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The risk of ignoring management science in marketing

The risk of ignoring management science in marketing

In the post of March 31st, I was referring to the fiftieth anniversary of Montgomery & Urban beautiful and fundamental book on management science in marketing, now unfortunately out of print.

In their introduction, they had listed the six major factors that were slowing down the growth of this discipline, also known as operations research and almost totally overlapping the area of decision analysis.

Let’s see whether and to which extent the situation, as it was described by these authors (slightly adapted and summarized), has changed after fifty years, and, possibly, what could we do about that.

  1. Complexity of marketing phenomena:
    • as we have already discussed in a previous post, the response to market stimuli tends to be highly nonlinear, exhibiting threshold and ceiling effects; the famous S-shaped (or logistic) curve!
    • furthermore, the response to this period’s investments (like a promotion) will occur in future periods (the so-called lags), the positive or negative effects of previous investments can have a cumulated impact on current results (carry-over), and the market’s reactions could easily decay in the absence of continuous stimulation
    • the market response tends to be dependent upon the convergence of many factors (multivariate.
  2. Interaction effects in marketing variables. Strictly related to the above, the impact of any single controllable variable is difficult to determine due to its interaction with:
    • the environment: level of economic activity, availability of credit, customer expectations, etc.
    • other marketing variables: sales depend on a combination of product quality, prices, distribution, etc.
  3. Competition and marketing decisions: the final outcome of marketing decisions depends upon how competitors react, while in many production and finance problems competitive effects are negligible or considered exogenous.
  4. Instability of marketing relationships, due to changes in tastes, attitudes, expectations, etc.
  5. Measurement problems: the consumer-oriented nature of marketing makes response relationships difficult to observe, requiring the recourse to indirect techniques.
  6. Incompatibility between marketing and operations research personnel: marketing decisions makers are rarely willing to accept or utilize quantitative techniques, while operation researchers are used to working with numbers and count on relatively certain phenomena and relationships.

In addition to the inevitable changes in the socioeconomic environment, that apparently accelerated and became less predictable on a worldwide basis, the continuous and exponential development of information and telecommunication technologies has certainly contributed to the exacerbation of the first four factors.

On the other hand, it seems that the same explosion of ITCs is helping at significantly reducing the impact of the last two factors. In particular:

  • Artificial Intelligence has finally become widespread and relatively accessible in many areas of our life, business included: I remember when, together with some colleagues and friends, I presented a small expert system to support SMEs’ marketing decisions in a UK conference for few maniacs in the early nineties!
  • Web analytics are increasingly making available to everybody a number and quality of data about consumers’ attitudes and behavior that were totally unimaginable just two decades ago.
  • Business Intelligence is finally becoming somewhat intelligent (!), instead of just being a sort of flexible reporting system as it was in the past since it started to include some diagnostic features based on multivariate statistics.
  • Last, but not least, even the well-known and basic spreadsheets, that were a breakthrough for few (and fanatic) early adopters in the late seventies and early eighties (some of you will remember VisiCalc, Framework, Symphony, and Lotus 1.2.3), are now on the desks of practically everybody, even in the smallest companies, and Excel’s Pivot Tables, the precursors of BI, are increasingly used to analyze relatively large datasets.

In practice, marketing people cannot afford to be, as stigmatized by Montgomery & Urban, rarely willing to accept or utilize quantitative techniques (and be afraid of technologies) anymore! Better move our ass!

But you could have found some good news for all of us with a humanistic background (and weak in maths) in the post of April 28th.

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