How do network orchestrators like Flipkart, Uber add value for customers?

In an earlier post, we looked at how network orchestrators like Uber, Zomato and Facebook see exponential increase in connections as they add more participants. There is clearly tremendous value in being a first mover and growing market share rapidly, even at the cost of reasonable business economics.

Yet, we also see that none of the networks are really unique – every platform idea has spawned several other copy-cats. Most of the markets are still nascent and have a lot of room for growth, so everyone believes they have a chance at success. Moreover, given the asset-light model of network orchestrators, there are no real entry barriers for a me-too product. 

This absence of competitive advantage is emphasized by the apparent lack of any platform loyalty by network participants. For instance, most customers of ride-sharing services have downloaded more than one app on their phones; likewise, many drivers have signed up to two or more networks. Availability and price seem to determine choice for both sides of the network. A similar situation of bargain-seeking can be seen in e-commerce and real-estate marketplaces. 

As long as the role of the platform is to just aggregate and enable discovery of supply and demand (at no cost to either), there is limited stickiness. The next platform with a slightly lower price or transaction fee will churn traffic to its network. In an extreme but plausible scenario, why wouldn’t the network participants try to disintermediate the platforms? On several occasions, drivers of the ride-sharing networks pass along their business cards, asking to be contacted directly. What would stop the customer from saving a bunch of phone numbers for the promise of a lower price? 

Essentially, how do these platforms add value beyond discovery and aggregation? Let us discuss two major sources of value and differentiation that appear to be working for the successful platforms.

Information

Every time a transaction occurs in the network, the platform gains valuable information that can be used to predict future demand/ behavior. A taxi network that has analyzed demand/ supply patterns can help its driver partners locate themselves at specific locations that increase the chances of being hailed quickly. The network can ensure that all the drivers do not land up at the most obvious hotspots (eg airports) even as customers are waiting elsewhere. Not only does this help the drivers increase capacity utilization, but customers also benefit from faster access to rides. In fact, surge pricing reflects inefficiency in network planning (matching of demand to supply). 

The principle would apply to any of the network businesses. E-retailers can plan inventory and logistics better, even as they offer valuable suggestions to customers on what else they might buy. A social network would be able to match people with other people, and people with advertisers much better. 

Valuable insights about the network can create improved efficiency on the supply side, and customized access and experience on the demand side. 

Risk Management

Any interaction or transaction carries an inherent risk of something going wrong. When it is done bilaterally, each party builds in safeguards to mitigate risk, thus creating inefficiency. If I were to book a cab, I would ask the driver to reach at least half an hour early because I am worried (based on previous experiences) that he would be late. It is inefficient for both of us – the taxi remains unproductive for that time and I might have to pay some waiting charges. Or we mitigate risks by purchasing from well-known sellers (brands) because they offer an assurance of quality. We could have bought a shirt directly, at a lower price, from the contract manufacturer who actually made the branded shirt. 

The network platform, as a third-party intermediary, can take on the responsibility of efficiently mitigating our risk, partly through the information it collects and partly through its own due-diligence. By providing an estimated time of arrival (using location information of the driver and rider), the taxi app gives an assurance of availability. By collecting user feedback ratings, the network builds a self-correcting mechanism of quality. Through physical due-diligence (e.g. supplier verification), and standing guarantee to the fulfilment of the transaction, the platform mitigates risk for all parties involved. 

Assurance of fulfilment, timeliness and quality by the platform can reduce transaction anxiety and increase stickiness amongst network participants.  

There is an Uber of something for almost every industry now. Actually, there are many of them. What will differentiate a successful platform from yet another copy-cat is the ability to use information effectively and efficiently to derive meaningful insights and reduce transaction anxiety.

Srinivasa Addepalli is the founder of GlobalGyan, a management education firm and a visiting faculty at IIM Ahmedabad and NMIMS. He was earlier Chief Strategy Officer at Tata Communications. Twitter: @addepalli