’s nice to speak with you today, Marv.  I’m looking forward to discussing and seeing your presentation on the topic of how innovation investment drives financial success in a business. Could you start by providing a brief background of yourself?

 

I’m happy to be here. Thanks for inviting me to talk today. As for my background, I started out as an electronic engineer and worked up through project management levels.  I joined Hewlett-Packard in 1973, and was with that company for 20 years.  Essentially all of that time was in R&D at one level or another.  I eventually ended up in Palo Alto as the director of a group at HP headquarters called Corporate Engineering.  We transformed this group into an internal consulting service that was responsible for improving HP’s R&D performance worldwide.

 

We were fairly successfully at that for a few years so I decided to show HP’s executives how much we had impacted the company’s bottom line through our efforts. I sent some people out to get the numbers and, when they reported in, we got a rather nasty surprise.  Some business units we had helped improve were, indeed, doing better.  But others, where we had made even more substantial improvements, were doing no better at all.  We couldn’t show any overall improvement in HP’s bottom line.  In fact, there seemed to be no correlation at all between R&D performance and financial success.

 

When we investigated further we found that a business unit’s financial performance seemed to depend more on the level and quality of interaction the local executive team had with their new product program.  Some did really well at this, and others hardly paid any attention at all to new product efforts.  In these business units, that job was generally considered the responsibility of the R&D manager.

 

These differences in performance seemed to depend upon the backgrounds of the executive leaders, their professional education and experience. Further investigation revealed that, in HP’s rather extensive executive training curriculum, no time at all was spent on this key question, “Howshould executives manage their investments in new product innovation to best achieve financial growth?”

 

When we reported these discoveries to HP’s executive staff, their response was almost predictable, “Marv, no one else is working on this issue.  Why don’t you take it on?”  We launched an effort to address this issue, but I left HP a short time later to start my own consulting company and lost track of HP’s work in this area.

 

This question seemed to be central to the success of my own consulting efforts, though, so I continued to pursue it after I left HP, and it ultimately led to development of the Patterson-Hartmann (P-H) model.  The P-H model is an essential part of that package of information that you would like every executive, and every leader of innovation at any level to know.

 

I enjoyed pretty good success with my consulting company, Innovation Resultant International, for 13 years and then closed it down in 2006, thinking that I was going to retire.  What actually happened, though, was that I immediately launched into writing my 3rd book on how to manage innovation.  That has carried me on into my current career.  Among other things right now, I am teaching a course called “Managing Innovation” at Stanford, and using this 3rd book as the text.

 

This is interesting. Can you talk more about what is the Patterson-Hartmann Model?

 

I have a few slides that will help describe the model, but first let me say it verbally.  It’s a description of the generic system that links investments in innovation to the financial performance in a business. Before I go further I should mention that the “Hartmann” in the P-H Model is George Hartmann, a mathematician at Xerox, now retired.  George and I met when my company was helping with the Xerox Corporation’s new product efforts.  The two of us put together this mathematical model over several years in a series of papers on the subject.  It became known in the literature as the “Patterson-Hartmann model.”

 

The Model defines the principles and quantitative relationships that govern the performance of the generic innovation system.  It also includes key qualitative performance drivers that are essential to the system’s success.  Another important aspect of the model, though, is that it is realistic, and aligns well with innovation practices and circumstances that have proven effective in actual practice.  My 20 years with HP and the 13 years working with other companies since then have all helped shape and tune the model.  The model describes very well the conditions, both good and bad, that I witnessed and experienced during those years.

 

This is the generic system I talked about.  It consists of a positive feedback loop up above, and the executive leadership down below that establishes the feedback loop and keeps it moving in the right direction.

 

The system description starts with Customers.  The purpose of every activity and individual at work in the feedback loop is to offer Customerssuch terrific value that they simply can’t resist.  The objective is to induce them to rip their wallets out and send you money in the mail which, of course, creates the revenue stream at the top.

 

This is a generic representation so any business that wants to apply these principles must figure outhowits own business modelfits into this generic system.  In some business models, for instance, the people who use a product or service are different from the Customers who evaluate and pay for it.  In these businesses you need to show the users separately, and understand both customer and user needs along the relevant relationships that exist between these two categories of people.

 

The second element in the system is Operations which includes all of the functions that are required to deliver value to Customers.  In a typical manufacturing firm, for instance, this would be Sales, Manufacturing and Customer Support, and maybe some others.  The objective of this element is to take information about new products and services from the Innovation Engine, and transform it into delivered value.

The third element is the innovation engine.  At this point, most people will automatically think, “Oh yeah, that’s the R&D department.”  But it’s a lot more than that.  As we will see later, innovation of new products or services is an inherently cross-functional effort, and will involve marketing people, business development folks, and even people working in Operations.

 

When these elements work well, value is delivered and the revenue stream at the top is created.  It flows back and funds operational activities, other expenses and taxes.  It also provides ongoing funding for innovation investments which closes the feedback loop.  What’s left at the extreme left is Net Income, a key driver of the firm’s cash flow and shareholder value.

