Managing Sewage Demand and Holiday Demand

When it rains it pours – that is, sewage overflows into streams, rivers and lakes and then into our beaches and drinking water (yuck!).   (NY Times 11/22/09)  For example, cases of serious diarrhea at one Milwaukee hospital increase when local sewers overflowed.

The problem with our old sewage systems is that they are capable of handling normal “loads”, but when it rains, the demand on the system exceeds capacity. With no place to inventory the excess water, it is spilled into local waterways.

So what is the solution when peak demand exceeds capacity? The knee jerk reaction is to increase capacity. But this can be foolish – it can be very costly to increase capacity when it will be used only at peak demand times. A better strategy is to smooth out the demand peak.  Of course, we can’t control rain, so that won’t work. But we can slow down the flow of rain into the sewage system by how we design our cities. In particular, planting trees helps to absorb the flow of water (maybe we can interpret this as an increase in capacity). Planting organic roofs can also slow down the flow of water – instead of rushing off the roof, it drips from the roof.  Or, if we could design sewage systems so that rain water was processed in a different system than toilet water, then the peak demand problem is solved - peak rain water can be safely spilled into the river and it would be unlikely to have a coordinated demand peak of toilet water, i.e., separate smooth demand from the variable demand. (I never did believe the stories about the problems induced when too many people flush during a Super Bowl commercial.)   

So what is the connection between sewage and holiday demand? Retailers face the peak demand problem in spades. The following graph plots sales of general merchandizers from 1992 to 2008 and clearly illustrates the annual holiday spike in demand

An interesting feature of this paper, contrary to what you hear in the press, is that the end-of-year spike is actually getting smoother. To illustrate, the following graph shows the % of annual demand that occurs in November and December:

From a peak of 25%, the fraction of annual sales occurring in November and December has been steadily declining, and now is about 21%.  Why is this? It could be that consumers want to smooth their consumption (they can’t wait for that holiday present) or it could be that retailers are encouraging this demand smoothing (via pricing). 

Another change in the data is the “back to school effect” - August’s sales relative to September’s sales has been showing a steady increase. Back-to-school is now the mini-Christmas of the year.

4Q is time for what’s hot and unavailable

Every 4th quarter there are stories about what is hot and hard to find. This year, it is the e-reader category, specifically Sony’s Daily Edition Reader ($399) and Barnes & Noble’s Nook ($259). (See WSJ 11/18/09 – Sony Says Some E-Reader Orders May Miss Christmas).  Sony is telling customers that they are now shipping orders on Dec 18th – a little tight to ensure being included as a stocking stuffer.

My favorite quote from the article is:

“The possibility that Sony, a huge electronics manufacturer, would be caught off guard by supply-chain issues is surprising, said Mike Serbinis, president of Shortcovers“

The presumption is that an experienced and large manufacturer should not have any trouble matching supply with demand. This simply ignores the fact that size and experience are no match for the uncertainties of the market.

Next, it is interesting that Sony is capable of quoting shipping dates:

“In October, the company told its first wave of customers that the Nook would ship Nov. 30. A second wave of customers was told it would ship Dec. 7; shipping dates of Dec. 11 and Dec. 18 were later given.”

This does demonstrate a sophisticated level of supply chain management, assuming their quotes are reasonably accurate: to be able to do this requires a significant amount of real-time information sharing across the supply chain and the skill to process that information quickly.

Finally, I can’t help but speculate on whether they intentionally kept supplies short. Suppose you think you could sell 100,000 units. If you make 75,000, they you are likely to run short. If demand turns out to be 120,000, you are really short and you get lots of free press about how hot your product is. But to make that strategy work, loosing thousands in sales has to cost you less than the free advertising. Hard to say if it is worth it.  Then again, it is entirely possible that if your new techno gadget isn’t “hot”, then it becomes “stone cold”. For example, if “natural” demand is 100,000 but you make 75,000, then actual demand turns out to be 125,000.  If “natural” demand is 100,000 but you make 100,000, then actual demand turns out to be 60,000 because who wants to buy a product that isn’t popular.

