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The Job to be Done of the Service Provider In a Network Business Model

Aroop Gupta, 2/9/2017


We often talk about how firms should focus on Job to be Done of a consumer. The firms that are able to address the Job perfectly, are able to position themselves as purpose brands. IKEA is a good example of this. Today more and more businesses are evolving with a network business model. In all such cases, the business acts as a facilitator between the supplier and the consumer. Some examples are Google Playstore for software, Lending Club in Lending, Uber for Transportation and Amazon & eBay in Retail. With network business models gaining more and more acceptance today, is there a Job to be done of the service provider that we are overlooking.

Let me elaborate this with the story of OLA Auto in the city of Bangalore, India. OLA Cabs Started operations in India in 2010 and by end of 2014 had expanded into 100 Indian cities. Their unique value proposition was to bring in more efficiency in the way commuters booked different mobility options for traveling from A to B. Business model of OLA was pretty similar to that of its US competitor - UBER. OLA was a technology company that connected riders with drivers and made its money by taking a share from the driver’s earnings. However, the only difference here was OLA instead of competing with the incumbent, identified an unmet job of its competitor and helped them become more efficient.

The transport system of Bangalore and where did Auto’s fit in

Bangalore was (and still is) one of the few cities in India that had good public transport. Just to put some numbers to the claim, as of January 2017 the corporation had six thousand buses carrying around five million passengers every day to different corners of the city. While the fleet of buses covered almost all corners of the city, the last mile connectivity was dependent on three-wheeled vehicles called Auto rickshaw (popularly knowns as Auto). An Auto is a small three wheeled vehicles which may be imagined as a semi-closed extension of a scooter (as shown in figure 1). The single cylinder engine of an auto is slightly more powerful than a scooter and can comfortably carry up to 3 passengers and driver.

Autos were usually hired for last mile connectivity or means of personal transportation where frequency and coverage of public transport were poor. As of 2011, there were close to 125,000 licensed autos plying on the roads of Bangalore for a population of nearly 9.6 million. Given the numbers, one would assume that this was a small number. However given the comparatively higher fares to buses, this mode of transportation was affordable by only a few in the city. This was reflected in a study conducted by the state government where it was concluded that only 7% of the total trips by commuters were by Autos.

The struggle with Autos and the Job to be Done of Commuters

The cost was not the only factor contributing to low usage of Autos. Many Auto drivers refused rides despite the fact that they were bound by law not to do so. Drivers often disagreed to ply by the standard meter rates set by the government and demanded excess fare. They would cite reasons like traffic congestion, bad roads or a broken meter. Because of this, commuters had to negotiate hard for fares before a ride and spend time waiting for some driver to agree before they could get a ride. This was a waste of time and effort especially during rush hours when commuters were hard pressed for time or were exhausted after a busy day at work.

This was a pain point for the commuters while hiring an auto. There was a struggle associated with finding an on demand means of transport at predictable rates. These pain points defined the Job to be Done, of the commuters of having an on-demand public transport at predictable rates. OLA Cabs identified this job and offered a solution that was targeted towards the pain points of commuters.

Enter OLA Cabs

OLA offered a platform where commuters could connect with registered taxi drivers who were ready to ply as per predefined rates set by OLA. While the pricing of these cabs was higher than Autos, the availability on demand and predictable pricing attracted commuter to adopt them as replacements to Autos. In just 4 years since starting operations in Bangalore, OLA had nearly 4000 cabs registered on its platform and had become a purpose brand for reliable transportation. So much so that Deccan Herald, one of the local newspapers of Bangalore recently reported “Autorickshaw drivers, once notorious for rejecting prospective customers whose destinations were far from their preferences, have turned humble after app-based taxi services took away the high profile customers." However, unlike UBER which eventually caused many licensed taxi services to shut shop or scale down, OLA understood the context and struggle associated with its competitors (Auto drivers) and spotted an opportunity. Instead of taking away customers from Auto Drivers, OLA used its platform to flip it to a low-cost offering.

The Job to be Done of Auto Drivers

Often the reason for an incumbent’s inability to respond to disruption is its underlying cost structure. While in this case, it may not be a case of disruption, but the causal reason for the behavior of the Auto drivers was their underlying cost structure. There are numerous consumer complaints in public forums about Auto drivers’ related to rude behavior, demand for excess fare and tampered meters. However, there were few attempts made to understand their context.

