Consulting Case Example: Improve Performance of a Manufacturing Company

Another case I received during my interviews. Again, I was told that this was a real case performed to perfection by real consultants 🙂

Interviewer: Okay, so there is this company in New South Wales in Australia. It makes wheels for railway carriages. Our client just bought this company and they feel that its performance can be improved. We have been called in to help.

Interviewee: (In this case, its me) Is it the production performance they are concerned about, or is the performance related to the revenues and costs?

Interviewer: Its a production issue.

Interviewee: What’s the issue?

Interviewer: Not many wheels are being manufactured.

Interviewee: Not many wheels compared to the competitors, I assume.

Interviewer: Yes.

Interviewee: Okay, how many wheels are we currently making? And how many are our competitors making?

Interviewer: We don’t have much information about our competitors except that they are making more wheels than we are. We currently make around 63,000 wheels per year.

Interviewee: Okay so 63,000 wheels per year is approximately 5250 wheels per month or 175 wheels per day. (I divided the monthly number by 30 to ease up my calculations). We need to make more than 175 wheels per day, right?

Interviewer: Yea, how do we do that?

Interviewee: How are the wheels made currently? Like what is the wheel making process?

Interviewer: We buy 1m x 10m bars of steel which are cut into 30cm slices called cheese. This cheese is melted and put into a milling furnace. While the hot cheese is spinning, heavy rollers squash it out into a wheel shape. This is then taken to a finishing area where it takes 2 days to cool down.

Interviewee: So each wheel takes 2 days to cool down?

Interviewer: That is correct.

Interviewee: Is there something that can be done differently in this process? Like quicker cooling?

Interviewer: No.

Interviewee: Could there be some process inefficiencies? Such as the steel bars not being the optimal shape for cutting, or steel impurities so that the cheese doesn’t melt as fast?  Do we buy enough steel to produce more than 175 wheels/day? Could there any wastage of raw material?

Interviewer: Those are interesting observations. To your point, there aren’t any process inefficiencies that could be the cause of our low output. But we do buy enough steel to produce more than 175 wheels/day.

Interviewee: That is interesting. So we do have enough raw material, but somehow aren’t producing enough wheels. Could it be that some of the wheels being produced aren’t usable?

Interviewer: Good point! 5% of all wheels produced get rejected due to operational error. The wheel punching machine isn’t calibrated well. Another 5% get rejected during testing due to structural problems in the wheels.

Interviewee: So only 90% of the wheels we produce are usable?

Interviewer: That is correct.

Interviewee: Is the calibration issue due to human error? How can we improve the rejection rate?

Interviewer: Yes. The calibration issue is due to human error. Some of the factory workers are not well trained to operate the machines. The structural problems we cannot address. So, why don’t you tell me how we can improve the rejection rate?

Interviewee: Well, we can reduce the rejection rate from 10% to 5% if we can address the operational errors. As these errors are caused by poorly trained workers, we can implement training programs and quality control measures to ensure that lesser wheels get rejected.

Interviewer: Okay, very good. How will this improve my monthly output?

Interviewee: So let’s say we currently make x wheels/day out of which 10% are rejected. So 90% of x = 175.  So x = 175/90%. As the rejection rate has gone down to 5% due to our improvements, our output increases to 95%. So the total number of wheels we will make after these improvements is: 95% of x = 184.7 (or 184 as we cannot have fractional wheels). The number of wheels we can make monthly would be 184 * 30 = 5520.

Interviewer: Very good. Now let’s stick to our 175 number. We did a little more digging, and we found out that even with this 5% improvement, we were still behind our competitors in the number of wheels produced.

Interviewee: Why? Is the factory running under capacity? How many wheels can the factory produce in a day?

Interviewer: We don’t know how many wheels the factory can produce in a day, but it is definitely running under capacity.

Interviewee: Okay, so we know that we buy enough steel to produce more wheels. Could it be that the factory is not running 24/7?

Interviewer: Excellent point. We asked around, and realized that each day, the factory experienced 8 hours of downtime:

• 30 minutes due to MRO
• 190 minutes of unplanned maintenance due to machine breakdowns
• 260 minutes due to production run changeovers where the operators change the wheel measurements

Interviewee: Which of these can we affect? Can we improve unplanned maintenance by buying new machines?

