Tag: grofers

Grofers scaling down

Readers of this blog might be aware that I’m not a big fan of hyperlocal grocery delivery firm Grofers’s business model. The problem is that there are no costs saved to make Grofers its margin – apart from the retail inventory expense incurred at the retailer (from whom Grofers procures), there is also the last mile delivery expense that is incurred which doesn’t leave much profits.

The reason for Grofers scaling back from nine cities in India, however, is not related to this. It is more to do with market size and scale.

Given the uncertainties in terms of demand and service times, a business such as Grofers makes sense only when there is a minimum critical mass in terms of demand. Serving a locality with only one delivery person doesn’t make sense, for example, since uncertainty in demand will mean that either that delivery person is underworked or service levels cannot be guaranteed.

If the average demand in an area can support more delivery persons, though, this can smoothen out the uncertainty (that aggregation smoothens uncertainty is one of the fundamental principles of operations) and higher service levels can be guaranteed without building in too much slack.

While the cities that Grofers has pulled back from are not small (Mysore/Vizag/Coimbatore etc) it is unlikely that any of them would have had the size and density of demand in order to support a scale of operations which would make sense for Grofers. There are several reasons for this.

Firstly, Grofers only captures the incremental demand for grocery delivery, and with most small retailers already offering grocery delivery, the value Grofers adds is to deliver from large retailers. While I don’t have data to support this, my hypothesis is that large retailers have a smaller share in small cities thus cutting Grofers’s natural market.

Next, the transaction cost of travelling to the store is lesser in smaller cities, given shorter travel times (on account of both size and traffic), further cutting demand for on-demand delivery. Thirdly, while smartphones are widespread across the country, my hypothesis (again don’t have data to support this) is that usage is lower in smaller cities (compared to larger cities). Fourthly, smaller cities are likely to be less dense than larger cities (data on this should be available but NED to compile it now) meaning delivery personnel have to cover larger areas.

Some thinking can lead to more such reasons, but the basic point is that not only are these cities small, but demand for on-demand hyperlocal grocery delivery is also much lower (on a per capita basis) than in larger cities for several reasons.

These two factors have together meant that the scale (and density) of demand that is necessary for Grofers to be viable as a business was simply not there in these cities. So it’s a logical move for them to pull out.

This doesn’t answer, however, the question of why Grofers entered these cities in the first place, since the above factors should’ve been apparent before the entry. My hypothesis here is that some fast-growing startups measure their growth in terms of the number of cities they’re in. I’ll elaborate on that on another day.

Why restaurant food delivery is more sustainable than grocery delivery

I’ve ranted a fair bit about both grocery and restaurant delivery on this blog. I’ve criticised the former on grounds that it incurs both inventory and retail transportation costs, and the latter because availability of inventory information is a challenge.

In terms of performance, grocery delivery companies seem to be doing just fine while the restaurant delivery business is getting decimated. Delyver was acquired by BigBasket (a grocery delivery company). JustEat.in was eaten by Foodpanda. Foodpanda, as this Mint story shows, is in deep trouble. TinyOwl had to shut some offices leading to scary scenes. Swiggy is in a way last man standing.

Yet, from a fundamentals perspective, I’m more bullish on the restaurant delivery business than the grocery delivery business, and that has to do with cost structure.

There are two fundamental constraints that drive restaurant capacity – the capacity of the kitchen and the capacity of the seating space. The amount of sales a restaurant can do is the lower of these two capacities. If kitchen capacity is the constraints, there is not much the restaurant can do, apart from perhaps expanding the kitchen or getting rid of some seating space. If seating capacity is the constraint, however, there is easy recourse – delivery.

By delivering food to a customer’s location, the restaurant is swapping cost of providing real estate for the customer to consume the food to the cost of delivery. Apart from the high cost of real estate, seating capacity also results in massive overheads for restaurants, in terms of furniture maintenance, wait staff, cleaning, reservations, etc. Cutting seating space (or even eliminating it altogether, like in places like Veena Stores) can thus save significant overheads for the restaurant.

