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good morning good afternoon and good evening um i'm barry muller filling in for gideon thomas on this week's revamp podcast um i wanted to introduce our listeners uh to our guest uh martin fleming chief revenue scientist everest um he does many things other things besides for that has a pretty um interesting background but i'll let martin take it from here to give us a little bit more information about his background so thanks barry it's great to be with you today that is correct i do have the role of chief revenue scientist with varicent and really what i am asked to do is to help bring together the transformation that we see in the sales process verison as you know is focused on sales performance management and really the intersection of that transformation with data science and increased analytic capabilities that we now have particularly because the sales process and sellers generate so much data on their own it's it's a very rich and fruitful space to help improve the productivity of sellers help sellers improve their income help sales leaders be more successful and help business leaders achieve their financial objectives so it's my role is really at the intersection of data science and uh business process transformation amazing so i love that trying to help others be more successful uh through data and ai um that's really cool and then uh before this podca uh before we start recording this podcast you're telling me a bit about of some of your other experiences um so yeah so i uh spend a significant portion of my time with veracent but also uh spend uh a great deal of time uh working uh as a research fellow with the productivity institutes a consortium of eight universities in the uk uh all of whose names folks would recognize cambridge oxford king's college london school of business that's the linda school of economics etc funded by the the government uh over five years looking at the issue of productivity which is a kind of a nebulous concept to most folks but really where we're focused is trying to understand not only for the uk but for the developed world generally what the requirements are to be able to realize more rapid growth more equal distribution of income [Music] and really a more res more successful and responsive economic system than we've seen over the past couple of decades um so not surprisingly uh you're gonna you're gonna find out that uh the the work that i that i do generally in data science technology economics all comes together on both sides of my uh of my life here um so we can certainly be uh be very interested to uh to talk further about that work it really builds on the 20 years that i spent at ibm the last 10 of which i was ibm's chief economist and chief analytics officer and it's become in the u.s certainly the practice to integrate or bring together data science and economics a number of years ago four or five could be six years ago now there were 20 or 30 of us who began meeting uh in the silicon valley area and we have a now have a meeting scheduled in two weeks in seattle there'll be 400 attendees so this space of bringing together economics and data science in the technology industry now beginning to spread to other industries as well uh has been a rapidly growing space so that's uh that's where i spend uh spend my life right that's awesome uh and it's really cool that it gets to encapsulate it the things that you enjoy doing um that's awesome and then so you mentioned that there was um three things that that the research you guys are doing is one productivity so i think that's interesting because you could do many different things to bring out growth you could do many different things to having a successful growing economy but you're focusing on productivity correct why is it specifically productivity what does that mean to us in the context of all business or and of all even anything uh not outside of business in addition to yeah that's a great question um you know we use the economists use the term productivity almost reflexively uh and uh have an intuitive understanding um to those not in the profession the term sometimes means uh work harder work faster and you know the sort of charlie chaplin on the assembly line image and that's really not uh what we mean when we use the term productivity what we're really talking about 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 um let me give you one or two examples um that that should should uh hopefully will be a good illustration much of what we do in our economic lives these days is not in the manufacturing sector it's not on the assembly line but it's we provide services to each other and many of us will pay quite handsomely to have good quality high level service a number of years ago a simple illustration is you know we have financial services that are provided via what at the time were thought of as stock brokers uh in individual trades increasingly over time we've seen organizations like charles schwab and others create really holistic service capabilities to be able to provide investors individual investors with a a portfolio of capabilities to be able to grow their their income in their wealth without having to be an expert on every stock that's issued on every stock exchange that has has over time uh evolved into uh organizations like vanguard infidelity where 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 where there's new sources of value that's being created that's generating benefit of income and wealth to to the individual investor that wasn't available years ago another great example that i always think about is you know what we've seen evolve in in recent years in the airline industry we have new airline models with for example in the u.s southwest air where a completely different model of serving uh travelers making travel available where it otherwise wasn't um and so that's that's another uh source of value that didn't exist so it's around innovation creativity new value and all of that gets measured in the in what economists refer to as productivity the value that gets created per uh generally per hour of effort per worker um and and that and there's a expression that economists use uh paul krugman made famous uh uh productivity uh in the long run uh isn't everything but it's almost everything um and and that's that's that's the source of income uh and wealth okay cool i love that um and thanks for elaborating on that so just to even break it down one step further so with the finance example economists have now i and i i want to focus on the word measured the effect of of all these efforts of uh charles schwab of vanguard with bringing their index funds and then even maybe even robin hood which recently ipo then and now um brings a whole different type of user where people can just um be in their bed and start investing easily without even realizing it so that's super interesting and then um i guess in the beginning you even reflected on that it's reflected also with technology which i guess could be hinted about with robinhood but um even um technology and sales productivity uh maybe you could give me uh and we talked about the fourth um the fourth industrial revolution maybe you could get give us a little bit more information on where where um some of your research does with technology and sales productivity sure sure so certainly sales productivity is one of many business processes that's really in the very early stages of adopting uh many of the capabilities that are now becoming available uh over the course of 20 or 30 years uh computing uh has become