A632.3.4.RB_BorutyAlan_Framing Traps

Framing Traps

Hoch, Kunreuther, & Gunther, tell us that “frames influence our thinking by simplifying issues” (2001, p.137).  But, influence is not always positive.  Framing can help us see things in a different light, but it also narrows our view placing other considerations in the dark.  If framing your thinking on the best travel option for a planned vacation abroad and deep rooted beliefs tell you flying is unsafe, you may want to plan a cruise.  Given the same scenario with the same information and end result, your frame can cause you to choose one clearly over the other.  This is called establishing yardsticks or reference points.  You will not choose an option that even appears to violate your yardstick.  The result was exactly the same.  Your yardstick distorted your thinking and made one choice the obvious best option to choose.  These distortions in thinking can be invisible to you thereby making your decisions less objective, perhaps even wrong (Hoch et al., 2001).

Frame blindness is when decision makers are unaware of how framing influences their thinking and ultimately their decisions.  Frame blindness is not normally an intentional error.  Most offenders are completely unaware and are surprised when their decision causes problems.  Regardless, frame blindness can have serious effects on an organization.  Internally, frame blindness can cause miscommunication, conflict between departments, morale problems, and accusations.  Externally blindness can be devastating.  Making blind decisions can result in career and company ending decisions.  While anything is possible, I personally do not see people effected by frame blindness making it to important decision-making positions on the corporate ladder

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Frame blindness is but one of the framing traps that decision makers can fall into.  Other framing traps, are more likely to be seen in decision-making positions in business.  Choosing frames is not a passive activity.  The price for choosing the wrong frame can be very high (Hoch, et al., 2001).  Unfortunately these traps are easy to fall into if you fail to consider and choose frames correctly.

Framing traps can be avoided with some effort and practice.  Conducting a frame audit can help avoid traps under the premise that if you cannot see your own frames, how can you possibly manage them (Hoch, et al., 2001).  The audit consists of: 1) Surfacing your frames, 2) Understanding the frames of others, and 3) Appreciate Emerging frames.

 

I have been in frame traps more than I care to admit.  I have never consciously thought about frames until now.  It was always a matter of intuition and situational awareness.  Whatever it was it was automatic and it almost always kept me out of trouble.  Back in the late 1980’s I was a new Technical Sergeant (TSgt) in a new unit.  I am not sue if all new TSgts are cocky and over confident, but I was.  I went into my new boss’s office to introduce myself it was immediately awkward and uncomfortable.  I told him I was excited to be there and started talking about ways I felt I could help.  His response was to explain that he would decide what I could do.  Within a minute, he was angry and I was defensive.  I worked out of that office for almost a year before I moved overseas and we never communicated much better than that first day.  We constantly mistook the others point.  I failed to see my frame or his.  When I did see his frame, I did not adjust to something more compatible.  His frame was I am the boss and will not be questioned.  I was not willing to take on a submissive frame or stroke his ego.  He was not willing to even tone it down so I could work with him.  If I had on day one changed to a more subordinate frame, he would have eventually stepped off his throne and lightened up and we may have had a positive working relationship.  Either of us could have adjusted frames, but it was my responsibility to do that and I failed.

