Business realities

Change management can be analytic, as opposed to touchy-feely.

Our client’s operating margin was falling. The bosses wanted to offshore their back office. Others weren’t convinced. To manage this change, we needed three questions answered:

• Who’s not convinced?
• Why aren’t they convinced?
• What’ll convince them?

Who’s not convinced?

We plotted the level of support and importance of key people on the stakeholder support matrix. This split people into 4 groups (below). Then we showed it around to people and had them move people around on the matrix.

• Minor sceptics. We largely ignored them
• Change facilitators. We tasked them with roles in the project
• Change agents. We made them influence the others
• People to convince. The ones we needed to focus on

This is a simple concept, actually. The insight is, putting names on such a matrix, and getting people to move them around, is a robust way to get everyone on the board and at the right spot.

Why aren’t they convinced?

We sent everyone a list of benefits and issues in outsourcing. They rated them. We grouped the results and plotted them. Here’s the result for Uli.

Uli saw more issues than benefits. Quality and possible better service were benefits. But he was afraid the company wasn’t ready, and vendors wouldn’t understand their operations.

The advantage of these charts is that you can put them side by side, and compare where different people stand. It gives you a great view of why they’re objecting, and whom you can use to counter that.

What’ll convince them?

Once we knew why people objected, it was easy to manage.

For example, to counter Uli’s fear of organisational readiness, we got people who felt this was not an issue to put forward their counterpoints.

To counter fears of vendor ability, we got a bunch of them to visit BPOs in India, and spread their confidence to others.

We arranged workshops, making sure that each group had people to convince and change agents.

This did require a lot of soft skills. But the success was largely because of the structured ground-work. Change management can be quite analytic.

Packaging can make a huge difference to products. It really hit me when I saw this bottle of Heinz’s ketchup. My two big problems with normal ketchup bottles are: (a) the sauce spills to the side of the bottle and sticks to the cap, and (b) it’s tough to pour the last bits of sauce — you have to hit the bottle a lot.

Now, I didn’t know I had these problems. But when I saw this bottle, it hit me. You keep the bottle upside down — so it’s easy to pour the last bits of sauce. And they way the nozzle valve is designed, the sauce doesn’t stick to the cap. Perfect! Since then, I don’t buy any other ketchup bottle. Even if I WANT ketchup, I don’t buy it unless I get this bottle. Packaging made be brand loyal. (Caveat: I’m not REALLY brand loyal. I’d buy any ketchup with this packaging. But only Heinz has it right now.)

The same thing with honey. The same packaging with honey gives me a third advantage. I can drink a bit of honey directly by holding up the bottle over my mouth and squeezing it. Plus, I don’t need a spoon. Because of this, my consumption of honey has shot up to 1 bottle of honey every month. Further, I have started spreading honey over ice cream these days. Note: packaging changed my eating pattern.

So, impressed by all this, I wandered around superstores, exploring the innovations in packaging (mainly in food). I will shortly blog about that. In the meantime, here are some innovative packages introduced around when Heinz’s inverted ketchup was.

A software services firm once asked us, “How come we are not able to staff projects quickly, even though we have a lot of people on the bench?”

There were a bunch of reasons, but among those, we found something interesting. They were implementing two policies that were logical on their own, but disastrous together.

(The bench is where programmers sit when they are not on a project.)

Here’s how they work. When a project starts, the project manager requests resources (people) for the project. HR passes on matching CVs to the project manager, who approves or rejects them, in consultation with the client.

They had two principles. Firtly, all matching CVs that are available are sent to the project manager. This is a good policy because it gives the project manager and the client a lot of options.

Secondly, while a PM is considering a CV, it is not double-submitted to someone else. Again, sensible, because you don’t want two clients asking for the same person at the same time.

But together, these policies killed staffing.

Every CV that is proposed is effectively “out of circulation” until it is accepted or rejected. Yet, the person is still on the bench, and very much “in circulation”. So he can’t be staffed, even though he’s available.

On average, 2.4 CVs were sent for every request. On average, a manager would hold the CV for 10 days. So, every request enforces 24 person-days of compulsary bench-time.