Interviewer: We don’t have the money to buy new machines.

Interviewee: What are production run changeovers? Why are wheel measurements changed? Can we shorten this?

Interviewer: Well – we make wheels in 2 sizes. During a production run changeover, we recalibrate the punching machine to change the size of the wheel being produced.

Interviewee: Are there inefficiencies in this process? Let me elaborate with an example – Let’s say we produce a big wheel and a small wheel. Suppose for the first quarter of the day, we make small wheels. Then we switch to making big wheels. In the third quarter of the day, we switch back to making small wheels – and so on. Each of these switches is contributing to wasted time during changeovers. If such inefficiencies exist, we can improve by only having 1 changeover. Lets make small wheels in the morning and big wheels in the evening. Hopefully, you get my drift =)

Interviewer: Great point. We actually did end up facing a similar issue. Let’s say, by improving the process , we can now reduce the time spent in production run changeovers to 80 minutes. How many more wheels will we make in a year?

Interviewee: Alright, let me have a couple of minutes to do some quick math.

Before: 24 – 8 (downtime) = 16 hours makes 175 wheels. In one hour – we make 175/16 wheels

After: Downtime is now 30 + 190 + 80 = 300 minutes or 5 hours. (Means we have 3 more hours each day to produce wheels) So each year, we would make 3 * 365 * 175/16 = 11,976 (roughly 12,000) more wheels

Interviewer: I think that sounds about right. Now do you have any questions for me?

Consulting Case Example: Lower Cleaning Costs for Company

Actual Case I received during one of my interviews. This is how I approached the problem, it is by no means the “correct” way. You may have your own ideas and methodologies, and there are a lot of different ways to solve the same case. And my charts weren’t as pretty.

Interviewer: Your client is a large departmental store in Manhattan which competes with Macy’s. The objective is to cut costs across the company due to lower profit margins during the recessionary economy. Your engagement manager assigns you the task of cutting down costs by 50% in the Cleaning/Janitorial Services Division.

Interviewee: So, let me reiterate the problem at hand to make sure I got down all the important points.

Client – Large department store competing with Macy’s

Objective – cut cleaning costs by 50%

Is there something that I have missed out or are there any other objectives that I should be aware of?

Interviewer: No, that seems about it.

Interviewee: Sounds interesting. Could I have a moment to collect my thoughts?

Interviewer: Sure, go ahead.

Interviewee: (Draw the following Chart)

I would first like to see what are the different Drivers of Cleaning Costs in a department store.

Is there anything else I am missing out?

Interviewer: What about flagship stores vs. other stores?

Interviewee: (Though I think that’s a redundant question but anyway)

That’s a good point, let me add that to my chart.

Interviewer: That looks like a good way to start.

Interviewee: I would like to know if the cleaning/janitorial services is in-house or outsourced.

Interviewer: They are currently outsourced.

Interviewee: Do we know if we are getting a good price compared to our competitors?

Interviewer: We have no idea as to what our competitors are doing with respect to cleaning.

Interviewee: Okay then, does our client just have one store?

Interviewer: The client runs 4 stores in Manhattan.

Interviewee: And we want to cut down cleaning costs across these 4 stores by 50%, right?

Interviewer: That is correct.

Interviewee: Do we use the same supplier for all the 4 stores?

Interviewer: (Smiles) No we use a different supplier for each store. Well, the client also gave us this chart.

Interviewee: (This doesn’t really tell me anything, quiet for a couple of minutes due to confusion)

Well, I suppose I will get a better idea if I knew the spend/store.

Interviewer: That’s a good point. Take a look at this chart.

Interviewee: Wow, stores 1 & 4 seem to be the reason for most of the spend.

Interviewer: Good Point. Why do you think that is the case?

Interviewee: Maybe because stores 1 & 4 are larger than the other stores. Would you happen to have the size for each store?

Interviewer: Yes, the sizes of the stores are as follows:

Store 1- 20,000 sq ft

Store 2 – 5000 sq ft

Store 3 – 2500 sq ft

Store 4 – 8500 sq ft

Interviewee: That’s really helpful. Now let me figure out the cost/sq ft for each store.