The second way to avoid framing traps is to ‘identify and change inadequate frames’ (Hoch et al., 2001).  I do not believe I realized that I approached and communicated with some people differently than others until late in my Air Force career and only then because I was told that it was an expectation.  And of course, I did my best to comply.  What I realized was many of the frames I used professionally were no longer effective, if they ever were.  As the “group Chief”, I decided to schedule time each week to manage by walking around.  When I first started this habit, I used a frame I used with friends.  I was trying to communicate with younger Airmen and hear their concerns, but was completely surprised by their reactions.  I got shock, suspicion, a couple of formal reports, one salute, and zero conversations.  After thinking about it for a while I understood.  I was the Chief, not their friend.  They expected me to be the Chief and did not want to be my friend.  I understood that position and while being their friend was out, I did not have to be the enemy.  I made the adjustments I thought I needed and my second MBWA tour went much better.  My goal was to ‘overhear’ some of the issues in their world and fix the ones I could.  I only made minor frame adjustments after that visit and only if I was seeing people I had not met before.  It took a few visits out and around the organization for people to get comfortable that I did not have an ulterior motive.  Through those visits I learned what was really happening in my organization.  The Airmen told their issues simply, truthfully, and accurately without embellishment or exaggeration.  And I acted on every issue they presented to me.  Some were out of my control, some I disagreed with, some were disapproved, and many I fixed.  I provided specific feedback on every issue explaining the disposition of the request.  It was effective and productive, and popular with the Airmen.  I got more things accomplished than I ever thought was wrong simply because it was important enough for me to change my approach when talking with Airmen in my group.  Hoch calls my first meeting and the reactions I got a frame misfit.  “Poor results, surprises (violations of expectations), inconsistencies, and difficulties communicating with others are indications of a weak frame.  Consider the possibility that your frame may be wrong or, at least, not perfect!”  (2001, p.147)

Finally, framing traps can be avoided if you ‘master techniques for reframing’ (Hoch, et al., 2001).  I cannot claim mastery in reframing although I have had to do a lot of reframing when I moved back home.  I was redefining who I am and what is important to me…a work still in progress.  I am in a new environment, my outlook on living is changing, different things are becoming important to me and they are replacing things that once were, and I am identifying what truly makes me happy.  All of these discoveries require reframing in some way.  I created frames where I had none before.  My hobbies fall into this category.  My relationship with my siblings required me to update old frames.  They did not change as much as they matured.  The slower paced, small town, everyone knows your business environment forced me to reframe on a number of occasions.  As I mentioned, frame work is still a work in progress.  Knowing what I know now, I suppose it always will be.

Reference:

Hoch, S. J., Kunreuther, H. C., &  Gunther, R. E. (2001). Wharton on making decisions. (1st edition.). Hoboken, NJ: John Wiley & Sons Inc.

A632.3.3.RB_BorutyAlan - Framing Complex Decisions

Framing Complex Decisions

Decision making in business has naturally become more complex over time as competition has increased and businesses, through experience, have gotten smarter about the variables that affect the industry.  However, the advance of technology and information systems has brought complexity to a new level.  Tools have been developed to help businesses make sound decisions in the middle of complexity.  This blog explores a few of these tools. 

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.  

A632.2.3.RB_BorutyAlan_Sheena Iyengar_How to make choosing easier

How to Make Choosing Easier

Sheena Iyengar’s TED video How to make choosing easier takes a detailed look at the effects of choice overload on consumers and provides solutions businesses can implement to mitigate the problem.  Ms. Iyengar and colleagues conducted a few experiments to determine if the number of choices involved in making a decision has an effect on the outcome of our decisions.  Her experiments were simple in design, but the results were consistent and conclusive.  The number of choices absolutely has an effect on our decisions (Iyengar, 2011).  In fact, the research showed that too many choices overwhelms us.  When we can no longer effectively keep track of the comparison data for each choice and making a choice is difficult, frustrating, or simply not possible, we have reached choice overload. According to Ms. Iyengar, “choice overload is one of the biggest modern-day choosing problems we have” (2011). 

Ms. Iyengar further explained that there are three specific and negative consequences associated with choice overload.  First, we may actually disengage from the process and actually not choose any option even if our best judgement tells us we should.  Secondly, if we do make a choice, we are much more likely to make a poor quality choice.  Lastly, if we do make a choice we are less likely to be satisfied even if we made the right choice (Iyengar, 2011).  These negative consequences resulting from businesses offering more and more choices can be avoided if businesses are willing to a make four simple changes.  Implementing the changes will have a positive effect on and benefit both the customer and the business.  The changes Ms. Iyengar discussed are; 1) cut 2) concretization 3) categorization and 4) condition for complexity (2011).

