Category Archives: Demand

Product Differentiation Dashboard

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It makes economic sense to have more than one product version because of increased revenue generation[1].  There are additional reasons for versioning in addition to revenue generation. By having multiple versions of a product you can experiment and watch economic behavior as consumers will focus on the features and products that are most desirable. This sort of experimentation is the basis of monopolistic competition and the mechanism that allows the entrepreneur to successfully compete.  Product versions can be generated in a variety of ways including, distinct product features, product design, product promotions, product availability, warranties, and through customer service.

We have developed a product differentiation dashboard to assist with understanding the concepts and to help in determining how differentiation can improve revenues. The spreadsheet is currently in Beta development, but it is available for your perusal. The spreadsheet can be used with 3 products at this time. For now, it assumes that there is only one demand curve for the differentiated products. You can use the results from the Demand Dashboard discussed in the last post to identify the slope of the demand curve and the price where demand is close to zero.

Here is what you will enter in the Differentiation Dashboard.

  • The slope of the demand curve and the price level where demand is close to zero.
  • The variable and the fixed costs for a single product.
  • The variable and fixed costs for the high-end, mass appeal and low-end products.

Here is a link to the spreadsheet: https://skydrive.live.com/redir.aspx?cid=a3660eed58d91ed9&resid=A3660EED58D91ED9!107&parid=root

Special thanks are extended to students in the Technology Management Course for their suggestions for improving the spreadsheet. As is always the case; simplicity should be the goal and they helped to achieve that goal.

[1] Goldilocks pricing is a rule of thumb that suggests that you should start out with three price levels and offer additional versions of products to attract additional revenue (Varian and Shapiro, Information Rules, Harvard Business School Press 1998). The idea behind Goldilocks pricing is that one product is too few, ten products too many and three is just the right amount. Thus one arrives at Hermes, Mass Appeal, and Midas.

Demand Dashboard

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When large organizations develop demand curves for existing products they turn to a variety of quantitative and qualitative approaches. Historical data plays an important role in developing and constructing demand curves for existing products. The historical data can also be used to forecast future demand using time series analysis and statistical approaches such as regression analysis and moving average approaches. Organizations can also draw on qualitative approaches such as market surveys, focus groups and the Delphi technique to gain additional insight into market demand.

Many entrepreneurs do not have the time, money and interest to engage in these approaches.  They are probably on the right track because it is often difficult to determine the demand for new products. This is particularly true for products and services that have been radically redesigned and in so-called Blue Ocean markets. The historical data is either not available or it is not appropriate for the context. Very few economic and marketing textbooks have actual data that can be used to construct a demand curve. Most of the data sets are generated by taking a demand curve (such as p = 80 -.2q or q = -5p + 400) and then generating the prices and quantities.

We have developed a Demand Dashboard to assist with identifying demand curves. The spreadsheet is currently in early Beta development, but it is available for your perusal.  You can get the spreadheet from my SkyDrive at https://skydrive.live.com/?cid=a3660eed58d91ed9&id=A3660EED58D91ED9%21107.

Here is what you can do in the demand Dashboard:

  • You can just enter the slope and the price where demand is close to zero and just play around with the curve.
  • If you want to use a statistical calculation to determine the demand, you will need at least 2 demand points to plot. If you want confidence intervals for the slope estimate you will need 3 points. Each point will represent the price and the demand quantity. One point can be the price level where demand is close to zero. You can also use the statistical estimates to manipulate the slope and the price level where the demand quantity is close to zero.

If you have access to IBISWorld  you can obtain some demand and market research information that can be used to assist in developing demand curves (this data is available to University of Buffalo faculty and students). The Economic Research Service for the US Department of agriculture also has some data that might be of interest, but it is of course mostly related to agriculture.

In the next  post we will present the  Product Differentiation Dashboard. It is part of the same spreadsheet that you can now dowlnoad from my SkyDrive. It will assist in making decisions related to developing different versions of a product.

