By Anirban Kundu. This post originally appeared here.
Much has been said about the value at stake and new growth opportunities presented by the Internet of Things trend. A Cisco estimates puts this at $ 14.4 Trillion opportunity where as a new McKinsey survey values this around $ 6.2 Trillion by 2025. One thing which comes undisputed from various reports across analyst’s community is the significant addition to the global GDP, trade volumes and new opportunities which would be created across sectors and industries. Most reports in unison claim the benefits of the Internet of Things and the far reaching consequences this would have for the city we live in, the buildings we work and live in to the vehicles we drive. Every aspect of our experience with the physical world would be re-imagined from the way we work, our shopping experience, our medical services to the purchase of the insurance and banking services.
In midst of all these far reaching consequences lies the biggest dilemma for the early adopters of Internet of Things. The promised value seems to be bit more elusive and early adopters still have not found the golden bullet to unlock all the treasure trove as has been outlined in the research. While we are confident about the promises of 2020, the IOT early adopters working in 2016 seems to be in for a “cognitive dissonance”. The journey to the value realization is still more distant and needs some fundamental restructuring of the existing business processes and industry structure as it exists today.
In this blog I intend to take a detailed look at the value realization dilemma with concepts from Economics and Analytics and chart a detailed path to the all elusive value realization. This would lay the foundation of a “Business Value Calculator” for the IOT scenarios which can be adopted by various entities to realize the potential of IOT. At the onset we need to reexamine the aggregate consumer demand in the context of Internet of Things.
The Promise of the Infinity:
The “Consumer Demand” curve needs to be revisited in the context of Internet of Things to bring fore the “Promise of the Infinity”. Today our industry structure and the cost of production imply a physical limit on the profitable supply of the aggregate quantity demanded and is limited by the equilibrium quantity arrived at by the intersection of the supply and demand curve. As can be seen in the Figure below there are 2 major opportunities which has not been part of the revenue for the company namely – consumer surplus and the area of the curve beyond the equilibrium quantity.
Interestingly enough the area beyond the equilibrium does not even have a mention in economics literature due to constraints of profitability. However, in the context of Internet of Things this region which till now has not been accounted in any financial calculations would be critically examined and holds the key for the promise of the infinity.
Fig 1: Consumer Demand Curve/Equilibrium Pricing
Business’s today are based on this demand supply structure where we have spent elaborate efforts to reach the highest possible quantity demanded and continuously worked towards decreasing the price and bringing more customers into the fold. However as with the physical networks this limit is still a finite limit and as such we never had to explore the “fat tail” of the consumer demand curve. This however is changing with the new business models where products are being offered as services. This fundamental transition has now liberated the current constraints on the product pricing and opens up the “Promise of the Infinity”. This coupled with the power of the network has now made it possible for the ecosystem to drastically bring down the prices of the products by converting them into usage based services.
With new pricing structure and the offering of the products as services we need to reexamine the demand curve being the equilibrium previously set due to physical constraints. The new value is now added by the large number of quantity demanded in the calculation of the value captured by the enterprise. While we see the prices of the services driven down we more than compensate this decrease by an exponential increase in the quantity demanded at the price. This open up 2 interesting analytical scenarios first being the “price elasticity” analysis of the consumers and the second being resource usage analysis.
The Power of Exponential
We are now in the era of transition where we are set to see that more and more products would be offered as services and as such we are moving to a completely new paradigm of computing the quantity demanded. In the earlier figure where the limits to quantity demanded were also bound by the limits of affordability. There is a finite limit to the number of the people who could afford to “buy” a Ferrari or the most expensive jets. On the supply side we also would have the limits on to the units produced profitably. This has a fundamental change in the price elasticity of the products v/s service.
As the product purchase is bound by the physical limits there is considerably higher price elasticity than the price elasticity of the “products as a service”. This is a fundamental change which changes the slope of the demand curve and makes it much flatter in case of products as services and hence increasing the quantity demanded exponentially.
Earlier the revenue recognized by the company was at the time of the purchase and additional services paid by the users. In case of the product as services we would convert one time product cost into usage based pricing and this would imply that the number of transactions in case of the “products as a service” is exponentially higher than the number of products sold.
In a resource sharing paradigm the quantity defined would be based on the number of times the service is utilized at a reduced price as compared to the outright purchase price. This coupled with the net new users of the services takes the number of transactions as an exponential of the previous constrained quantity supplied.
Fig 2: An exponential increase in the number of transactions resulting from the new business model of products being offered as services
This is the foundation to start the definition of the IOT Value calculator. The final revenue increase is produced by the interaction of the increased quantity demanded and the reduced price of product when offered as a service. In the next blog we would illustrate a more analytical treatment of the difference in the price elasticity between the two models. Also the usage metrics analysis based on the customer preferences. As in evident in the revenue calculation we have 2 exponential effects against the substantial decrease of the product price. Considering the nature of the inelastic demand curve for the “product as a service” we have the quantity effects far outweigh the effects of the price decrease. A mathematical treatment is available on request.
The analysis therefore lays the foundation for unlocking the elusive value of the IOT. Here we define this from an economic perspective and a follow up paper would be published where a company can simulate the usage behavior, price elasticity and increased number of transactions.
Finally the appeal of Consumer Surplus and Perfect Price Discovery
This is the sweet spot where advanced analytics meets the Economics to present the additional opportunities of mass personalization. We have seen the value which is captured moving down the “fat tail” of the demand curve. Advanced analytics through segmentation, clustering and perfect price discovery helps us to transform the consumer surplus into economic value.
While the demand for the product as a service would gather momentum, we would still see the need of mass personalization being driven by the ability of the enterprises to transform their manufacturing facility to enable lot size 1 production. Harley Davidson had cut the lead time in the development of the customized production to less than 6 hours. This leads the fragmentation of the existing business models fracturing along two paths- one path to capture the high value consumer surplus through value added personalized offering and on the other side we would exponentially increase the number of transactions being offered at a lower price made possible orienting the product offering as services.
With advanced techniques in customer segmentation and the availability of personalized data availability per user we now are able to offer personalized products to translate the consumer surplus to economic value. While the traditional pricing strategies related to segmentation to offer group, channel or regional pricing have been employed successfully in the past to capture more of the consumer surplus, there were still potential to capture additional value specific to individual users. “Mass personalization” would help to transform more of the consumer surplus into economic value.
Bring in the additional value of the consumer surplus and combining it with the value based on the products as a service companies would be able to significantly extract the elusive of the IOT and set us on the path to create an Internet of Things “Value Calculator”.