On a typical day, 75% of CVs were locked up this way. For example, on 22 Dec 2003, 291 CVs out of 384 were proposed for resumes. So a new request would have less than a quarter of the available bench to pick from.

No wonder they were complaining they couldn’t staff quickly enough, even though they had a large bench.

Once, we were looking at whether banks made money on demand drafts (DDs).

DDs are costly. 90% of a bank’s costs are people-related, and it takes a fair bit of time (hence people) to process DDs. If you pay for DDs in cash, it costs even more because the teller has to count the notes.

To recover this cost, banks charge a fee. The fee increases with the size of the DD. A DD for Rs 10,000 may cost Rs 50, while one for Rs 100,000 may cost Rs 200.

But apart from the fee, banks also earn float on the DD. Let’s say you go to a bank, pay Rs 100,000, and take a DD. You mail the DD to someone, who cashes the DD three days later. The bank has your Rs 100,000 for 3 days, and earns the overnight interest rate at around 5%, netting Rs 41 in the process. This float is significant for large DDs.

Our client bank was making a small loss on DDs. Every DD less than Rs 50,000 caused a loss (even after including float). And 3 out of every DDs was smaller than Rs 50,000.

Then we had this bright idea: let’s lower fee for large DDs, attract of them, and get more float income. DDs above Rs 50,000 are profitable. So big DDs are worth going after. 80% of the float income comes from the top 22% of DDs. So surely, the big DDs are worth going after. Float income increases forever, whereas fee income is capped. So big DDs could absolutely be terrific.

We were thrilled. Here was a revolutionary counter-intuitive idea: have lower charges for DDs to get more money. We kept talking about it to our client. But at the end, we didn’t suggest it. It got left behind the conventional idea of increasing the fee for small DDs.

We were a bit disappointed, and kept cursing the conservatism of public sector banks. Goes to show how the bright young consultants can be naive. For, as it later turned out, the bulk of DD revenues is really fee income (88%), not float income. Had we lowered the fee income, there’s would’ve been no chance for the float income to make up for it.

Why did we miss that? A couple of reasons. The simple one was, though the float income increases forever, doesn’t beat fee income until the DD is about Rs 2 crores. DDs typically stay with you for a few days, and you can’t earn much interest on that.

The other reason was subtler. We had assumed that the float income for a DD of Rs 100,000 is 100 times that of the DD income for Rs 1,000. But the float income does not increase linearly! Someone who gets a DD for Rs 1,000 doesn’t mind waiting a bit to present it, but someone who gets a DD for a lakh would walk to the bank the very same day. The chart below shows how long customers wait to cash DDs. The X-axis is the size of the DD. The Y-axis is the number of days they wait. It shows a clear diminishing trend.

Lesson: Conservative bankers might make more money not listening to hotshot consultants.

We were working with the financing subsidiary of a conglomerate. They had two divisions that gave loans for buying vehicles (mostly trucks, but also cars). One division used the direct channel. They had direct marketing agents (DMAs) who were paid a commission for getting the contract, and the division collected the monthly installments. The other used the dealer channel. The dealers would get the contract as well as collect the installments.

They wanted to cut costs, and asked us which channel had more flab. Since the company used IRR (internal rate of return), we defined the operating cost as the reduction in IRR. For example:

12% IRR paid by customer (through monthly installments)

9% IRR to subsidiary after reducing the cost of processing his loan

3% is therefore the operating cost.

After two months of analysis, we confirmed the subsidiary’s own opinion: the dealer channel had lower operating cost. The direct channel’s operating cost was 3.8% while the the dealer channel’s was 2.7%.

So we said the direct channel is flabby.

But the direct channel guys didn’t agree, and fought every inch of the decision.

“Do you think these figures are wrong?” I asked.

“Look, all we’re saying is, we KNOW they pay out huge commissions to dealers. We KNOW they’re overstaffed. They just CAN’T have a lower operating cost.”