ubiquitous uh and cheap uh and now with the advent of uh cloud uh cloud model cloud infrastructure uh available just about everywhere uh so both computing and storage uh really make the um have created this software as a service industry uh to be able to provide software uh to for almost any business process so um you know this is the this is the outcome of a a long period of innovation and investment uh much as we've seen historically there are some some historic parallels which are quite useful in understanding the potential and because we're talking about the future i say the potential the probability uh of seeing some greater success as we go forward you know if you go go back um to the beginning of the industrial era we've seen a period where initially [Music] steam and water power converted economic activity from what was very much of a manual process to a bit more of a manufactured process uh workers at some point learned that they weren't beholden uh to uh to a to a boss if you will but they could find new jobs and change jobs and increase their salary and wages by uh having their skill competed for in the open market um as we uh as the developed world went through the period after the second world war um the uh what what we think of as the manufactured manufacturing sector the the assembly line driven by fossil fuels uh became the the driver of growth uh and workers and management and government work together to provide a new new framework for workers uh and and labor um and then by the 1970s we began to see electronic uh technology appear and evolve and now we're going through a similar transformation that was where the 2008-2009 financial crisis was a was a very important turning point where i think we're now going to find that the 2020 2021 pandemic is is going to add to the pressure of transformation but if uh if we see some of the uh economics play out as we have in the past there's a reasonable probability that uh we're gonna see some very deep and fundamental transformation in how 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 uh 200 years yeah so thanks martin uh for sharing that um i wanted to ask have we seen um with the recent pandemic or our current peridot excuse me um that innovation has been even spurred quicker than uh past uh catastrophes whether it be the 2008 financial crisis or a different type of crisis well you're right there's been a a um there are a lot of financial crises in history but there have been three or four that we consider global financial crisis there have also been a number of pandemics both the financial crises and the pandemics have been associated with very significant transformation in activity not surprisingly from in terms of financial crises because balance sheets get get cleansed all of the bad assets disappear and um then so that investors are positioned to take on better and more meaningful investments pandemics uh interestingly enough i think as we all probably have realized create a certain psychology uh 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 and workers question uh their careers question their uh how they're working and that drives further change however i would my observation is is that the changes that we've seen thus far are really only i would say maybe only the beginning or not perhaps even the beginning the the increased use and utilization of e-commerce really is just a continuation of what we've seen over many years already now it's been utilized at a much greater pace much greater rate uh but it's it's it's what changes that were in train uh for for years likewise working from home the other big trend uh didn't start uh 18 or 20 months ago it increased in intensity but those are just two of two changes in economic activity and business process where we're very likely to see many many more come along as a result as both businesses and workers behave uh in a fundamentally different fashion uh as we go forward yeah know that uh totally makes a lot of sense maybe you could many of our listeners are revenue operation professionals or sales leaders maybe you can give a concrete example of recent research either from the pandemic or even from beforehand that might be interesting to them yeah now we certainly we see the sales profession changing and changing rapidly and it's a great example of a business process uh that's going through significant transformation many of the processes that sales leaders have to oversee and lead for example how territory sales territories are created how quotas are assigned are are now in a position where all of the manual effort uh that in the past has gone into that is is quickly being replaced in an automated fashion and it's not automation for the sake of automation it's automation that results in uh more efficient and effective sales territories and in greater efficiency uh by the sellers um so it's an opportunity for sellers for sales leaders for for business leaders generally to to uh to benefit financially um and the these are our spaces where in the past there has been relatively little innovation and now we're in a position where we can we can we can introduce some significant changes and really improve um the the um the lives so to speak of sales leaders yeah no that makes a lot of sense i'm trying to understand with that does that innovation being spurred from uh the pandemics that innovation being spurred by um startups resources now um not being able to work on bigger projects so they have to focus on more niche projects so now they can focus on sales because mobile is 10 years over or it's since it started really going um big yeah so i would i would say all of the above certainly with what the central banks of the world have done of providing an enormous amount of capital i mean we've seen what what's happened to the balance sheets of central banks enormous amount of capital has been added all of that capital now is uh flowing through the financial markets it's certainly available from uh from venture firms from private equity firms in various different forms so so certainly the the the inexpensive uh availability of capital is a contributing factor you're right that the um the advent of mobile devices over the past 15 or so years i guess we're almost getting close to 20 years right of the of the invention of the iphone that in some respect changed everything is making making the use of these tools at the user level much more readily available and you know i wouldn't i would i don't necessarily think of um sales performance management as a niche space as much as one of many business processes that are now going through some of these changes that um that the technologies made available that the availability of capital has made available um and uh and certainly to some extent you could say certainly the the pressures created by the pandemic have spurred uh at a at a faster pace yeah no that makes sense um and then i guess um if you will that the pandemic has also changed the need for some of like territory planning because people weren't flying to places so then things needed to be re-allocated or absolutely no no question about it the ability to understand relationships that sellers have with clients the existing relationships that we want to be able to maintain we while at the same time being able to bring in new opportunities into a sales territory that in the past you're right may have required expensive travel now is now is available that hadn't been the case in the past so that creates a better match an opportunity to better match the skills of the seller with the need of the client and and allows for the