Store 1- $2.5 k/sq ft

Store 2 – $1.5 k/sq ft

Store 3 – $3.4 k/sq ft

Store 4 – $4 k/sq ft

So it seems that Store 2 is getting the lowest price per sq ft for cleaning services. What if I decide to contract the cleaning/janitorial services to supplier of Store 2? Can I achieve even lower prices due to economies of scale?

Interviewer: There will be no volume based discounts. What kind of savings are you looking at if we contract the cleaning services to Supplier #2?

Interviewee: I would like to have a minute to do the math. (Furiously crunch out some numbers)

Total Current Spend: $100 million

Possible Future Spend if contract cleaning of all stores to Supplier #2:

Store 1- 20,000 sq ft * $1.5 k/sq ft = $30M

Store 2 – 5000 sq ft * $1.5 k/sq ft = $7.5M

Store 3 – 2500 sq ft * $1.5 k/sq ft = $3.75M

Store 4 – 8500 sq ft * $1.5 k/sq ft = $12.75M

Total = $54 million

Possible Future Savings if contract cleaning of all stores to Supplier #2: $46 million (which is 46%)

Need another 4% in savings.

Interviewer: Very Good, now how do you plan to get the rest of the 4% in savings?

Interviewee: Perhaps we can now look at the Suppliers cost and help him get some savings which he can pass on to out client.

Interviewee: We are in no position to negotiate with the Suppliers.

Interviewee: Going back to Chart one, I see that although Supplier #2 has the lowest supplies cost. Supplier # 4 has really low percentage of labor costs.

Interviewer: I see, but how does this help us?

Interviewee: Maybe, we can lower Supplier # 2’s costs by using the low labor costs, like those of Supplier # 4.

Interviewer: Hmm… Well, out suppliers do not want to collaborate, so that is out of the question. But why don’t you try it and see if we get significant savings?

Interviewee: (Doing some quick math and getting the hint that it might not be worth it)

On second thoughts, it looks like that idea will not really help us much.

Interviewer: Are you sure?

Interviewee: (Thanks for totally confusing me now) Yes, I think I am sure.

Interviewer: Okay then, moving on, how will you get another 4% of savings?

Interviewee: (Umm… I don’t know… Pondering over Charts)

Interviewer: How about some strategic ideas to lower costs?

Interviewee: (Oh of course!! Hit head with hand… Some Qualitative Ideas!!)

Yea, there are a couple of ways we could achieve another 4% savings.

We could cut down the frequency of store cleaning. For example, we could have the stores cleaned every other day instead of everyday.

Interviewer: Well, we are sort of a high end store and we do not want to compromise on our quality.

Interviewee: Of course, we would need to empirically figure out how much we can cut down on the cleaning frequency to ensure that the look and feel of the store is not compromised.

• Maybe we can extend this idea to the stores themselves. Cleaning frequency can be cut down in Stores other than the Flagship Store.
• Maybe certain areas of the stores which receive less foot traffic can be cleaned out a lot less frequently. We will have to monitor which areas get maximum traffic and focus on those areas.
• Perhaps we can find cheaper cleaning supplies or substitutes without compromising on quality.
• We could negotiate with our current supplier for volume discounts.
• We could try to find a further cheaper supplier of janitorial services altogether.
• We could try to build an in house cleaning services team. That way, we may be able to save on some of the premium we probably have to pay our suppliers.

Interviewer: Yes, these all seem like pretty good ideas. Now suppose you have a meeting with our client. What are you going to tell him about your findings?

(This means sum up your case in a minute)

Interviewee: Well, initial studies show that we would be able to achieve a 50% cost reduction in cleaning/janitorial services. Currently, we use 4 different suppliers, each offering a different pricing schemes, for our 4 Manhattan stores. We can achieve 46% of our targeted savings by contracting the cleaning services of all 4 stores to supplier #2. Furthermore, we can achieve an additional 4% of savings if we cut down the frequency of store cleaning, use cheaper cleaning material substitutes or focus on certain areas of the store getting more foot traffic, as long as it does not compromise our quality standards. A combination of both will give us our 50% savings target.

Interviewer: Thank you, those seem like excellent ideas.