Archive | March, 2012

The Leanest Cement

22 Mar
CEMEX Czech Republic 1


Lean-Manufacturing and Just-In-Time (JIT) methods got developed a decades ago in post World War Japan, which gave them tremendous advantage in manufacturing. This then translated into all kinds of innovations in all sectors. So much so that its hard to tell which improvements are Lean and which are not, almost all improvements that worked look like Lean. One key differentiation is developing a clear method to detect waste and then innovating to remove or reduce that waste. Achilles Heel of Lean is that it seldom makes a big bang in large and old companies, for instance Cement, but I came across an interesting thing Cemex of Mexico did with Lean.

I am surprised why this is not discussed in B-Schools, I got wind of it while attending my Entrepreneurship courses at Lehigh University, where an entrepreneur from the cement supplies industry (interesting story, for a later writing) casually referenced how Cemex used innovative methods to improve its cement production and delivery process. I put that in the back burner and forgot all about it, there were more interesting things being discussed.

Wired (magazine)

Wired (magazine) (Photo credit: Wikipedia)

This week at the University we discussed Lean and after doing the readings, I pulled the Cemex story out of my back burner and did some research and viola, there was an article by Wired Magazine had an article about it. Of all the places, Wired picked this up, usually focuses on technology and never cement , unless they did something cool with tech. In this case that is exactly what they did.

The real story is named ‘Bordering on Chaos‘, it’s a must read in my opinion. I will attempt to summarize it as the.

Cement is a commodity and no one pays much attention to it. The builders care about the quality and cost, but buying cement in bulk ahead of time is a waste of many things – waste of space(imagine high-rise cities), waste of manpower to safeguard against theft and weather and you can see where i am going with this. All the builders wanted was a concrete of a set quantity and quality at a given location at a given time, beyond which they couldn’t bother much about it.

Cemex, understood the waste in the downstream chain and offered to solve this in an innovative way, which would benefit them as well as their customer. Instead of selling tons of cement, they decided to deliver concrete on all the parameters that their downstream customer wanted. ‘X’ tons of concrete ready mix, delivered at ‘Y’ hours (give or take 5 min) or else 20% off the total price, just like the pizza delivery.

This has tremendous marketing implication, they changed the unit of business from tons of cement sold to tons of concrete delivered on time, which gives a big change in perception at the top and the employees involved.

So it worked something like this and there in lies the genius,  they learnt from existing tech, stats and supply chain trends

  • All orders come to a centralized control station all through the day
  • Every morning a bunch of Ready-Mix trucks will go out into the city in and try to have a random distribution through out the city. The trucks have a GPS unit and the driver has a PTT(Push-to-Talk) phone, all movements of trucks and traffic conditions are monitored at the control station
  • When a new order comes in, the control station redirects a nearest Ready-Mix truck that can reach the site given the traffic conditions. Since there is random distribution, there is a good chance that some truck is nearby
  • The control station was modeled on the 911 service in the US where the operators have relatively high freedom of operation, the employee participation and freedom also was given, which included training and a path to succeed

Doing this Cemex reduced waste, reduced money tied up in inventory and production, championed JIT(Just-In-Time), opened up a new market, improved its employee morale and at the end became more profitable.

I think this is a fascinating story and all of this took place not in the US or Western Europe, but in Mexico, how often have you heard that. That gives hope to rest that innovation is not limited to rich society.

Discovery Driven Growth of a Lean Startup

20 Mar

The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful BusinessesThe Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries

My rating: 5 of 5 stars

Discovery Driven Strategy: Unconventional Paths to Exceptional GrowthDiscovery Driven Strategy: Unconventional Paths to Exceptional Growth by Rita Gunther McGrath
Friends, these two are an amazing combo book to read.

My rating: 4 of 5 stars

I am using the framework described in this in coming up with my venture. Combine it with Rita McGrath’s book Discovery Driven Growth and you have a complete picture. Also read the blogs from both. Rita’s blogs are even more interesting, she has a direct to the point way which takes out all assumptions, and she is big on making and evaluating assumptions.

Eric’s book will give you direction for that original idea, Rita’s book will give you momentum for that original idea’s evolution to a new product/service or crash and burn early on.

I never thought crashing and burning would be fun too 🙂 try it for your selves.

I will in the near future get a chance to meet Ian, the co author of this book, i will post more on it when i get to it.

View all my reviews

Prediction to Evolution

15 Mar
Darwin's finches or Galapagos finches. Darwin,...

Image via Wikipedia

In one of my earlier blogs, i had mentioned about folly of predictions. After some careful thought, combining my interests in natural processes and business, this idea popped up.