Cut simply means reduce the available choices that the consumer has sort through to make a choice.  The benefit to the customer is an “improved choosing experience” (Iyengar, 2011).  I would choose to say the consumer choice is faster, easier, and less frustrating.  By offering fewer choices the business’s sales will increase and the overall costs will decrease as less inventory is ordered, stocked, maintained, and inventoried.

Concretization refers to making the choices vivid and real in the consumers mind.  One of the ways to accomplish concretization is to clearly indicate the consequences associated with each choice.  Basically, anything that clearly illustrates why a choice is worth making over the other choices is concretization (Iyengar, 2011).  A simple example would be, clearly marking the prices for each choice.  This provides the consequence for making one choice over the others.  Dramatic photographs, illustrations, and diagrams are another way to make a choice more real and therefor, easier for a consumer to pick or pass. 

Categorization is beneficial to business because consumers can process more categories than choices.  Individual choices do not have to be cut, but they have to be logically categorized in a way that is meaningful to the consumer (Iyengar, 2011).  Magazines and books categorized by content like fitness, crafts, do it yourself, cooking, gardening, and self-help would be good categories to separate magazines, but categories should not be so specific that it reduces the number of choices to only one or two.

Ms. Iyengar’s fourth simple recommendation to business is ‘condition for complexity’.  If having to make choices numerous times before coming to a decision, the arrangement of each choice is important. By monitoring the customer’s engagement, it is possible to determine who is engaged and who is bored.  In her experiment, when the choices were arranged from the choice with the highest number of options to the lowest, they were, almost from the beginning, selecting whatever option came up as default.  When the order of the choices were reversed (low options to high) the consumer chose from the available options and stuck with it to the end.  The technique allows the consumer to ease into the process and slowly learn to make choices as they progress.  By the end they evaluated the numerous options and made their selection.  Starting slowly and easing them up in numbers of options actually conditioned the consumer for complexity.  They learned how to choose even though one choice had no relationship with the other options (Iyengar, 2011).

Personally, I was surprised by the research findings on the number of choices.  I have always claimed a preference for more choices so that I could compare price, quality, brand, function, and features.  And most of the time, I do.  I was taught to look at all the information before making a decision.  I believed a reasonable assumption was more choices would result in a better or the best choice being made.  However, Ms. Iyengar insists that, in this case, “less is more” (Iyengar, 2011).  This caused me to reflect on some of the choices I have made, I realized that when I am planning a purchase, I actually limit my options to two or three before comparing details and making my decision.  Sometimes I limit my choice to certain brands, other times I am more concerned with price, and sometimes I am looking for specific features, but I consistently limit my choices as long as I give myself time to plan.  In circumstances where pre-planning is not possible and the options are many, I can easily see myself staring at the options and agonizing far too long over which option I should pick.  I am guilty of getting lost in the choices especially when I have seldom or never bought a product before or if I am purchasing an expensive item such as a vacation package, furniture, or appliances.  If I find myself staring at the options and going back and forth between products, I determine if I have to have it right away.  If so, I pick a brand I am familiar with.  If not, I walk away.  The internet has helped me a great deal because I can and do research it at home and make my decision before I leave the house.  