Thus, a restaurant whose seating capacity determines its overall capacity (and hence sales) will not mind offering a discount on takeaways and deliveries – such sales only affect the company kitchen capacity (currently not a constraint) resulting in lower costs compared to in-house sales. Some of these savings in costs can be used for delivery, while still possibly offering the customer a discount. And restaurant delivery companies such as Swiggy can be used by restaurants to avoid fixed costs on delivery.

Grocery retailers again have a similar pair of constraints – inventory capacity of their shops and counter/checkout capacity for serving customers. If the checkout capacity exceeds inventory capacity, there is not much the shop can do. If the inventory capacity exceeds checkout capacity, attempts should be made to sell without involving the checkout counter.

The problem with services such as Grofers or PepperTap, however, is that their “executives” who pick up the order from the stores need to go through the same checkout process as “normal” customers. In other words, in the current process, the capacity of the retailer is not getting enhanced by means of offering third-party delivery. In other words, there is no direct cost saving for the retailer that can be used to cover for delivery costs. Grocery retail being a lower margin business than restaurants doesn’t help.

One way to get around this is by processing delivery orders in lean times when checkout counters are free, but that prevents “on demand” delivery. Another way is for tighter integration between grocer and shipper (which sidesteps use of scarce checkout counters), but that leads to limited partnerships and shrinks the market.

 

It is interesting that the restaurant delivery market is imploding before the grocery delivery one. Based on economic logic, it should be the other way round!

Restaurants, deliveries and data

Delivery aggregators are moving customer data away from the retailer, who now has less knowledge about his customer. 

Ever since data collection and analysis became cheap (with cloud-based on-demand web servers and MapReduce), there have been attempts to collect as much data as possible and use it to do better business. I must admit to being part of this racket, too, as I try to convince potential clients to hire me so that I can tell them what to do with their data and how.

And one of the more popular areas where people have been trying to use data is in getting to “know their customer”. This is not a particularly new exercise – supermarkets, for example, have been offering loyalty cards so that they can correlate purchases across visits and get to know you better (as part of a consulting assignment, I once sat with my clients looking at a few supermarket bills. It was incredible how much we humans could infer about the customers by looking at those bills).

The recent tradition (after it has become possible to analyse large amounts of data) is to capture “loyalties” across several stores or brands, so that affinities can be tracked across them and customer can be understood better. Given data privacy issues, this has typically been done by third party agents, who then sell back the insights to the companies whose data they collect. An early example of this is Payback, which links activities on your ICICI Bank account with other products (telecom providers, retailers, etc.) to gain superior insights on what you are like.

Nowadays, with cookie farming on the web, this is more common, and you have sites that track your web cookies to figure out correlations between your activities, and thus infer your lifestyle, so that better advertisements can be targeted at you.

In the last two or three years, significant investments have been made by restaurants and retailers to install devices to get to know their customers better. Traditional retailers are being fitted with point-of-sale devices (provision of these devices is a highly fragmented market). Restaurants are trying to introduce loyalty schemes (again a highly fragmented market). This is all an attempt to better get to know the customer. Except that middlemen are ruining it.

I’ve written a fair bit on middleman apps such as Grofers or Swiggy. They are basically delivery apps, which pick up goods for you from a store and deliver it to your place. A useful service, though as I suggest in my posts linked above, probably overvalued. As the share of a restaurant or store’s business goes to such intermediaries, though, there is another threat to the restaurant – lack of customer data.

When Grofers buys my groceries from my nearby store, it is unlikely to tell the store who it is buying for. Similarly when Swiggy buys my food from a restaurant. This means loyalty schemes of these sellers will go for a toss. Of course not offering the same loyalty program to delivery companies is a no-brainer. But what the sellers are also missing out on is the customer data that they would have otherwise captured (had they sold directly to the customer).

A good thing about Grofers or Swiggy is that they’ve hit the market at a time when sellers are yet to fully realise the benefits of capturing customer data, so they may be able to capture such data for cheap, and maybe sell it back to their seller clients. Yet, if you are a retailer who is selling to such aggregators and you value your customer data, make sure you get your pound of flesh from these guys.

