Getting the best value out of any complex system - including business strategies, personal development decisions, life and spiritual goals - involves consideration of a wide range of inputs and alternate options to arrive at an optimal solution. The challenge of deriving an optimum is either approached as an aggregation of several local optima or as a global optimum decision. Let's explore how the systems approach enables robust and optimal solutions .....
There is always a need to make an optimization decision on a business strategy, personal commitment, life goal, career path etc, making trade-offs on how to appropriate funds, spend time or other resources, in order to achieve the best value out of the situation given the variables and constraints that impact the situation or system. Determining an optimal solution can be a daunting task when complexity is involved due to the many moving parts and interactions involved in a complex system. Most individuals and organizations often address large optimization problems by attempting series of smaller optimizations or spur of the moment decisions in the hope that the aggregate of the respective 'optimal' decisions would be optimum for the overall system. This cannot be any further from the truth, as a decision that is optimal for a portion of a complex system may not be the best approach when the frame of reference is expanded to the larger system. For instance, the decision to cut back on maintenance activities on a factory line in the face of cost pressures may appear great in the interim until the impacts of the skipped maintenance results in major breakdowns which then cost more to fix with attendant loss of revenue, impacts to customer needs and associated loss of good will. In our personal spaces, everyone can think back to at least one decision that looked great in the spur of the moment but that turned out to be a 'not so great' decision in light of other considerations or impacts.
.....a decision that is optimal for a portion of a complex system may not be the best approach when the frame of reference is expanded to the larger system.....
The Systems Optimization Approach....
A benefit of the systems thinking approach is the ability that it provides to elevate the optimization conversation to consider the whole system, interactions, interfaces, stakeholders etc in arriving at the optimal decision. It ensures a big-picture focus in coming up with the best decision that serves the purpose of the interconnecting parts. For instance, in a career development 'system', a decision may be made to take a pay cut to undertake a development assignment in a different role or industry. To an untrained eye in such a scenario, it might appear to be a bad decision especially in the face of pressing financial demands. However, in a lot of instances, such decisions have proved to be pivotal to ultimate career leaps. Hence, a sub-optimal decision for the financial subsystem in the short term was optimal to the personal development subsystem in the same time frame and ultimately lends itself to optimal long term career and financial subsystem outcomes. A narrow focus on just the financial subsystem in the initial frame may have resulted in getting stuck longer-term in a sub-optimal career without attendant long-term financial benefits if growth opportunities are absent. It would somewhat appear that the system thinking approach facilitates a journey into the future to enable an optimal decision in the present to guarantee value delivery in the future. It is however worthy of note that the definition of what might be optimal would differ based on the qualification of value and the specific contexts of the systems in question. As such, the pay cut decision instance discussed above may not necessarily be optimal for all individual in all contexts.
.....It would somewhat appear that the system thinking approach facilitates a journey into the future to enable an optimal decision in the present to guarantee value delivery in the future......
What then are the key things to consider in keeping with the big-picture systems approach in optimization?....
The optimization measure of success...
A critical question in any optmization decision is that of the 'objective' of such an optimization - what exactly are you looking to achieve? In a business, it could be maximization of market share, or minimization of operating cost, or minimization of inventory etc. In personal development, it could be to maximize financial gains, maximize impacts/legacy, maximize influence, minimize disruptions to critical personal life events/interactions, etc. As I typically like to think of the spiritual perspective to provide a rounded approach, optimization in that zone could be to improve your zen - inner sense of peace, maximize returns to the master investor, to maximize your spiritual impacts, amongst others. Often in complex socio-technical systems, optimization involves more than one objective to be achieve simultaneously in what is known as a multi-objective optimization problem.
The true value / objective of an optimization using a systems approach must be aligned to the overall goals of the system. What really does success look like in the overall scheme of things? As an example, think of the goal to maximize financial gains achieved by sacrificing critical relationships and personal health; and it would be a significant stretch to justify such an objective except in unique extreme personal circumstances / contexts. Decision and alternatives prioritization in an optimization is driven by the definition of value. Hence, determination of value is a critical step in framing your optimization conversations. For instance, in a business context, while 'minimizing cost' may appear similar to 'maximizing profit' as a key objective, they are significantly different and drive different 'behaviors'. Maximizing profit may allow some interim cost increases to guarantee a significant increase in revenue aligned with the overall goal, an option that would be off the table in a cost-only focus even though the underlying intention of the cost approach may have been to improve profit. Hence, it is critical to ask, "what really am I trying to achieve?" leveraging the solution-neutrality definitions of value in system thinking.