If Toshiba had incorporated ‘condition for complexity’ or not given me the option to ‘build my own’ laptop at all, I would have bought my computer the first time I visited their site, would have received my computer two weeks earlier, and would have spent two hundred dollars less.  But they did not and neither did I.  I needed a new laptop and I wanted another Toshiba.  As I looked through their site, they had several machines that I liked but none had all the features I wanted.  I finally found one that was a fair compromise between speed, storage, memory, screen size, and price.  Then I saw the ‘build your own’ option.  I should first say, I had no business building my own laptop.  The selection options were in no particular order and were confusing.  There were about fifteen decisions with choices ranging from one or two to eight or so and some had if/then conditions.  I tried to go through the selections but found myself scanning all of the selections without choosing anything.  So I decided to give it some more thought.  After a day or two I went back to the site with the same results.  Finally, I did some research which helped me get through the selections and I ordered my machine.  After checkout, I realized that when you build your own computer, it is assembled in and shipped from China which added over two weeks to the delivery.  The build your own layout and functionality definitely affected my ability to choose the options to build my own computer. The beginning selections were complex and riddled with options that were affected by later choices.  The last choice was for the screen and had only one option to add touchscreen.  They definitely needed to be organized and clarified.  I ended up with a very nice computer that I like very much and use every day. Looking back on it, after my second failed attempt to build my own computer (or earlier), I could have easily gone back to the machine I picked out earlier.  I would have ordered it that day, received it in two business days, and payed less money.  My computer skills would never have noticed the difference.  I overbuilt my machine and it has capability that I do not use, but I do not regret my purchase.  I got a nice machine at a good price, but simple math tells me I made the wrong decision.  Some of it can be attributed to Toshiba not conditioning me for complexity, but not much.

I enjoyed Ms. Iyengar’s presentation.  While the findings were different than I expected, they make sense.  I came to realize that I was cutting options on my own by doing research before making my final decision.  I believe I can make my decisions easier by researching all of my out of the norm decisions beforehand. 

Concretization would also help improve the decisions I make.  I have a tendency to be a bit impulsive when I want something.  Being patient and waiting on the decision until I get a full understanding of all of the options would definitely help.  I think the example of building my own computer fits better into concretization than complexity.  Most likely my failure to get a full understanding made the experience more complicated than it should have been.

Reference:

Iyengar, Sheena, (2011). Sheena Iyengar: How to make choosing easier. TEDSalon NY2011. Retrieved from: http://www.ted.com/talks/sheena_iyengar_choosing_what_to_choose

A632.1.4.RB_BorutyAlan_Multistage Decision-Making

Multistage Decision-Making

Reading the text on multistage decision-making convinced me without a doubt that assessing the future impact of a decision made today is complicated.  The model used by researchers is based on assumptions that affect the outcome, utilizes a level of mathematics well beyond the skill of the managers that are making the decisions and does not produce an absolute answer for every situation (Hoch, Kunreuther, & Gunther, 2001).  Managers use their experience, expertise and intuition to predict future performance of the market in which they compete.  Despite the limitations humans have with forward planning, changing our view of the current world based on lessons learned from the past, and our ability to accurately perceive the present, task experienced managers intuition produces surprisingly accurate results (Hoch, et al., 2001).  I see this as an illusion.  Sooner rather than later the illusion of intuitive ability will fail.  Betting on an illusion is a foolish bet.

As an Air Force leader, I was often tasked to make supply and manning decisions that were forecasted out for three to five years for planning purposes.  After gathering the applicable data, it was simple to look at demands out in the future.  The data was stable after years of averaging and produced fairly accurate results.  It was provided up the chain for leaders to plan future budget requirements ultimately for congress to fund.  However, no decisions were made on forecasted numbers.  They were updated so often by the time the decision was made, they were not forecasts anymore but near real time data.  This is a much simpler example than the manager that has to see the impact of a decision years out, but the concept still applies.  The manger is experienced with the market and has some expertise in predicting likely impacts out into the future as long as the past results are an accurate indicator for future performance and everything else remains stable.  But I would not bet the farm on it.  I would use optimal dynamic decision analysis to prepare strategy for operating in predicted future market activities as well as developing executable plans to take advantage of market changes.  However, in my opinion, committing hard resources on a prediction in today’s market is too risky unless you are driving or controlling the changes that will affect the market in the future.  Today the rate at which technology is advancing is affecting every market making accurate predictions difficult at best.

Reference:

Hoch, S. J., Kunreuther, H. C., &  Gunther, R. E. (2001). Wharton on making decisions. (1st edition.). Hoboken, NJ: John Wiley & Sons Inc.