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31 min 
Martin is also a research fellow with the Productivity Institute, a consortium of eight universities in the UK, including Cambridge, Oxford, King’s College, and the London School of Economics. They look at the issue of productivity, trying to understand what the requirements are to be able to realize more rapid growth, more equal distribution of income and a more successful and responsive economic system.
He spent 20 years at IBM, the last 10 were spent as IBM’s chief economist and chief analytics officer. Over the past few years, it’s become a standard practice to integrate data science and economics, especially in the technology industry. And, now it’s beginning to spread to other industries as well.
We asked Martin why his work in economics focuses on productivity. He shared that economists use the term productivity almost reflexively and have an intuitive understanding. To those not in the profession, the term sometimes means work hard and work faster, and the sort of Charlie Chaplin on the assembly line image. But, what it really means is the effort that we make as individuals and as organizations to create new and greater sources of value. Value that perhaps hasn’t existed in the past, or perhaps can be improved in the future.
Martin gives the example in the financial services sector. A number of years ago, we had financial services that are provided via stockbrokers and individual trades. Increasingly over time, we’ve seen organizations like Charles Schwab and others create holistic service capabilities to be able to provide individual investors with a portfolio of capabilities, to be able to grow their income and their wealth without having to be an expert on every stock that’s issued on every stock exchange. Over time, that has evolved into organizations like Vanguard and Fidelity, where that value is now being created by providing a broader range of services. So, that’s a measure of productivity in the financial services market – new sources of value being created that generate a benefit of income and wealth to the individual investor that wasn’t available years ago.
We’ve also seen the airline industry evolve. They have new models of serving travelers, making travel available, where it otherwise wasn’t. That’s another source of value that didn’t exist. So it’s around innovation, creativity, new value, and all of that gets measured in what economists refer to as productivity, the value that gets created per generally per hour of effort per worker.
There’s an expression that economists use that Paul Krugman made famous, “Productivity in the long run isn’t everything, but it’s almost everything.” And that’s a source of income and wealth.
Sales productivity is one of many business processes that are in the very early stages of adopting technological capabilities. Computing has become ubiquitous and cheap, and cloud infrastructure is available just about everywhere. So both computing and storage have created this software as a service industry to be able to provide software for almost any business process. This is the outcome of a long period of innovation and investment.
There are some historic parallels that are useful in understanding the potential and the probability of seeing greater success. If you go back to the beginning of the industrial era, there was a period where initially steam and water power converted economic activity from what was a manual process to a manufactured process. Workers at some point learned that they weren’t beholden to a boss if you will, but they could change jobs and increase their salary and wages by having their skill competed for in the open market.
As the developed world went through the period after World War II, what we think of as the manufacturing sector, the assembly line driven by fossil fuels became the driver of growth. Workers, management, and government worked together to provide a new framework for workers and labor. And then by the 1970s, we began to see electronic technology appear and evolve.
And now we’re going through a similar transformation. The 2008-2009 financial crisis was a very important turning point similar to how the 2020-2021 pandemic is going to add to the pressure of transformation. But if we see some of the economics play out as we have in the past, there’s a reasonable probability that we’re going to see some very deep and fundamental transformation in not only how work gets done, but in the nature of economics as we go forward, much as we’ve seen in three occasions over the past 200 years.
We asked Martin where he sees the COVID pandemic causing faster innovation than the 2008 pandemic or other crises in the past. He shared that there have been many financial crises in history, but there are three or four that are considered global financial crises. There have also been a number of pandemics, and they have been associated with very significant transformations in activity. Not surprisingly, in terms of financial crises, because balance sheets get cleansed all of the bad assets disappear. Investors are then positioned to take on better and more meaningful investments.
Martin shares that pandemics create a certain psychology. There’s a virus that’s unseen, there’s a disease that’s feared, and that causes workers in business and businesses and governments to react as we’ve seen. And workers question their careers, question how they’re working and that drives further change. However, the changes that we’ve seen in the increased use and utilization of E-commerce are just a continuation of what we’ve seen over many years already.
The other big trend, working from home, didn’t start 18 or 20 months ago, it increased in intensity. But those are just two of two changes in economic activity in business process. We are very likely to see many, many more come along as a result, as both businesses and workers behave in a fundamentally different fashion as we go forward.