expense uh to be managed in a little bit more effective way so that trade-off between skill and location uh has become more uh more effective and the trade-off between managing existing client relationships but balancing territories at the same time has become a little bit more manageable with the tools that are being created so across both of those dimensions as a place where sales leaders now find that they have a greater ability to deliver productivity and efficiency for their sales organization yeah makes sense so if i'm a sales leader how i think a lot of what we just spoke about is the trends the macro if you will if i'm a sales leader what from your research can i take to maybe make myself a better sales person yes i can use technology to make myself more efficient is there something else that i can also gain from some of your research well i guess the other space is around what we think of as 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 which in our research we have found is not wrong but it often is a little bit too narrow so that the opportunities that uh that sales leaders assess as being likely to close uh maybe a 60 chance of closing a 75 chance of closing actually has a 90 or a 95 chance of closing and likewise the opportunities that they feel like well i'm not so confident about this may not close you know is really a a 10 chance or a zero percent 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 that's where the the more sophisticated modeling helps not only to provide a better view of the opportunity the outcome of the opportunities but to provide a better forecast as well for sure let's let's take that even one step deeper i'm like thinking like my prior experience is like um sometimes i make opinions based on the data that came from my experience but like i'm not in sales but i you know i do some business development here and there at past companies and even um winning internal marketing conversations uh for the company but um my personality also might be different than my salesperson personality or the person under me so that could also bring some biases has there been any research around that specifically yeah you know we as humans we all want to reduce things to rules of thumb you know based on lessons learned and that's helpful um but the rules of thumb change markets change competitors change products change and so we have to be continuously updating those rules of thumb and that's really what the machine learning and artificial intelligence modeling does for us it helps us to stay current in terms of those percentages or those ratios that we're applying based based on our prior experience it gets even worse when these rules of thumb get baked into organizational behavior you know 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 uh while there's massive changes over that time in a marketplace so the the machine learning and artificial intelligence really is a way of continuously updating uh the empirical estimates that are that are being produced by the data and therefore giving you a better view of uh the opportunity cool and then when you reference machine learning ai is that going as deep as deep learning um or is it even a higher step-up yeah so so strictly speaking deep learning um will go beyond just uh available um numeric data to to vision to text uh in particular um and and and typically requires vast quantities of data because you're solving these neural network models at many different layers now most of these business applications are not yet at the point to be able to use deep learning however uh we are beginning to see some um for example imagine uh for medical devices uh you're inspecting uh a medical medical device which becomes very important if you're going to insert it into a person right and so often times you have a large number of quite skilled workers who are part of the inspection process while with the vision technology that we have available now in the artificial intelligence models the there's a great deal of uh prediction that the that the deep learning model can do of finding a potentially defective advice defective device that then only there's only a smaller subset of the product the actual products that have to be inspected by humans so so there are beginning to be those applications but again going back to our fourth industrial revolution discussion we're in the early days where you know we're talking about a 20 30 40 year period where all of this capability becomes available and as workers we see our skills being transformed into other job roles right oh that makes sense cool now thanks for explaining a bit more about deep learning yeah so i guess um here maybe i'll ask you a question or two about your time at ibm and then uh we'll wrap it up i'd love to know um two things and you can in any particular order one what was the most surprising thing about either research findings from there or even your experience there as um since you were there for so long and then um on another thing is what thing consistently stayed the same um you were there for 20 years what what on day one was the same as on on well 365 times 20 days now you know i think ibm has a strong culture um around um i want to i want to say learning the intellectual content and capability uh certainly the research organization has for decades um certainly been very productive and highly regarded and that continues to be the case so the the the culture of uh learning insight and being able to produce new insights and new approaches is one that has been maintained consistently and continues to be quite valuable intangible asset uh for ibm um you know i think one of the i had a i guess i wish they have a couple of interesting experiences to share one would be around um in living in a large organization such as ibm and it's the case in others um over time one learns how to manage almost anything uh effectively um because you know the the management the management system that's required uh is relatively complex but you get a great deal of experience being able to to pro provide management and more than management i would say leadership across a broad set of capabilities in a broad set of teams and i probably hadn't thought a lot about that prior to joining ibm um i guess secondly uh topic you and i have touched on a bit uh is around diversity um you know you the the workforce is very diverse um and you learn that um it's the it's the um i was going to use the word diverse it's the uh this the broad set of points of view that we all bring from whether it's 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 and those differences as they come from our life experience is what allows uh innovation to be so effective and so productive um and it probably ties into your original point what's what's you know part of the the intellectual and product success of ibm is tied really to the to the diverse uh population uh of us all bringing uh many different points of view cool love that um so my final question that i asked all my guests um what's your favorite book and why oh well my new favorite book uh is holding up my uh my my mac here my my colleague diane coyle from cambridge just has a book called cogs and monsters uh where she uh spends uh all of her all of her effort um critiquing the economics profession um so she's done a terrific terrific piece of work um and i've just begun going through it but it's uh it's it's become my new favorite book love that all right well thanks again martin and thanks to our listeners uh see you guys next week and martin looking forward to staying in touch thanks good bye [Music]