H1N1 Production and Forecasts

The following table provides a summary of the H1N1 vaccine forecasts and actual availability:

Date	Forecast (million doses)	Actual
7/30/09	120 by October.
9/12/09	50 by Oct. 15,
9/26/09	40  by mid October
10/17/09	28-30 by the end of October.	11.4
10/26/09	30 by the end of October
10/28/09		23.2

Why the error in their forecasts? My favorite quote (NY Times Oct 25, 2009) is

Dr. Thomas R. Frieden, the director of the Centers for Disease Control and Prevention, “We really thought that having five different manufacturers would buy us some insurance, that they wouldn’t all have problems.”

The implicit assumption in this quote is that yields would be independent across flu manufacturers.  This may be true if yield primarily depends on manufacturing choices that could differ across the 5 manufacturers. But the manufacturers all used the same seed stock (the virus injected into eggs that is suppose to replicate within the eggs to make the vaccine).  Consequently, if the seed stock isn’t very good, it doesn’t matter if you have one manufacturer or 100! If you are going to diversity your risk by choosing multiple suppliers, then you should make sure that their yields are uncorrelated. (On a related point, there was no shortage of nasal spray vaccine, because they had a much higher yield … and used a different seed stock.)

There are some other reasons for the errors.  In July the forecast was based on an assumption of a high yield. However, the actual yield would not be known until the first batches were completed in August. Therefore, it seemed premature to put any faith in the July forecast without better information.

So why were the September forecasts wrong? The government basically asked the manufacturers’ for their forecasts, and not surprisingly, they got optimistic numbers. I am not saying the manufacturers lied. Instead, they probably thought it was possible that they could improve yields quickly enough to make the numbers. For example Sanofi Pasteur’s initial yield was 1.5 doses per egg and they did manage to increase it to 3 doses per egg.

Some of the shortfall was due to shortages in parts. For example, MedImmune, maker of the nasal vaccine, had more vaccine than it could put into nasal sprayers (their yield was apparently 5 times higher than expected), despite having their supplier of nasal sprayers work 3 shifts, 7 days a week.

Finally, one of the manufacturers, from Australia, satisfied Australian demand first.

The lesson from all of this, dare I say, is “don’t count your chickens before they have hatched”! Production yields are uncertain, and the government could have benefited from learning more about what determines those yields, when information would be learned about those yields and relying less on manufacturers’ forecasts.

Capacity shortages of H1N1 vaccine

Have you been able to get your H1N1 vaccine? Probably not – it has been widely reported that there are delays in the distribution of this vaccine. The interesting question is why? Reading a bunch of articles on this topic doesn’t shed a whole lot of light. But one figure jumps out at you – as reported in WSJ (10/19/09 – Delay Undercuts H1N1 Vaccine Campaign), the U.S. government has ordered 251 doses from 5 manufacturers. The current U.S. population is just over 300 million, so they have ordered enough to vaccinate over 80% of us. To put this in perspective, the U.S. normally vaccinates about 100 million. In fact, 114 million dose of seasonal flu was ordered in addition to the 251 million does of H1N1. The two types of vaccines are made with nearly identical manufacturing processes. So that adds up to about 365 million doses of vaccines, which is at least 3 times the typical production volume.

Given that manufacturers had to more than triple their capacity, it is not surprising at all that they are behind schedule in production.  Making matters worse, the quick ramp up may have contributed to the their lower-than-hoped-for yields. 

So instead of complaining that you can’t get an H1N1 shot, maybe you should be thankful that they have been able to produce as much as they have. Given the number of deaths among children, let’s hope better news will come soon.