I was tasked with resolving the issue. After a month of breaking the cost every single way, something interesting emerged. If we measured the operating cost per contract in Rupees, both divisions had the same cost per contract: Rs 18,500. That is, the total cost incurred in getting the customer and servicing the loan over the lifetime of the loan was Rs 18,500 in both divisions.

It turned out that the size of the loan was different: the dealer channel was still lending mainly for trucks, while the direct channel had entered the high growth passenger car market. Cars cost less than trucks. So while the dealer channel was paying 18,500 and getting interest on a large truck, the direct channel was paying the same 18,500 for less interest on smaller cars.

This is a strategic decision. The subsidiary had chosen to enter the car business knowing it would be less profitable but have higher growth.

But the story had a twist.

The 18,500 of operating cost per contract broke down as follows:

	Dealer	Direct
Getting the loan	5,000	7,000
Servicing the loan	13,500	11,500

The dealers are paid a servicing cost as a percentage of the loan. Servicing in the dealer channel is a variable cost. The direct channel, however, employs its own people, and incurs a higher cost only when it hires more people. About half of the costs are fixed. If the business doubles, the number of people you need increases only by about 50%. Servicing in the direct channel is more a fixed cost.

This subsidiary was planning to double their business in two years. At that point, the dealer channel would still cost Rs 18,500 per contract, but the direct channel would have come down to around Rs 13,000. So, going forward, the direct channel is really cheaper!

We told them to try and reduce the dealer commission.

Postscript: The subsidiary still went ahead and cut costs aggressively in the direct channel. It’s easier to fire your own people than to tell 500 dealers to reduce their commission, especially when you need them to also sell your trucks.

Banks install ATMs to lower their branch costs, and to attract new customers. When working out the economics of ATMs, we found that lowering branch costs alone could not be a viable reason to install an ATM.

The bank argued as follows:

“Every time someone withdraws money from an ATM, they avoid going to the branch. With enough people going to the ATM, I can afford not to increase my branch size, and that saves me money. Since it costs me Rs 20 every time a person withdraws cash (in terms of salary, rent, etc.) and an ATM costs about Rs 2,200 a day, I’ll break even if there are 110 cash withdrawals from the ATM.”

The argument misses a crucial point: every ATM transaction does not replace a branch transaction. People visit ATMs more frequently than branches, thanks to them having smaller queues and being open 24 hours. As a rule of thumb, people visit ATMs twice as often as a branch to withdraw cash.

A teammate didn’t believe me. We argued.

“When I used the branch, I would withdraw money for the entire month at the beginning of the month. I continue the same with an ATM.”

“But I withdraw cash whenever I need money. And in smaller chunks. Sometimes, I just withdraw Rs 200. That way, I get to carry less cash too.”

“Ah, you may be the exception, as always. Very well, I will find out.”

He went to a fairly representative branch, and asked them how much money would people withdraw before their ATM was installed. Since ATMs impose a limit of Rs 15,000, he discarded transactions above Rs 15,000. The answer was: people used to withdraw about Rs 3,600 every time they came to the branch. Then he asked, what’s the average ATM withdrawal. Answer: Rs 1,900. In other words, people seemed to withdraw only half as much from an ATM as from a branch. (And therefore, on average would withdraw twice as often every month.) My teammate was finally convinced.

So, in order to break even, the ATM must be used about 220 times a day, not 110 times. This is nearly impossible. ATMs are used mostly in peak hours: morning while travelling to work, during lunch, and evening when travelling back to work. Apart from these hours, the ATM is practically unused. This gives roughly a 4-hour window. The time between two ATM transactions is at least a minute. So a very busy ATM might be able to make the 220 transactions in that time. Most ATMs will not.

In fact, we found that only 4 ATMs managed to break even, among their 250. The cost-saving argument alone is difficult to justify an ATM.

