We live in an era where quality in practically everything is falling (and often plummeting).
Sometimes this drop in quality, as we have seen recently, is due to inflation. We can understand that if the cost of manual labour has increased by a 10% being it a 50% of the total cost, the other 50% will have to decline by a 10% to mantain the same price. Normally the price will just go up, since inflation cannot be related to only one product, but the whole chain of the product, from the raw material to the transport. But if at some point of the chain we want to revert the trend (like for example: dealing with a decline in consumption that force us to give better prices to attract back more customers) we will have to either reduce quality, or use our brains a little more. Guess which one is normally the solution.
Other times it is due to public demand, as in clothing. Quality falls because people demand constant closet changes and are not interested in keeping clothes for more than one season (known as fast fashion). Our parents and grandparents use to have the same clothes for years. They would buy it many times taylor made and would last for an entire life. Their closets were smaller but with a very good quality clothing.
Also, and especially relevant, are the times when the drop in quality responds to a desire by companies to increase their profits. not even to fight against inflation or to win more customers. More often than not this strategy is following a random number given as a goal. Have you ever wonder why 5% increase? Why not 4,9% or 3,14%? Why to make it from one year to next, and not to reelaborate the strategy? Normally they want to give investors a short term good news, that transform into a long term bad idea. A strategy similar to bringing in snakes to get rid of mice: yes, it is effective but it is not at all efficient in the sense that you will soon have to deal with a plague of snakes.
But what is the difference between cost reduction and cost optimization? In cost reduction, short term profit is sought at all costs, resulting in a reduction in the quality of the resulting product. Optimization, on the other hand, seeks the long-term potential of the product by working on the basis of the overall strategy and not on the basis of the individual product. To illustrate this better I will give two examples that we can see around us:
Mercedes changes the engines of its A-Class for Renault engines. It is direct, they want to keep the price of the cars or even get them ahead of their competition (BMW and Audi) by reducing costs and unfortunately quality.
On the other hand, and partly following the fashion, all manufacturers are starting to replace their buttons and needles with screens. It is not so much fashion as cost optimization. The buttons, the wiring, and the control unit that controls them used to be cheaper than the first displays. But with the evolution of technology it is now cheaper to save the buttons and offer a solution that (although more cumbersome at times) is an improvement. In the short term having to develop the software is an added cost, but the optimization comes when by offering something better (more visual, with more configuration options and even more intuitive) you are able to improve the cost.
Tesla, and I dont usually speak good about them, has a master degree in cost optimization. Their cars are pure minimalism but in a way that you can see how they have optimize resources to get rid of future problems. They are not reducing A-cost to solve A-problem. They are confronting A-problem to generate B-solutions that will help optimizing C-costs. This is for example visible in the new Model 3. Their backlights, between other elements, have changed.
A-problem: update the car
B-solution: new tail lights, giving the complete feeling of a new design
C-costs: before they are now one piece and not two they are easier to install, easier to avoid alignment problems and therefore making improvements in quality.
Cost reduction usually has a very bad ending. You sacrifice product to improve profits but rarely are you able to go back. Once quality is compromised, the customer loses confidence. Investors will always spect a continuation of their profits and will not understand why it was chosen the short term gain sacrificing the long term gain. Dont believe me? Boeing current crisis started brewing over 20 years ago. They decided to reduce costs for a better "growth of the stock". Few years after the quality have gone down so much that they even recuse their quality checks (also this way they could save more money). Right now it is very clear the strategy has damaged the company to the point where many employees, including BoD, will refuse to fly some models of their very own company. To regain confidence not only from employees, but from customers, industry and authorities is going to require a bigger investment as the savings generated.
The manager, who sees the short term gain and not the long term pain, is unable to realize that it is precisely this drop in quality that leads the company to have to redouble its efforts (and possibly invest more money) to win back the lost customers. Its a catch-22 situation. Soon will the problems not only come from a unsatisfied customer, and an angry investor. Soon will the companies delivering the product cancel their contracts to avoid further damages to their balances. Soon they will find no one willing to offer them new products, bringing their options to a complete stall.
I highly recommend the book Onward by Howard Schulz (ex-CEO of Starbucks), where he explains how Starbucks regained the public's trust and improved its image while optimizing costs. Precisely at a point where they were about to stall they decided to take the very risky but very necessary decision of stopping everything, getting rid of the mistakes made, and starting again.
Optimizing is more complex than reducing. It is like playing a chess game. You dont go for the obvious solution. For example: instead of installing three lamps, we install 2… a 33% price reduction. You see your chances you have, both in the long term and with the current situation, and you start working on the A-B-C… what is the problem, what could be the solution, what costs will be affected.
A- Problem: You need to change the lighting
B- Solution: You choose a better system that cost 10% more but is 75% more efficient (LED lights compared with incandescent lighting)
C- Costs: You have spent more money on the short term, but you will have a 75% savings on the long term.
Optimization requires not only a basic understanding of the needs short and long term. It requires as well the capacity to detect where the problems are and how they can be solved. To accept the problems and to work towards long term solutions. You have to be willing to walk the process (A-B-C) until you understand that the solution you are taking is not sacrificing any of your long term goals.
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