Once in a while consumers face more complex and difficult problems they need to solve in order to achieve some end goals. These problems are likely to be compounded by multiple decisions, and furthermore, some of the decisions could be inter-related or interdependent. In the process of problem solving, consumers may be required to perform several different tasks; the process is likely to require evaluations, judgements, and making choice decisions about their next steps. Engagement in solving such problems can be challenging and demanding, but it can also be more gratifying — when reaching the end goal.

Problem solving binds together learning and performance: Learning about the possible operations at each stage that the solver may choose from for making the best move to advance from the current state to the next; and, performing the chosen operations to progress in solving the problem towards the end state or goal. The challenge entails figuring out what is the major factor causing a difference between an initial or current state and an end or target state, identifying what operations (or actions) can be taken to reduce that gap, and choosing the operation to perform. One has to realise that such problems tend to include interim states and sub-goals, requiring a decision at each stage (another reflection of these problems being compound). In other words, for solving the greater problem, an individual (consumer) may need to go through ‘sub-problems’, wherein one has to reduce a gap between an interim state and a target state representing a sub-goal (e.g., for removing an obstacle, overcoming a constraint) before being able to progress in reaching the end goal. People are generally seeking to advance to a state that seems to them most similar to the end state (goal), yet they appear less pleased to enter into steps they perceive as a deviation from the direct route to their end goal. The caveat of reluctance to solve sub-problems is of course that unless one goes through them the route to the end goal may remain blocked or inaccessible. [1]

  • An example shown illustrates how the model conception above of problem solving plays out in the case of the puzzle-game ‘Tower of Hanoi’ (in this game no disc can be put on top of a smaller disc, therefore a player has to move a small disc from a pin to clear the way for a larger disc from another pin, needed yet to free the way for moving another disc at the bottom of the latter pin). [1b]

A consumer may face a more complex problem, for example, when devising a travel plan for vacation in which he or she wants to stay in several destinations (e.g., cities, holiday resorts) in a foreign country (or in a few neighbouring countries). This is a travel plan that involves more than flight + hotel package that one may relatively easily order through an airline or an online tourism booking platform — it requires more effort in choosing destinations, scheduling and coordinating bookings of transportation and hotels (one may add to that pre-ordering of visits to events or tourist sites). The end goal is creating an itinerary plan that includes the desired locations with timely connections between them to create an enjoyable and smooth vacation.

Decisions are likely to be interdependent because the choice of one location for specific days may clash, for example, with non-availability of hotel rooms in the next location; bookings of all rooms are also contingent on the flight dates possible and available. The complexity of planning the vacation would also depend on whether one chooses to rent a car or use public transport (e.g., trains). It can be a time consuming effort to solve the problem of devising a working itinerary plan, but the reward is clear if one reaches a satisfying plan for the vacation, which may include family or friends. (Note: The example concerns only the pre-travel stage — one should always be prepared for resolving new last-minute problems that may arise during the travel journey itself, and ‘fix’ the plan.)

A highly significant problem (which also presents an opportunity) in a consumer’s life is probably in organising and designing a new (owned) apartment or house. Solving this kind of compound problem, entailing multiple decisions, can be a time-enduring project (e.g., when it extends during the construction period of the building). Organising may imply deciding the layout desired for the apartment, such as what rooms it will include, and how they will be used. Designing the apartment may go into many details of format and visual design — indeed the consumer may do well to get the advice of an interior designer, yet make specific product choices according to one’s aesthetic taste and functional needs. Equipping the apartment with fixed furnishing systems or electric appliances is likely to be done at a later time, but usually one has to plan for placing them in advance, while organising and designing the apartment.

To put the example in the context of problem solving as described above, suppose that our consumer, say Dave, visually simulates in his mind’s eye how he expects the apartment to be set-up and look (‘end goal’). The starting point for organising the apartment is the plan created by the architect of the building (i.e., the ‘default’ plan). The first step is visualising the difference or gap between the default plan as starting state and the desired visual mental image of the apartment as the end (goal) state (including its layout & interior design). The core of the problem solving process for Dave is figuring out and performing the steps needed to get closer towards his end-goal image of the apartment, going through multiple stages and choice decisions.