An interesting example to buttress the concept of overall value as it guides optimization decision is one of a cartoon I had seen a couple of times of a person who had to carry a cross alongside other people. Over the course of journey, it was somewhat uncomfortable for the individual to carry and so at any opportunity the individual trimmed off the end of the cross to make it lighter. However, at some point in the journey, they all arrived at a deep gulf and the only way to get across was to place the cross across the gulf to get to the other side. Of course, this individual was stuck and could not move on. The true value of the cross (i.e. bridge) was now apparent but it was too late as the seeming optimal decisions previously to 'lighten the burden' had diminished the overall value of the bridge. The ultimate assignment could no longer be delivered due to resource shortages. It is a classic example of how we think that we are making the best local decision but shortchange the overall outcome by narrowing off all the opportunities to add value due to the serially optimization.
.....in a business context, while 'minimizing cost' may appear similar to 'maximizing profit' as a key objective, they are significantly different......
The right system and optimization boundary definition....
The definition of value often varies slightly from one system to another given the specific context in which such a system delivers it services. Hence appropriate system definition is important for the optimization process to enable value characterization, define true variables and identify the constraints (what you cannot and will not compromise) driven by the system context. Taking a queue from systems engineering, the definiton of your system must progressively answer some critical questions. It is important to define the critical stakeholders that interact with the system, the value that is expected from the system (career, business, relationship) from the stakeholders, the overall approach of the system to deliver the expected value, the interactions within the the components of the system that help meet this goal (e.g. for career it could be the combination of roles, years of experience, trainings, connections, etc.), what potential emergent behaviors are likely to be seen from the interactions of the subsystems that could impact the overall system performance (similar to maintenance impacts of the factory line productivity discussed earlier), etc.
In some cases, the time horizon under review may also be critical to the system definition especially in a dynamic system where stakeholders or system behaviors change regularly. The best decision for today may not be the best overall decision over a 10-year horizon. A common instance is that of career professionals who de-prioritize family time in favor of career progression early in their journey with the hope that there would be time to compensate in future. Unfortunately as with the 'return trip' effect, the journey back from the career pinnacle often appears significantly shorter as the many landmarks missed on the outward journey now seem too many to explore. In addition, due to the dynamic nature of the scenario, the young children seeking for attention on the forward journey are no longer there and are now replaced with teenagers and adults who are now ‘equally busy’ and not interested in trying to make up those 'lost times'. The upfront definition of the system for the individual may have pointed out key stakeholders in early life career decisions and hopefully qualifying value differently in the optimization equation.
.....appropriate system definition is important for the optimization process to understand the value, true variables and the constraints (what you cannot and will not compromise) driven by the context.....
Taking one for the system 'team'.....
What then, is the best way to optimize? A common error is a pseudo-system approach to optimizing is an attempt to assign a flat optimization factor to all components of the system expecting every part of the system to be reduced or increased by the same effect. In actual systemic optimization though, it is not uncommon for one party or system to receive a 'free pass' or even get allocated more resources in order to achieve an optimal system. Optimizing the system may result in gains in some subsystems which are beefed up to support others; with loses in other subsystems driven by elimination of duplicate activities in favor of a central support. For instance, in the current digitization efforts widespread in the corporate environment, more money may be spent on state-of-art equipment to beef up technology that replaces tons of manual activities and improve data availability for more efficient decision making. These combined impacts would result in significant losses in some other departments whose tasks are now eliminated leading to significant cost reduction that more than offsets the increased expenses in technology. Such an optimal solution may not have been achieved if a flat percentage cost cutting was applied to all departments, in which case the existing manual tasks remain the same with less man-power to execute them which in turn results in productivity losses and increased costs from rework and delays in handoffs from one team to another. The result of the latter approach is counterproductive to the intended optimization. Hence in most systemic optimization including life decisions, some aspects of the system may often be required to take a significant impact for the overall system gain - 'taking one for the team'.
.....Optimizing the system may result in gains in some subsystems which are beefed up to support others with loses in others, such as the elimination of duplicate activities in favor of a central support......
So, teeing it all up.....
Given that we do not have an infinite resource pool and there are multiple options available to utilize these limited resources with varying outcomes, optimization is very critical to define the 'right' investment option that guarantee the best outcomes for a long-time horizon in a situation where there are no assurances of the cards that will be dealt in the dynamic future. A systems approach drives the optimization focus to key interactions and interfaces that may otherwise be missed.
Hence, before you make that decision or trade off on your key resources - time, finances, people, etc. - ask these critical questions as an individual or business to elevate the optimization decision and improve probability of success of the outcomes for the overall system …. Is the optimization decision and time horizon appropriately framed? What is the optimization objective? What is the true definition of value of the system or decision in focus? Are all the key stakeholders identified? Are they prioritized appropriately? Are key interactions identified and included in the optimization? Am I truly optimizing the 'system'?
Wishing you a transformational time ahead,
Funmilola (Funmi)
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