Framing Complex Decisions
In the fall of 1992, I was a brand new Master Sergeant in the U.S. Air Force assigned to Kadena Air Base, Okinawa, Japan. There were contractors in the maintenance facility testing a new system. Then without any warning or fanfare, it happened. The box in front of me made a noise. The contractor said, ”There it is“. There were no bands playing, no parades, and no cheering crowds. I said, “There is what?” I had just witnessed my first email delivery. It was also the first time I ever heard the word Internet. I said, “So what?” and I left the office…unimpressed. That event took place just twenty four years ago. To some, it may seem like a long time. Consider this, Alexander Graham Bell invented the phone in March of 1876. Other than a few design changes and adding touch-tone in 1962, Bell’s telephone technology went unchanged for nearly 100 years as did the way we communicate. Cell phone testing began in the early 1970s (Ament, 2006). Now think about how technology has changed over only 24 years. In 1991, I did not know a single person that owned a cell phone or a computer. Today the opposite is true. That is amazing to me!
The rate of change in technology has not slowed at all. Today, business cannot compete without technology, yet they cannot keep up with the pace of technology. Technology has put out information on any and every topic available, at a mouse click, to any and everyone who desires it. So much information, in fact, humans cannot process it effectively or efficiently. This information is incredibly valuable, so we employ technology to gather, analyze, translate, and store it for us. Manufacturers replace products approximately every 18 to 24 months and end support for the replaced products shortly after that. Technological obsolescence occurs “when a technical product or service is no longer needed or wanted or when a new product has been created to replace an older version” (BusinessDirectory.com, 2017). There are legitimate reasons manufacturers replace products to include profit, keeping in line with industry standards, or to incorporate the newest technology into their product lines. Sometimes new technology is incompatible with the older version rendering the older equipment useless. Businesses cannot afford to take that risk. Therefore, most businesses develop plans to avoid technological obsolescence of their information systems. These plans normally establish a schedule to replace systems (that are in perfect working condition) every two or three years. We created a tool to help us be smarter, faster, more competitive, and more profitable and in the blink of an eye, we became slaves to our own invention. But, I digress.
The course I am currently taking is called Decision Making for Leaders. In this module, we are considering how complex environments affect the decision-making process as well as some of the tools available to mitigate complexity. Hoch, Kunreuther, & Gunther explain that “the environment of business has become a maze of information and Internet-driven change. This change is intertwined with the globalization of economic activity, the attendant growth in the size of companies and markets, the increasing importance of knowledge-intensive processes in business activities, and the natural evolution of systemic stress on organizations facing increased competition resulting from these forces. One result of these changes is a significant increase in the complexity of business decision making” (2001, p.118).
Data Complexity
I think it is safe to say every industry operates in a data-saturated environment. The textbook uses the phrase data-rich, but I would argue that data-rich does not paint an accurate picture. I would assess the amount of data to be an order of magnitude greater than data rich. Saturated seems the better description. Decision makers are having to abandon their old search engines and databases for data mining and warehousing tools that are far more advanced, can easily handle large amounts of information, and are more capable handling the data (Hoch, et al., 2001). Having data that is relevant, accurate, understandable in sufficient quantities is important to the decision maker. It saves time for the manager refining searches in hopes of getting the data needed to solve a problem or make a decision. Data mining produces data that is easier to interpret, evaluate, and determine variables to use in other decision making tools. Whether it be data-rich or data-saturated, more data that is organized understood, relevant, and useable is a good problem to have.
Systemic Complexity
Data drives systemic complexity, but it is not the only driver. The interactions of networked systems also adds complexity. The boundaries created by the interaction of multiple systems affect decision context (Hoch et al., 2001). These interactions add complexity by adding additional consequences to consider in the decision-making process. In the past, system interactions were ignored and decisions were made with little effect on the outcome. Today, most businesses are network dependent. The interactions represent operations more closely and can no longer be ignored (Hoch, et al., 2001).Computer models are the primary tool used to help make decisions in this environment. Modeling is used to capture interaction data. The models build upon the available data, consider the model itself, and optimizing or evaluating alternative decisions in the context of the model (Hoch, et al., 2001). Advances in technology have allowed modeling to become quite sophisticated, capable, and accurate. They require decision maker input and produce impressive results. These models provide an integrated look at sales, production, logistics, and some finance and accounting. They also track these functions for use in optimizing production and delivery commitments (Hoch, et al., 2001). Large-scale simulation models are also used in systemic complexity environments. Originally developed by the insurance industry to do earthquake modeling, these models are used in catastrophic event assessments. Large-scale simulation models are complex tools in and of themselves, but given all of the details for a given event, they can produce an assessment, in real time, on the impact a catastrophic event (direct hit from a hurricane) will have on the economy and business (Hoch, et al., 2001). They require significant expert data input.
Multistakeholder and Environmental Complexity
The interactions of multiple stake holders add a different sort of complexity to decision making. Multistakeholders from different, often competing roles and offices, come together in a manner of ‘co-opetition’ to establish agreed-upon rules to ensure he process does not become unstable or dysfunctional when problems occur. Examples of processes include utilities and insurance underwriting where standardization is required for the public interest and multiple entities have an interest in the process. The rules commit the different stakeholders to agree-upon support, responsibilities, etc. A new approach to the multistakeholder complexity issue is to listen to each of them. Each is assumed to have a legitimate alternative point of view. Each must be heard, understood, tracked, and influenced but not completely controlled (Hoch, et al., 2001). Listening and hearing in this manner makes stakeholders equal in voice and responsibility. I do not believe listening to each side in a conflict situation is a “new” approach, but I would agree that it is a good idea and a starting point to resolve an issue. In addition to listening and creating consensus multistakeholder interactions are supported by behavioral approaches like role playing using long–range simulations so the stakeholders can see who would win and lose given a certain scenario. Strategic models that are used include advanced simulation tools. Stakeholders can see the impact of their decisions for each year over a ten-year period. Many different games of this type are used to prepare stakeholders for the effects of their decisions on the larger picture and serves to help develop a more cooperative relationship (Hoch et al., 2001). Business is a fast-paced, high-risk venture before inserting technology, endless streams of data, and having to accurately predict your next move to stay ahead adds stress to to the situation. There is no doubt it is a complex, high-pressure environment that is difficult to survive in. My question is, how did businesses grow and succeed without the critical data we now have? Are we making things harder than they should be or is this really a new world we live in? Modeling and simulation tools have made it possible to help business manage the complexity that technology has added to making good decisions. Technology continues to advance daily. Can we keep up? There are differing opinions, of course. Is technology a blessing or a burden?
References:
Ament, Phil, (2006). Telephone. Troy, MI: Copywrite 1997-2007 The Great Idea Finder (2006, 11January). Online. Available: http://www.ideafinder.com/history/inventions/telephone.htm Accessed: (2017, 26 January).
Business Dictionary.com, (2017). Technological obsolescence. Retrieved January 26, 2017 from: http://www.businessdictionary.com/definition/technological-obsolescence.html
Hoch, S. J., Kunreuther, H. C., & Gunther, R. E. (2001). Wharton on making decisions. (1st edition.). Hoboken, NJ: John Wiley & Sons Inc.
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