A highlight of the Consumer Electronics Show (CES) is the latest in the competition between companies such as Samsung and LG to create increasingly thinner flat screen TVs. While these TVs contain new LED technology that can decrease the TV’s energy usage, the major advantage of these models is the decreased thickness. No prices are available yet, but they will most likely be significantly higher than comparable thicker models without an improvement in picture quality. So consumers will be asked to spend more for these TVs with the only real advantage being the novelty of the ultrathin design.
Sure the TVs will take up less space in your house and possibly will be easier to wall-mount, but how significant is this advantage given how thin flat screens had already become? Personally, I would prefer innovations that create lower-priced versions with comparable or better picture quality over more expensive, thinner versions. What innovations in TVs are consumers really looking for and are companies optimizing their decisions around these needs? What drives electronics innovations today?
Generally it seems that the cool factor and the race to have the thinnest/smallest/lightest product seem to be the primary driving factors of new design. And while it makes sense to focus on cool, new technology that attracts media attention, is this always the optimal solution based on what is actually a very complex objective? Operations researchers know that sometimes the obvious answer is not the global optimum. Would it be better to focus on achieving functionality that consumers really want but that might have less of a wow factor? Does the next MP3 player have to be the size of a button or are consumers more satisfied with larger, cheaper versions? The success of a product depends on more than just price and media buzz; better meeting customers’ needs may generate higher returns than creating cooler products.
Those familiar with operations research will recognize this as one of the classic OR problems: Determine what products to produce (and how much of each product) to maximize profits given limited resources (raw materials, manufacturing time, etc.). Like most real-world applications of OR, the problem requires more complex constraints and objectives. While raw materials and manufacturing time are definitely limited, so are time, people, and money for research, design and marketing. Companies may not have enough resources to simultaneously develop several versions of the same product. And the profit a company reaps from a product is more than just the dollars earned with each sale. It includes intangibles like the increase or decrease in customer satisfaction and brand awareness and value. And unlike linear programming applications, these different pieces of the profit are not necessarily independent.
Obviously this is a difficult problem to solve, with significant time and resources expended just to get the values for the coefficients, as well as the complexities of multi-objective optimization to overcome. And especially in fast moving industries like electronics, companies do not always have the time to perform detailed analysis for every product decision they make. But just formulating the problem, deciding on the various factors that make up the objective and the sources of constraint, can provide valuable insight during the decision making process. Sometimes it might be enough to think with a global-optimization point of view, to spend some time considering what drives profit, how the pieces interact and if the decisions being made are really meeting the overall objective.