If the cost of failure for any decision is low or none, should we predict or evolve?

perhaps the question is not worded right so here is an example which might drive the point home. The case i take is that of an Book publisher.

Publisher are skeptical by nature of the business, so they read through the manuscript of the authors before they decide if they will spend considerable resources to print, bind and distribute the books and deliver the text to the reader and still make a profit. they have their heuristics to decide, but this is the old way of doing business, read 2 years ago. The cost of failure in this model is high, a failure to predict failure will red line the final figures.

Enter the eBook publisher, they have a different business model, they enable the author to do most of the work for a fee and they take a cut of the total revenues, its an over simplification but the core of the business is more or less correct.  Their model uses modern technology to deliver the same text to the reader at fraction of the cost of the model earlier. Here the cost of failure is less, people will either buy or not buy, not buying your eBook is not going to adversely affect your bottom line badly, since much resources are not sunk in that activity.

So, if the cost of failure is close to zero, should the eBook publisher publish all and any manuscript that comes along its way, do its thing and put it on eBook shelves and see what happens. By doing this they will be the trend setters, some will click and become best seller, many will languish in the middle, and some will be just sinkers. Just as natural selection chose the best in a given condition, here market selection will decide what will be bought and what not, and just as evolution creates several ecosystems, you will also enjoy several reader ecosystems. So here there is no need of prediction, you evolve, or rather your evolution is the market itself. Perhaps alternate source of income like intelligence on readers. Perhaps long tail markets will come in play here.

There is no way one can predict the market to any degree of accuracy, instead of predicting  what it will do next, you are at every step when the market changes. Most forms prediction using big data revolves around serendipity, the case of Target knowing if a daughter was pregnant or not, i dont think they went around asking that question, but some one noticed it. This is a perpetual problem with big data mining, you don’t know the question, there are answers and mountains of it.

Well, i havent run the numbers to see if this will work out, i am going to do that shortly(perhaps run a simulation) and report back in another blog. But the idea is compelling.

Whats social about CSR?

4 Mar

This is about the Corporate Social Responsibility (CSR) that Management takes up and the its issues with Corporate Governance. The funds expended on CSR are coming from the returns to the shareholders, and its in direct conflict with their interests of maximizing returns

Unless a CSR’s ulterior motives are to maximize returns to its share holders in the long-term (there is historical evidence that markets like long-term planning) they shouldn’t even set on that path, it’s a path to the sunken millions(read $’s). But there in lies the dilemma? Do CSR for CSR’s sake or do it for real returns, where does one make the distinction, and more precisely who makes the decision?

3M wordmark

Image via Wikipedia

There are examples of CSR’s which according to me works wonderfully, examples that come to mind are

  • Patagonia Apparel’s – recycle the threads program,
  • 3M’s recycle of used bottles in their products.
  • Calpers investing in badly run companies and bring them inline (there is bad social things in finance that need cleaning up too!)

In these cases the CSR could be woven right into the product itself and the results were inline with what they were doing, there was an item at hand which has its CSR

In other cases like the Coke case and the BP case we discussed tonight, the CSR’s were way orthogonal to what they did in their day-to-day, so why even embark on such an attempt, dump so much cash into it and get a bad rep as a result?

My question is this, did the Management see this fiasco coming in the near future? what made them take that dive into things like this?

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Notes on Forecasting

4 Mar

Yesterday’s class on prediction was very interesting. I agree some form of prediction is inevitable and necessary after all, one of the expectation from any kind of an expert is some form of prediction. But the prediction game is played by mostly those who are least quipped or trained on it, most of those prediction are just few points ahead of chance (50%) and in most conditions that would just be fine, when the outcomes are binary in nature like games, but recently that was also proven wrong by black swan events like Jeremy Lin and the NY Nicks :). But in the business parlance such binary situations will be rarely found.

To give some real world examples, I came across this Freakonomics episode that Dr. Steven Levitt of ChicagoU and Robert Dubner of NPR put together (skip to section on USDA‘s crop prediction markets, Time Westergren’s Pandora online radio, and Robin Hanson of GeorgeMasonU and business of prediction markets)

I am in no way supporting not predicting the future, but predicting the right kind of future, that is why i made the comment on the insurance sector which spends a lot of time and energy figuring and factoring in possible events to make precise prediction of a group of things rather than any particular event. This concept is very beautifully described by Dr. Niall Fergusson of HarvardU in his book/video named ‘Ascent of Money‘, (skip to 12min for the topic under discussion, other chapters are equally interesting)

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