Cloud Computing and Variable Costs

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Any discussion of cloud computing will certainly be accompanied with thrashing and gnawing of teeth.  This past August I was teaching a course on technology development in Bangalore and Chennai to managers and systems developers working for a variety of high-profile IT service providers.  There were significant areas of agreement; but there were some topics, which appeared to be splitting hairs, where the discussion was very intense. This is not surprising because the drama is in the details when it comes to market positioning and high-tech one-upmanship.  There is very little agreement on how to define cloud computing.

One of the benefits of cloud computing is that it should permit organizations to add and subtract computing resources according to need.  This means that the computing resources are scalable as workload increases.  This includes the ability to add more data storage and more computing power for web servers, database servers and applications servers for the human resource system, the CRM system, the financial and accounting systems and the inventory management systems.   You can even develop  applications in the cloud  using products such as Force from salesfore.com,  Google Cloud and Amazon Web Services. Google Docs is an online cloud application for creating word-processing documents, spreadsheets, and presentations. All of the browser-based applications of email are part of cloud computing. This Blog was created in the cloud.

Cloud computing permits companies to increase capacity by turning to the cloud, rather than by investing in additional capacity. Cloud computing simplifies management’s agenda because capacity planning is easier. In environments characterized by fluctuating demand risk is reduced because the breakeven point is lower. In an ideal cloud computing environment, the IT resources are scalable and the costs are variable and perhaps traceable to a particular product or service.

Cloud computing has the potential to be a major technological advance, but until we see the ideas and applications maturing it will still be approaching the top of the “inflated expectations” curve of the Gartner Hype Cycle with a  partly cloudy future.

Here are a couple of YouTube videos that explain cloud Computing,

Cloud gold

Cloudy Tonight and Tomorrow

Product Differentiation: Nokia versus Apple iPhone

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Product Differentiation and Cell Phones

The most important activity in the history of human kind has been in the area of communications (see Figure 1). The desire to communicate has been the driving force behind many advances in modern technology; driving a variety of  substitute and complimentary products and services.  The wireless phone is the current battle ground for the universal communication device that will be used for talking, texting and tagging friends and colleagues, scheduling, listening to music, reading eBooks, and in location assistance. Nokia sells nearly 40% of all phones and Apple sells less than 1%[1]. Apple and Nokia’s strategies are distinctly different. Apple has gone after the cream and focused on the high-end and competes primarily in the Smartphone arena and is also beginning to compete with the $300 to $500 net-book laptops. Smartphone’s have applications such as scheduling, location assistance, email, and internet access.

Nokia is interested in the high-end Smartphone market, but they are also selling to the price-sensitive demographic and have an even bigger target in their sight. They want to become the biggest entertainment media network in the world[2]. They are going to accomplish this through R&D with 10 labs throughout the world and by pursuing a comprehensive differentiation strategy with phone prices ranging from $10 to $700 (see Figure 2). Nokia offers devices to satisfy every budget and they are trying to make their products and services indispensable. They currently roll-out around one million cell phones per day and have 1.1 billion users. They sell mobile devices to the hundreds of millions of price-sensitive cell phone users in India that cannot afford a data plan. For $1.30 per month rural users in India can receive information on weather, agriculture, education, and Bollywood.  But they are also going after the high-end market high bandwidth market and have developed Ovi, an iTunes type platform with a variety of downloadable Smartphone applications.

Apple has been making steady gains in the smartphone business. They have about 8% of the market and Nokia has about 43% of the market. Apple has been willing to offer a down-scaled version of the Ipod to the price sensitive masses with the Nano and Shuffle. I suspect that iPhone technology will also be adapted to the price-sensitive tail of the demand curve.

[1] Jill Greenberg,  “iPhone Envy? You must be jÖking”, Fast Company, September 2009. http://www.fastcompany.com/magazine/138/iphone-envy-you-must-be-joumlking.html

[2] ibid