Volatility in autos – and the demise of brand loyalty

Any casual observer to the auto industry can sense that brand loyalty has been declining. But the following graphic, posted in today’s NY Times (http://www.nytimes.com/2009/10/21/business/21auto.html) illustrates how dramatic the decline has been:

So what does this mean for strategy? Clearly, this has interesting implications for marketing (does it mean you have to do more advertising or less?).  But it also has interesting implications for operations. Logic suggests that if brand loyalty decreases, market shares should be more volatile – customers will move quickly to products they like and then just as fast they will move away to another brand’s products. It would seem that this places an extra premium on flexibility – it should become (or has become) harder to predict a model’s market share, and so flexible capacity is needed to manage the unavoidable demand-supply mismatches.  Throw in uncertainty in the economy, fuel prices, and the diffusion rate of green transportation and you have a very challenging environment ahead – as if we didn’t know that.

Production smoothing on a grand scale

It was just reported that the US GDP fell at an annual rate of 3.8% in the fourth quarter of 2008 but it would have fallen 5.1% had it not been for the inventory adjustment – demand “fell off the cliff” but firms kept producing, thereby causing inventories to rise.  One might interpret this as a nice demonstration of the production smoothing strategy on a grand scale – it is costly to shut down production, so keep producing and build inventory with the assumption that eventually demand will exceed your production and you can then draw down your inventory.  Production smoothing is particularly effective for coping with seasonal demand because then the firm has a good sense that demand will indeed return during the high season.  Now it is a little bit different. The drop in demand is not seasonal but systematic and it is not clear when demand will level off or at what level it will converge to. In particular, if the economy is still producing above the new long term rate of demand, then further adjustments to production will be needed.

The depth of the downturn may hinge on firms’ willingness to hold inventory. If they want to reduce their current inventories to their levels over the past five years, then they will need to really slam on the break (in effect, we have already produced for future demand and to return to equilibrium requires stopping production so that demand can catch up).  However, if firms are willing to hold on to their additional inventories, then the adjustment need not be so severe – in that case all that is necessary is that the firms align their current production with their current demand rate.

These issues are exhibited on a more “micro” scale at Chrysler. They stopped production in December 2008 because their inventories were higher than they could manage (or wanted) and continuing to produce would have only increased them further. They only just resumed production. If their current production rate equals their current demand rate, then their inventory level will remain unchanged. If they want to reduce their inventories, then they will have to produce at a rate that is lower than demand for some time.

So this raises the question of whether inventories are stabilizing or destabilizing to an economy.  You can tell a story for either one, and some additional data collection is needed to resolve the conflict.

Wall Street Journal, Jan 31, 2009, Economy Dives as Goods Pile Up

Little’s Law everywhere – even in the “body of Christ”

Little’s Law dictates the relationship between three performance metrics in a process, Inventory, Flow Rate and Flow Time:

Inventory = Flow Rate x Flow Time

If you know two of them, then you can calculate the third. It is hard to not be a Little’s Law junkie – seeing the application of Little’s Law everywhere.  Here is an application that you might not expect – the production of communion wafers. The New York Times published an article about a company in Rhode Island that makes a lot of communion wafers – about 1 billion per year. It comes with a short audio slide show which is reasonably interesting.

So what is the Little’s Law question from the article? Wafers are produced at the rate of 100 per second. They spend 15 minutes in a cooling tube. How many wafers does the cooling tube hold on average? Use Little’s Law! Inventory = 100 x 15 x 60 = 90,000, or enough for 360 Sundays at a medium sized church that serves 250 per service. (360 Sundays is almost 7 years.)

If Little’s Law isn’t your thing, then you can calculate out their process utilization. At 100 wafers per second, that is 100 x 60 x 60 x 24 x 365 = 3.2 billion wafers per year.  They only sell about 1 billion per year, so their process utilization is about 1 b / 3.2 b  = 31%

New York Times, December 24, 2008: http://www.nytimes.com/2008/12/25/business/smallbusiness/25sbiz.html?pagewanted=2&partner=rss

Is JIT dragging us down?