Realistically, especially as much as the visual appearance (design) of the rooms is concerned, the end-goal image is unlikely to be firmly conceived and specified at first, described more plausibly in the form of general ideas (e.g., colours, textures, materials). As Dave progresses, he may learn about available products (tiles for flooring or walls – default ‘standard’ options offered and possible upgrades), and their costs, thereof the end-goal can be updated and better formulated while decisions are made to choose the products that implement the desired design most closely. A perspective taken from other theories of decision making may tell us that decision processes do not necessarily progress in a linear way, allowing for ‘cycles’ in which consumers go back and forth updating information and choices; additionally, in less familiar and more complex situations, consumers’ preferences may not be well-established in advance, thereby consumers gather information, learn and construct their preferences as they proceed [2],

Returning to the problem-solving framework, interdependence between decisions or moves can manifest in the form of a ‘sub-problem’; for example, making a certain choice about the setup or design of the apartment requires sorting out first a particular condition in another aspect or area of planning. Suppose, for instance, that Dave has a furniture with interior lighting installed which he intends to place in a preferred location; Dave should make sure to request an electric socket close to that position and perhaps also a switch nearby to turn the light on. A similar situation of ‘nested problem’ may arise also in planning locations for electric appliances in the kitchen (e.g., refrigerator, cooking oven, dish washer). Decisions are often tied in different ways.

The ‘apartment problem’ can also be viewed from the perspective of Jobs to Be Done theory [3]. It may shed light on how a consumer like Dave may approach the project of organising and designing a new apartment. The ‘job’ is like the end-goal Dave wishes to accomplish with his apartment: what he intends to do in the apartment (beyond the basic need of ‘sheltering’). In a more complex job like this one, Dave may break-down the grand job of ‘living in the apartment’ into several sub-jobs, such as working on his computer (in a study room), hosting guests for dinner, watching TV programmes and cinema films by streaming. Each planned job for the future may have its own implications for performing it successfully. Then Dave has to co-ordinate between the sub-jobs in order to build them together into a coherent grand job of enjoying his experience of living in the apartment, possibly with others.

In practice, consumers are likely to find out that they cannot always solve the problem in the way they wished to or thought to be the more effective way to do so at any stage or on any of its aspects — one has to proceed under constraints, interventions, and restrictions. For example, Dave may find himself in a situation where the selling person in the store for products used in fitting the apartment leads him through products and options in an order or direction that conflicts with his intentions or approach to solve aspects of his problem. Sometimes the seller is helpful as a guide (having better knowledge and experience in performing these acquisition processes), but in other times the seller has different objectives or approach from the consumer’s, and that may create confusion, stress, and later regret on choices made (e.g., this may lead to going back through previous decisions already made and modifying them). Still, one should be prepared for disruptions while implementing the planned solution on site.

  • Important note: For simplicity, the two examples given above assume a single person-consumer is solving the problem. Of course in holiday travel and in moving to a new apartment, a number of people (family relatives, friends) are often likely to take part. Solving such problems as a group can complicate further the process in a number of ways. Consequently, it is not rare to find that a group nominates a trusted member, with better acumen and good taste in the domain, to make much of the planning (‘problem solving’) on their behalf while occasionally consulting or updating the other members on specific matters.

Solving more complex problems requires consumers to exhibit deliberation and persistence. In some stages the process can be daunting and frustrating (e.g., increased cognitive effort of negotiating multiple alternatives, conflicting sub-goals, difficult constraints). Yet, reaching a satisfying solution, and thus accomplishing one’s end goal (as closely as one could expect), offers opportunity for improving consumers’ quality of life, gratification, or sense of accomplishment and pride. To get there, it is important to keep one’s eye on the end goal, but also to be ready to update and adapt it to reality while on track to solving the problem.


[1] Drawing on (a) “The Processes of Creative Thinking”, Herbert A. Simon with Allen Newell and J.C. Shaw (1962/1979), in Models of Thought (editor Herbert A. Simon), Yale University Press; (b) “Problem Solving and Learning”, John R. Anderson (1993), American Psychologist, 48 (January), pp. 35-44.

[2] Referring to the research work of James R. Bettman on decision processes (“An Information Processing Theory of Consumer Choice“, 1979) and his research programme with John W. Payne and Eric J. Johnson on the constructive view of preferences and decision strategies (e.g., “Behavioral Decision Research: A Constructive Processing Perspective”, 1992, Annual Review of Psychology, 43, pp. 87-131); “The Adaptive Decision Maker“, 1993, Cambridge University Press).

[3] Drawing on “Competing Against Luck: The Story of Innovation and Customer Choice“, Clayton M. Christensen, 2016, Harper Collins Publishers.

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