 

The Executive Leadership team includes those people who have span of control over all of the personnel and other resources critical to the feedback loop elements.  In a typical business unit, this might include the business unit general manager, and the managers in charge of R&D, marketing, sales, manufacturing and customer support.  As we shall see below, this team has a number of key roles to play in assuring the success of feedback loop activities.

 

Now we’ll briefly describe operation of the feedback loop and identify three quantitative growth drivers that determine annual revenue growth rate.  The vertical axis in this chart is financial; revenue above the horizontal axis, and innovation investment below.  The scale of the negative axis has been adjusted to magnify the size of investment waves by 10x. Otherwise they would be too small to see.

 

In 1998 a first wave of innovation investment occurs and, in this example, it causes a first revenue wave that begins in 2001, the same year that the investment wave ends.  The red arrows in the feedback loop denote where these waves occur in the system.  The first performance driver, Innovation Gain, is simply the ratio of the revenue wave magnitude to the total investment that was required to create it. In other words, Innovation Gain is the number of dollars of new revenue that is created by each dollar invested in innovation.

 

The next chart shows the effect of introducing new investment waves in each subsequent fiscal year out to 2007.  Each new investment wave is larger than the preceding one by a constant percentage, and creates a new revenue wave that begins in the year the investment wave ends.  Innovation Gain is unchanged throughout. After a startup phase,annual revenues grow at a constant exponential rate.

 

In particular,note the nature of annual revenue and innovation investment in 2004 through 2007, the years where performance is completely stable.  Total revenues for each year include contributions from products that were introduced in the current year, and in the preceding four years.  Total innovation investment includes majorexpenditures for development of new products that will be introduced in the current year.  Also included, though, are expenditures that fund innovation efforts for products that will be introduced over the next three years.

 

This chart format, known as a “Revenue Vintage Chart,” not only shows annual performance, it makes visible cause-and-effect relationships that span many years in a firm’s history.  Early strategic efforts in the beginning of the black investment wave that starts in 2005, for instance, can be seen to affect the firm’s future at least until 2012 when the corresponding black revenue wave finally comes to an end.

A second quantitative growth driver can be defined using this chart.  Innovation Intensity is the ratio of total investments in innovation in any given year to the total revenues received in that same year.

 

One final quantitative performance factor is needed to establish annual revenue growth rate performance, and that is the effective time delay between an innovation investment and the revenue that it creates.

 

The P-H Model provides a way of determining a lump-sum investment that has the same mathematical impact as the distributed investment waveform.  The total number of dollars involved is, of course, the same but the timing of the equivalent investment needs to be properly placed to achieve an equivalent effect.  Likewise, a lump-sum equivalent for the revenue payback can be determined.  The time interval in between is the Turn Time, the effective delay between an innovation investment and the revenue that it creates. Methods for calculating or approximating Turn Time are provided in more detailed explanations of the P-H Model.

 

The relationships of these three growth drivers are shown in this next chart.  The vertical axis is annual revenue growth rate, g, expressed as a fraction.  The x-axis is the product of Innovation Gain time Innovation Intensity.  The curves on the chart show growth rate performance for various values of Turn Time, expressed in years.

 

In the example shown on the chart, Innovation Gain is 12.5 - $12.5 of revenue created by each dollar invested – and Innovation Intensity is 0.12 (12% of revenueis invested in innovation).  The product of these two is 1.5 which becomes the x-axis value of the feedback loop operating point.  Turn Time is 2.02 years which places the operating point almost exactly on the Turn Time = 2 years curve, with just a small offset toward the 3 year curve.  The y-axis value of that operating point is the annual revenue growth rate, and is equal to 0.2225 (22.25%).

The P-H Model revenue growth chart provides the means for quantitative analysis in support of higher quality management decisions. In this case, for instance, if I need to know the effect of a one-year increase in the development cycle, I can just move straight down to the 3 year Turn Time curve and read the new growth rate. The delay will reduce growth rate by almost 10%.  On the other hand, if either Innovation Gain or Innovation Intensity decrease, the operating point for the loop will slide down the Turn-Time = 2.02 curve to a new, lower value on the x-axis, where the reduction in growth rate is readily apparent.

 

Here is a fairly good example of the sort of work that goes on inside the innovation engine. As I mentioned earlier, it involves a lot more than just the R&D department.  Opportunity discovery, for instance should address both markets and technologies, and this will involve market researchers, business development people and R&D folks.  Strategy creation and product concept validation will involve a similar cross-functional team.  Ideally, product development and introduction will involvenot only R&D and marketing personnel, but will also integrate the firm’s operational wisdom gained from experience.

 

A couple of general observations are worth noting at this juncture.  The strategic front-end work in the Innovation Engine is costs relatively little, and yet it has by far the greatest influence on Innovation Gain performance; especially on the size of future revenue waveforms.  Firms wanting to improve innovation performance often get the greatest bang per buck by focusing in this area.  In contrast, the technology and product development work in later stages of innovation consume the Lion’s share of innovation investments, and have an overwhelming influence on Turn Time.  In particular, delays introduced by design flaws or changing product definitions are highly detrimental to Turn Time performance.  In addition, though, theydramatically increase the size of investments needed to get the product out and thereby reduce Innovation Gain performance as well.