We all know these are tough economic times, but do we know why the economy is struggling so mightily? One theory is that JIT (and other lean manufacturing practices) are to blame. See, for example,

http://jamesfallows.theatlantic.com/archives/2008/12/pensee_dept_followup_on_the_no.php

The metaphor is simple, animals with stored fat are more likely to survive in times of scarcity than thin animals.  Alternatively, think of a group of hikers on a glacier. JIT means they all tied together with very short ropes so when one falls, they all fall in quick succession.  Are these metaphors correct? Is lean manufacturing the cause of our woes? There is reason to believe it is in fact the scapegoat.

Consider the auto industry and GM in particular.  Their demand is now much lower than their capacity.  (Actually, it has been for a long time, just now there is a very large discrepancy.) If they maintain production at their capacity, then their inventory continues to build, converting cash into inventory. This can work for a little while but eventually you run out of cash, risking bankruptcy.  This is the problem they currently have.  The alternative is to stop production, but then you pay your workers to do nothing, so you still burn through cash but then have no product to show for it. This is very costly – in theory, inventory can eventually be converted into some revenue.  

Now consider the role of lean production in this mess. If you turn back time to one year ago, had GM been less lean, then they would have had less cash and more inventory.  Consequently, they would have had less of a buffer to weather the current storm, so their problems would have hit earlier or would have been more severe.  If they had been even leaner, then they would have had less inventory at that time and more cash, thereby giving them a bigger cushion to survive the downturn.  Based on this reasoning, their current problems are as bad as they are because they weren’t lean enough, not the other way around. 

It is possible to defend JIT in another way – if JIT were the problem, then we would expect the leanest of the auto manufacturers to be suffering the most.  Toyota and Honda are among the leanest, and they are suffering, but not by as much, which is again consistent with the notion that during this crisis, being lean is a help and not a hindrance. Maybe the better metaphor is the following.  Two people are thrown overboard a cruise ship and nobody notices, so they need to fend for themselves. They see an island in the distance and start to swim for safety.  Who is more likely to make it, the fit and lean person or the “master of the buffet” person?

Honda’s Flexible Plants Provide Edge

This has been a tough year for most auto makes :  so far this year sales are down 24% at Chrysler, 18% at GM, 15% at Ford and 7.8% at Toyota.  But U.S. sales at Honda are up 1.7%.  There are two reasons for Honda’s success. (1) Honda’s product mix depends less on SUVs and pickups than the others (i.e., fuel efficient models make up a larger portion of their portfolio). (2) Honda has some of the most flexible plants in the U.S. To illustrate that flexibility, Honda is able to switch from producing  Civics to CR-Vs with only 5 minutes of downtime!  Honda has achieved this flexibility through many different decisions.  For example, the Civic and CR-Vs were designed to be manufacturered in the same sequence of steps, so the same step (such as a door installation) can occur at the same location on the assembly line.  Honda did have to invest $400m several years ago to improve its flexibility.  That looks like a good investment in the current climate.  

Wall Street Journal, Sep 23, 2008 – Honda’s Flexible Plants Provide Edge

Supply chain coordination snags Airbus and Boeing

Although airlines in general are having a hard time turning a profit now, there remains brisk demand for new aircraft from Airbus and Boeing. (Possibly because new aircraft are more fuel efficient.)

With a full backlog and a price tag around $200 million per aircraft, these companies do not want to delay delivery of any new aircraft.  But apparently they have had to park nearly finished aircraft due to some missing parts. For example, Boeing couldn’t deliver several 777s to Emirates because they didn’t received customized galleys from Snell, a German producer. 

The problem is that Snell didn’t anticipate the increase in volume and consequently didn’t build enough capacity. This is a good example of how a supplier’s capacity decision can have significant financial consequences for a buyer.

Wall Street Journal, Aug 8, 2008 – Lack of Seats, Galleys Delays Boeing, Airbus