Hyperlocal and inventory intelligence

The number of potential learnings from today’s story in Mint (disclosure: I write regularly for that paper) on Foodpanda are immense. I’ll focus on only one of them in this blog post. This is a quote from the beginning of the piece:

 But just as he placed the order, one of the men realized the restaurant had shut down sometime back. In fact, he knew for sure that it had wound up. Then, how come it was still live on Foodpanda? The order had gone through. Foodpanda had accepted it. He wondered and waited.

After about 10 minutes, he received a call. From the Foodpanda call centre. The guy at the other end was apologetic:

“I am sorry, sir, but your order cannot be processed because of a technical issue.”

“What do you mean technical issue?” the man said. “Let me tell you something, the restaurant has shut down. Okay.”

I had a similar issue three Sundays back with Swiggy, which is a competitor of Foodpanda. Relatives had come home and we decided to order in. Someone was craving Bisibelebath, and I logged on to Swiggy. Sure enough, the nearby Vasudev Adigas was listed, it said they had Bisibelebath. And so I ordered.

Only to get a call from my “concierge” ten minutes later saying he was at the restaurant and they hadn’t made Bisibelebath that day. I ended up cancelling the order (to their credit, Swiggy refunded my money the same day), and we had to make do with pulao from a nearby restaurant, and some disappointment on having not got the Bisibelebath.

The cancelled order not only caused inconvenience to us, but also to Swiggy because they had needlessly sent a concierge to deliver an impossible order. All because they didn’t have intelligence on the inventory situation.

All this buildup is to make a simple point – that inventory intelligence is important for on-demand hyperlocal startups. Inventory intelligence is a core feature of startups such as Uber or Ola, where availability of nearby cabs is communicated before a booking is accepted. It is the key feature for something like AirBnb, too.

If you don’t know whether what you promise can be delivered or not, you are not only spending for a futile delivery, but also losing the customer’s trust, and this can mean lost future sales.

Keeping track of inventory is not an easy business. It is one thing for an Uber or AirBnB where each service provider has only one product which is mostly sold through you. It is the reason why someone like Practo is selling appointment booking systems to software – it also helps them keep track of appointment inventory, and raise barriers to entry for someone else who wants the same doctor’s inventory.

The challenge is for companies such as Grofers or Swiggy, where each of their sellers have several products. Currently it appears that they are proceeding with “shallow integration”, where they simply have a partnership, but don’t keep track of inventory – and it leads to fiascos like mentioned above.

This is one reason so many people are trying to build billing systems for traditional retailers – currently most of them do their books manually and without technology. While it might still be okay for their business to continue doing that (considering they’ve operated that way for a while now), it makes it impossible for them to share information on inventory. I’m told there is intense competition in this sector, and my money is on a third-party provider of infrastructure who might expose the inventory API to Grofers, PepperTap and any other competitor – for it simply makes no sense for a retailer to get locked in to one delivery company’s infrastructure.

Yet, the problem is easier for the grocery store than it is for the restaurant. For the grocery store, incoming inventory is not hard to track. For a restaurant, it is a problem. Most traditional restaurants are not used to keeping precise track of food that they prepare, and the portion sizes also have some variation in them. And while this might seem like a small problem, the difference between one plate of kesari bhath and zero plates of kesari bhaths is real.

Chew on it!

Grofers, BigBasket and the Lack of Systems Thinking

Last week I wrote this post about why Grofers is not a sustainable and scalable business. The basic point was that goods they sell undergo both high inventory cost (having been stored in a retail store) and high transport cost (delivery).

The most common response to the post was that my claim was wrong because “Grofers doesn’t store any inventory but only delivers”. And it was not unintelligent people who said this – I counted at least three IIM graduates who made this claim on Twitter (ok if that statement gives the impression that I think that all IIM graduates are intelligent, so be it. I don’t disagree).

While their claim is correct, that Grofers doesn’t store any inventory but only delivers, the problem with their line of attack is that they are looking at it from a very localised perspective and not looking at the bigger picture.