 

Executive Leaders have several crucial roles to play in managing Innovation Engine performance. First of all, they guide and inspire opportunity discovery and strategy creation.  They set the strategic intent of the enterprise that helps set the direction of opportunity discovery efforts and keeps them focused on the right questions.  They guide strategy creation efforts, and set high expectations for the results that emerge. They track and monitor technology and product development activities, and see that each team has an abundance of the needed skills.  Overall, they keep the Innovation engine in balance; between strategic and development work, between marketing and engineering, and between short term and long term goals.

 

In addition to the three quantitative growth drivers, there are qualitative factors as well that control innovation performance.  These influence the behavior of the individuals and teams at work throughout the innovation system.  In particular, though, the level of creativity and initiative of innovation professionals working within the Innovation Engine are affected.  These three qualitative growth drivers are illustrated in this diagram.

 

The first is the level of involvement of individuals with their work assignment.  This ranges from a high level, where they are enthusiastic and passionately strive to succeed, to the lowest level, where they are detached from and perhaps even cynical about their assignment.

The second factor is each innovation professional’s feelings of effectiveness at work.  At its highest level, individuals feel fully effective in everything they do.  When they leave for home they are completely happy with what they’ve accomplished, take pride in the progress that was made that day, and know that they are a valued member of the team.  They know that, if they continue to perform at this level, appropriate recognition and reward will follow.  At its lowest level, individuals feel completely ineffective.  Nothing they do seems to make any difference to the success or wellbeing of the enterprise.  In fact, due to various circumstances, much of the work they do may even be discarded or redone.

 

The third factor is the energy level of each innovation professional.  At its highest level, individuals work hard at assigned objectives all day but never seem to become depleted.  They always show up the next day ready to do it all over again.  At its lowest level, most individuals are completely exhausted. Job pressures demand that they work extensive overtime and, it seems like the harder they work, the further behind they get.  Since weekends are consumed with work there is no time to recover.

 

When all three of these factors are at their lowest levels, individuals are working in the lower left corner of the cube and are clinically burned out.  At the upper right corner of the cube, where all three factors are at their highest levels, individuals are fully engaged at work, and able to deliver their best possible results.  Burnout is impossible under these circumstances, and the enterprise is able to operate at “Best of Breed” levels.

 

Once again, Executive Leaders play crucial roles in determining where in this cubical space their innovation professionals are likely to operate each day.  They establish the ground rules that determine the nature of work assignments, and the degree of professional freedom and responsibility that individuals experience.  They set the workloads for individuals by how they staff project teams, and by the number and intensity of innovation programs they have underway in the innovation system at any given time.  A skill set essential to effective innovation leadershipis learning how to read the signs related to employee level of engagement, and then knowing how to manage the innovation system in ways that nudge people toward the Fully Engaged corner of the space.

 

How is the P-H Model Useful?

 

It creates a comprehensive intellectual framework for improving innovation performance.  What I mean by “comprehensive” is that it spans the whole range of important aspects of product innovation in business – the strategic, the engineering, the motivation and morale of employees, and the financial impact of their work.  Above all, it included the executives as part of the system.  My experience as a consultant was that, in many companies, executive leaders really didn’t see themselves as part of the innovation activity.  They felt that was the domain of the R&D manager.  I think that’s true even today.

 

This model highlights common gaps in innovation performance, and their root causes.  It provides quantitative and qualitative principles that improve decision quality.

 

I think one of the most important things that the P-H Model does is provide innovation leaders with kind of a “periscope” that allows them to see beyond their inherent learning horizons.  I think it was Peter Senge that taught us about learning horizons. If something happens geographically too far away, or too far in the future, we can’t discern cause and effect. It breaks that learning loop that enables us to learn from experience.  This model gives people a perspective and some mental models that allow them to see over those horizons.

 

How can this model be used effectively?

 

The most effective way we have been able to apply this knowledgeis to engage our client companies at the executive level, and convince them that this material offers a worthwhile learning experience for their organization. We propose an executive seminar at a very reasonable price that will include not only the executives but mid-level managers and key individual contributors as well.  All of the leaders involved in innovation efforts are invited to attend.  In a more elaborate version of this event, we conduct workshops at key points during the seminar where attendees can immediately begin to discuss what they have just learned, and apply it to their own performance issues.

 

This seminar – workshop version provides anrich environment in which an innovation team can not only learn new innovation principles, but also discover the “low hanging fruit” that exists in their own operation.  These are the opportunities that are not that difficult or expensive to take on, but that can make a tremendous difference in overall innovation performance.  The elements of the model work to show people how things should work.  This highlights the gaps in their own performance, and points to ways in which problems can be easily corrected.

 

Well, thank you, Marv, for sharing on this topic.  Did you cover all of the points you wanted to make?

 

Yes and, in fact, I’m sure I have probably talked too long, and we’ll have to edit this down a bit.

 

 

 

About Marv Patterson


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Marv Patterson

 

President, Dileab Group

 

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