Martin shares that the sales profession is changing rapidly, and it’s a great example of a business process that’s going through a significant transformation. Many of the manual processes that sales leaders lead, for example, quota management and how sales territories are created for the sales team, are now being automated. And it’s not automation for the sake of automation, it’s automation that results in more efficient and effective sales territories and in greater operational efficiency by the sellers.
This transformation is an opportunity for sellers, sales managers, and business leaders to benefit financially. And these are spaces where in the past there has been relatively little innovation, and now we’re in a position where we can introduce some significant changes and really improve the lives of sales leaders.
We asked Martin what is spurring this innovation. He says the central banks of the world have provided an enormous amount of capital that is now flowing through the financial markets. It’s become available from venture firms, private equity firms, and various different forms. So, the inexpensive availability of capital is a contributing factor to innovation. Also with the advent of mobile devices over the past 15 to 20 years, tools have become more available at the user level.
Martin says sales performance management is one of many business processes that are going through changes made possible by technology and the availability of capital and spurred on by the pressures of the pandemic.
The pandemic has also changed territory planning because people weren’t flying to places and territories needed to be reallocated. While maintaining existing relationships with clients, new opportunities have become available to a sales territory that in the past may have required expensive travel. So that creates a better match and opportunity to better match the skills of the seller with the need of the client and allows for the expense to be managed in a little bit more effective way. So that trade-off between skill and location has become more effective. Sales operations leaders now find that they have a greater ability to deliver productivity and efficiency for their sales organization.
We asked Martin what his research says about the use of technology to improve sales efficiency and make more informed decisions. He refers to revenue intelligence – the ability to assess opportunities, wins or losses, what the probabilities are, the ability to forecast sales, and the ability to assess the performance of sellers. All of that has been done by sales leaders historically; every sales leader in the world is assessing their opportunities. But, they’re doing it based on their own experience and their own intuition. In Martin’s research, they have found that this is not wrong, but it often is too narrow. So, the opportunities that sales leaders assess as being likely to close, maybe a 60% chance of closing a 75% chance of closing, actually have a 90 or 95% chance of closing.
And likewise, the opportunities that they feel like, “Well, I’m not so confident about this may not close,” is really a 10% chance or a 0% chance. And why do those probabilities matter? They matter, because when you’re trying to estimate, or you’re trying to forecast revenue, you have to assign the correct probability to get to the right revenue forecast. So, that’s where the more sophisticated modeling helps not only to provide a better view of the outcome of the opportunities but to provide a better forecast as well.
We asked Martin about personal biases that sales reps bring to their role and if there’s any research around that specifically. He shared that as humans, we all want to reduce things to rules of thumb based on lessons learned and that’s helpful, but the rules of thumb change, markets change, competitors change, and products change. And so, we have to continuously update those rules of thumb. And that’s really what machine learning and artificial intelligence modeling do for us. It helps us to stay current in terms of those percentages or those ratios that we’re applying based on our prior experience.
It gets even worse when these rules of thumb get baked into organizational behavior. We always allocate so much revenue to this, or always allocate so much revenue to that or we always expect some certain outcome. And in some organizations, you can have the same practice going on for 10, 15, 20 years, while there are massive changes over that time in a marketplace. So the machine learning and artificial intelligence really is a way of continuously updating the empirical estimates that are being produced by the data, and therefore giving you a better view of the opportunity.
Martin shares that IBM has a strong culture around learning insight and producing new insights and new approaches. This part of their culture has been maintained consistently and continues to be a valuable intangible asset for IBM.
He shares a couple of interesting stories of his time at IBM. Living in a large organization such as IBM, over time one learns how to manage almost anything effectively. The management system that’s required is relatively complex, but you get a great deal of experience. He learned to provide management and leadership across a broad set of capabilities and a broad set of teams.
Secondly, the workforce is very diverse and you learn that there’s a broad set of points of view that we all bring from different geographies, different races, different religions, different ethnic groups. And that’s what adds to the innovation in creativity. We’re not all bringing a similar perspective, we’re bringing different perspectives from our life experiences. That’s what allows innovation to be so effective and so productive. The intellectual and product success of IBM is tied really to the diverse population of us all bringing many different points of view.
Martin also shares that his new favorite book by his colleague Diane Coyle from Cambridge, called Cogs and Monsters, in which she critiques the economics profession.