One such study was done by the Indian Institute of Science, Bangalore, which provided some interesting insights into the operating conditions of the Auto drivers. According to the study, an auto driver on average works for 26 days in a month and each day is around 8 – 11 working hours. On an average, he drives for around 120KM (75 miles) around the city of which 90KM (56 miles) are productive or money making. Rest of the time is spent roaming around the city looking for a hire. For every kilometer the vehicle is on hire the driver makes nearly Rs 9/KM. Based on which the average earnings for a day are Rs 810. This is the gross earning of the drive of which the driver needs to pay off his daily expenses.

The majority of these drivers come from economically backward classes of society. Hence very few actually own the vehicles they drive. Majority lease it from a Bank or rent it, which translates into roughly Rs 150 – 180 per day. Other expenses include (all averages) fuel cost of Rs 250 per day, Rs 11 per day for insurance, Rs 33 toward vehicle maintenance and other miscellaneous expenses (like meals, snacks etc.) at Rs 75 per day. All this add up to Rs 520 – 550 per day. This means that the driver makes net Rs 300 per day.

This does not include any unforeseen expenses during work like traffic fines, vehicle breakdown not covered by insurance etc. In addition to this, the fares set by the government often do not keep pace with the fuel cost. The fare revisions (controlled by the state government) often came in much later than the revision in fuel prices (which happened every fortnight). So any increase in the cost of fuel would eventually further dent the net amount. In short working for almost 8 -11 hours daily, an auto driver could take home on third or less than their gross daily earnings. So there was a Job to be done for the Auto drivers to improve their daily earnings.

OLA’s solution to the problem – Make the system more efficient for Autos

There were two ways to address the problem. Either to keep fares in line with the cost of living and fuel prices in the city or enable the drivers to be more efficient. While the former was difficult to achieve (fares were regulated by the government), OLA’s technology platform could drive more efficiency in the way drivers got ride requests. As the majority of the costs that an Auto driver incurred were fixed, a marginal increase in the efficiency of drivers would directly translate into additional earnings for the drivers. OLA was quick to identify the inefficiency in the system and offered to bridge the gap. In the new system, a commuter would enter the pickup and drop point and request for a ride using the OLA app. The request was then broadcasted to all the nearby drivers registered with OLA. The drivers could choose to accept the ride. However, the driver who accepted the request would have to comply with the standard meter rates. OLA made its money by charging a small convenience fee to the commuters which commuters were happy to pay as their Job was being addressed.

This reduced the idle time that the drivers spent looking for hire and the friction with the commuters. The success of the program can be seen in the numbers. OLA started offering Autos on its app in November 2014. The pilot program started in Bangalore with only 300 Autos. As of March 2016, OLA had nearly 80,000 autos registered on its platform across 12 Indian cities. Of the total registered autos, a majority of them are in Bangalore. The response to this organized way of getting an Auto was so successful that the company has now decided to extend this offering to 10 other Indian cities.

Conclusion

Hence coming back to where we started, in a network business model, we often focus on the Job to be Done of the end consumer. However, a business model where the value proposition is just to act as a facilitator between a consumer and a service provider, we often tend to overlook the Job to be Done of the service provider. We usually assume that there would be a service provider on the other end always and in most cases there always is. However, the very reason that the service providers exist, proves that there exists a Job for which the service provider has hired the network. In other words, the service providers in such business models is also a customer of the network. The Job to be Done of this customer may vary from (and not limited to) just earning some extra income to showcasing talent or skills.

Think of it, why do hosts hire AirBnB, drivers hire UBER, freelance programmers hire Apps Stores and investors to hire Lending Club. In all these cases the supplier or service provider hires the network for a reason. Understanding that reason would help the network business to understand the possible alternatives that suppliers would be willing to hire to get the Job done and create new business lines. For instance, there are hosts in AirBnB who rent out their homes for just some extra income. For them there exist an opportunity to flip their rooms to experience centers for furniture retail during low occupancy periods. Something that West Elm – a furniture retailer did. Instead of opening stores opened boutique hotels. If AirBnB understands this Job to be Done of the host, it can very well be the online marketplace for furniture retailing in future.

So I leave you with a thought, think from the perspective of the service provider of different network businesses and what is their Job to be done. Once you identify the Job to be Done, think where else can such businesses go. Some of them what I could think of are Google Playstore or Apple Appstore fulfill mobile application developer job openings (versus college degree and other qualifications), Lending Club (or other marketplace lending platforms) offer Financial Advisory services to investors and Uber eventually moves from a transportation company to a platform for organized labor.