Reliance Infocomm, after launching their prepaid business in India, introduced an new scheme. Pay Rs 4,300, and get a mobile phone PLUS prepaid vouchers worth Rs 4,300. Effectively, you’re getting a mobile phone for free. The scheme made good financial sense for Reliance. With a million subscribers to this scheme, they could recover Rs 430 cr of their upfront capital investment and retire their debt. Besides, the Rs 4,300 would have normally been bought over a period of around three years by prepaid subscribers, making its present value around Rs 3,600, at an interest rate of 12%. Add to that the reduction in distribution cost due to bulk selling, and possibility of non-usage, etc… the economics might work out.

But after the scheme was launched, Reliance was puzzled. Why did the sale of their normal prepaid cards dip? Any new prepaid customers would obviously go in for the new scheme. But old prepaid customers would still need prepaid cards, and should have bought them from the dealers. The dealers should have come back to Reliance to stock up their prepaid cards. Why didn’t they?

What happened was, they hadn’t anticipated was the ingenious market. Many new customers didn’t need the full Rs 4,300 worth of talk-time. Spotting this need, dealers would repurchase these prepaid vouchers at a discount.

Dealer: “Look, if you don’t need the entire Rs 4,300 worth of vouchers, I’ll buy some of them back.”

Customer: “I just need Rs 1,000 of talk time. Can I return Rs 3,300 worth of vouchers and take Rs 3,300 from you?”

Dealer: “I’ll take Rs 3,300 worth of vouchers, but I’ll pay you only Rs 3,000.”

Customer: “Well, I’m effectively paying Rs 1,300 for a mobile phone plus Rs 1,000 worth of talk time. Sounds good!”

The dealer now has Rs 3,300 worth of vouchers. So he doesn’t go back to Reliance to restock. When regular prepaid customers come in for prepaid vouchers, he’d offer some from the repurchased stock. The customer benefits (lower cash payment), the dealer benefits (higher margins), and it’s only Reliance left wondering why the sales dropped.

Over my last few years as a consultant, I’ve seen many interesting ways in which markets have emerged where they shouldn’t have, creating havoc in pricing and scarcity. Fixed prices fluctuate, free goods acquire a value, and non-tradeable goods are traded. I’ll share a few of these examples over the next few weeks.

Once, a fan manufacturer asked us, We did an analysis and found that our wholesalers’ margins fluctuate. How could that happen, when we are fixing their buying and selling prices?

The manufacturer sells several popular fans. Their highest selling fan (call it HS), for instance, was sold to wholesalers at Rs 1,089, who would then sell it to retailers at Rs 1,100. No question of margin fluctuation.

I took a trip to Lohar Chawl, the wholesale fan market, to get to the bottom of this. After a few conversations in dingy warehourses, here’s what I discovered. Fans are bartered. Wholesalers keep as little cash and inventory on hand. Often, a retailer would order a fan (say X) not in stock. The wholesaler doesn’t want to lose the deal, and doesn’t have cash, but he would have some inventory of HS, since it’s such a high-selling fan. He goes to another wholesaler, and says,

“Give me some fan X, and I’ll give you some HS fans instead. You’ll be able to sell these HS fans fairly quickly anyway.”

“Why should I? Tell me your customers name and I’ll sell it to him myself, and make the profit.”

“Tell you what. I’ll give you my HS fans for Rs 1,079 instead of Rs 1,089. You’ll get a higher margin when you sell it.”

This is a routine matter in Lohar Chawl. If you don’t have a fan, barter it for another (often HS) at a discounted price. So the wholesaler’s margin would depend on how many fans they bought at a bartered price!

Poaching was another reason for the margin fluctuation. The manufacturer demarcated territories for each wholesaler, saying “You can sell the these 20 retailers, you can sell to those 18, and so on.” Ambitious wholesalers, or those with inventory to dump, would do a side deal with a retailer.

Look, your wholesaler charges Rs 1,100 for this fan. I’ll sell you this lot for Rs 1,095. And let’s keep it quiet.”

Yet another reason for margin fluctuation was smuggling. Sometimes, the wholesalers would be able to smuggle fans into Mumbai without paying octroi. And sometimes they wouldn’t.

The biggest lesson for me from this was, It’s bloody tough to restrict a free market. I’ll tell you more about this shortly.