A similar problem can be seen in this post on TechCrunch announcing BigBasket’s latest round of funding. Relevant section here (hat tip: Rohin Dharmakumar):

Challenges faced by BigBasket include the grocery industry’s low margins, the cost of adding new delivery staff, and the fact that it carries its own inventory. This allows BigBasket to offer a large selection, but also means it has more overhead than hyperlocal services that partner with existing merchants and needs to more time to prepare before expanding into new cities. (emphasis added)

Catherine Shu, who wrote that piece, might be right in claiming that Bigbasket carries its own inventory. But she is wrong in claiming that it is a problem, for Bigbasket is in a completely different business compared to those hyperlocal services, and in my opinion in a superior business. The carrying of inventory is a feature rather than a bug.

What the twitter comments on my post on Grofers and this piece on BigBasket illustrate is the lack of “systems thinking”. People are great at looking at localised problems, and localised “point solutions” to these local problems. What is not so intuitive is to look at a particular problem as part of a bigger picture and in a more holistic fashion.

Grofers itself may not carry inventory, but the goods it ships would have been part of inventory of some retailer. So while Grofers may not directly incur this high inventory cost, someone along the chain (the retailer in this case) does, and that means there is less money for Grofers to play around with and make a margin.

BigBasket, on the other hand, carries its own inventory and this inventory is aggregated at a much higher than retail level. This implies that the inventory costs for BigBasket are significantly lower than any retailer (since aggregation leads to lower inventory costs). And this inventory cost thus saved can help BigBasket make higher margins. It also allows them to serve the “long tail” to the customer cheaply, something Grofers may not be able to do if no shops in the customer’s vicinity stock such products.

The problem with localised thinking is that it leads to localised solutions, and local optimisation. Optimising locally at different points in a chain makes it harder to optimise at a system level.

Why Grofers is not a sustainable business

When I meet acquaintances for “gencus” nowadays, one of the things we somehow end up talking about is the startup world and inflated valuations of some Indian tech-enabled startups. The favourite whipping boys in any such discussions are food delivery companies such as Swiggy or TinyOwl and grocery delivery startups such as Grofers.

All three aforementioned companies have raised insane amounts of money and are making use of these insane amounts of money to poach employees at inflated valuations. They are also launching significant “above-the-line” advertising campaigns making use of the funds they are flush with. Yet, there is one fundamental concept that indicates that these companies are not likely to go far.

The whole idea of e-commerce is that you trade inventory costs for transportation costs. In “traditional” offline retail, transportation costs are low, since everything is transported in bulk, up until the retail store. In exchange for this, there are significant inventory costs, since inventory needs to be stored in a disaggregated fashion (at each retail outlet) pushing up uncertainty, and thus costs.

E-commerce works on the premise inventory is held in an aggregated fashion thus pushing costs down significantly (especially for “long tail” goods). In exchange, the entire transportation supply chain happens in an expensive “retail” manner. Thus, you save on inventory costs but incur transportation costs.

The problem with businesses such as Grofers is that they incur both costs. First of all, since they rely on picking up goods from retail stores, the high inventory cost is incurred (the hope is that retailers will give Grofers bulk discounts, but that is capped at a fraction of the margin that retailers make). And then, since Grofers transports the item to the customer’s location, retail transportation cost is incurred (whether it is directly paid for by the customer or by Grofers is moot here, since it has the same effect on prices and volumes). Thus, Grofers incurs costs of inefficiencies of both online and offline retail, and is thus a fundamentally unsustainable business.

It can be argued that Grofers offers a degree of convenience that you pay Grofers rather than incurring the cost yourself of getting the goods from the shop. This has two problems, though – firstly, a large number of small and medium retailers in India anyway offer free home delivery (and take orders by phone). Secondly, the cost incurred by Grofers for delivery is a transaction cost and irrespective of who bears it, it results in a reduction of total volume of transactions.

In its last round, Grofers raised $35M. Given the above fundamental inefficiency in its model, it is hard to see the business being worth that much in the long term.