Why is your SMART goal not smart?
Content:
In this article, I would like to challenge the SMART goal setting, allowing us to see the conditions in which the classical methodology, with its specifics and measurables, might not serve its best. While expecting the SMART to facilitate solid motivation and confidence, it might lead to misleading conclusions that the goal that was set has not been specific, attractive, or realistic enough — you name it.
But is that so?
1. What is a SMART Goal?
The SMART goal is a widely used methodology in business planning, allowing you to plan, delegate, and coordinate more effectively, as well as build trust—especially among investors and financial institutions that want to see how you measure success, how you plan to achieve it, and what the expected ROI time frame is. It is also commonly used in other areas, such as setting career or personal development goals.
When setting the goal, you might want to go through the following questions to make sure all the details were considered:
Check-List of SMART-Goal Questions
Specific: What? Where? How? Who? Such as: What is my goal? What do I want to achieve? Where is it going to happen? How am I going to achieve it? Who are the people/partners/stakeholders I am going to be engaged with?
Measurable: How much? How many? Such as number of items, pieces, amounts in €, $, or other currencies, sq. meters, kilometers, kilograms, % of increase or decline, and many others. Choosing the right metric for success is kind of an art , and I will share a few insights on it down below.
Attractive: How is that aligned with my values? Mission statement? Many times Achievable or Agreed is used instead of Attractive. I find the latter more useful, allowing to connect with values that drive motivation. Just choose the one you feel makes sense.
Realistic: How realistic is my goal? Is the time given enough for achieving it? Are the listed Metric or Specifics realistic to be accomplished within the given time?
Time: When? From when? By when?
Example of Setting a SMART Goal.
Case Study: Wind Power Energy
Disclaimer: The goal setting described in this article is a fictional template. Numbers are not based on any realistic data, Wind Power Energy or Argentina are simply cool romantic.
Let’s look at one example: the intention is to successfully enter new geographical markets and offer clean energy.
Version 1: The initial SMART goal could sound like this:
By June 2030, my company expands its global presence by entering two additional South American markets with favorable economic policies (e.g., taxation) and climate conditions for wind energy. This expansion is expected to result in a 300% increase in revenue by the end of the period.
The Specifics here are the chosen geography, the preferences in economic policies and climate. Conducting more research will allow us to select the exact locations — for example, replace “two markets” with Argentina, Chile, or even more specific regions. The details can go beyond location. For instance: How am I going to do it? Will I set up production there, or will I ship from my existing factory?
Now, how do I measure the success? In this example the Measurables (quantitive indicators) are 2 Countries and 300% revenue increase. But how do I know which indicators are true for my success? There are multiple variations on what kind of metrics to choose. It is important to be aware of that fact that the metrics for the sales or financial department will sound differently than for the HR or Corporate Sustainability departments. Though in the perfect world they are aligned with the strategic vision of the company.
June 2023 – is the Time (deadline) for asking: Have we made it or not?
The “A” stands for Attractiveness, aligning the goal with the company’s mission and values. Should the company consider partnerships with local manufacturers, allowing cost cuts on production? Should local resource extraction be considered, enabling the company not only to provide clean energy but also to create a supply chain aligned with a circularity mindset?
Therefore, you might want to revisit the goal setting and include more Specifics and Attractiveness.
Version 2: The SMART goal could sound like this:
Starting in June 2030, my company begins expanding into up to five South American markets by exploring methods allowing better transportation and improved modularity in assembly of wind turbines. The aim is to reduce transportation costs by approximately 35% compared to current metrics, while contributing to more effective and sustainable use of regional resources.
Now, with more Specifics provided, the next question arises: how Realistic is it? Research should be conducted to identify applicable locations, experts consulted to share their vision, and the favorability of policies should be verified by connecting with public institutions and assessing their openness to collaboration or potential client relationships. The deadline could be triggered and postponed, as more uncertainties arise with the expected innovations.
2. What is the environment for my goal?
When setting a goal, in addition to using the SMART Goal framework, I offer a few deeper questions to better understand the environment in which the goal is being pursued:
1) Is my goal or challenge unfolding in a predictable or unpredictable world?
2) Is this a dream goal driven by purpose and meaning—a big “Why”? Or is it an end goal with a clear target and measurable outcome?
3) Do I have a clear vision for this goal? If not, is it even possible to have one in the given environment?
4) Does this goal have an ‘End-Station’? In other words, am I playing a finite or an infinite game?
5) What type of environment am I operating in: simple, complicated, complex, or chaotic? And by the way, aren’t “complicated” and “complex” the same?
The information below offers ideas to ‘locate’ the challenge. It is based on the Cynefin (Ke-ne-vin) framework (Complexity Theory).
| Unpredictable Environment | Predictable Environment |
| 🌳 Complex: In this world, we have multiple stakeholders with no agreed vision and diverse values. Idea generation and multiple areas of expertise are applied for collaboration. Action: collaborate to innovate, experiment, and learn. | 🛠️ Complicated: In this world we have a clear vision and goal, are data driven, rely on past case studies, strong specialisation and expertise to gain confidence in our decision-making. Action: Coordinate to record, analyse, and make a decision. |
| 🌪️ Chaotic: Proactive steps are taken to stabilize the system — such as during a war or pandemic — and shift it toward either a complex or complicated environment allowing collaboration or coordination. Action: control to mitigate side effects. | 🗓️ Simple: This is a setting with the tasks to be easy, specific, repetitive,. If not automated yet, they can be boring and become a ritual toward simply doing. This environment invites practicing presence and appreciating simplicity. Categorise tasks, delegate, and act. |
Source: Working in Complexity (WiC), jointly offered by Climate-KIC Academy & Cultivating Leadership Development Coaching, 2020/21.
I have generated a few examples to give a better sense of them (this is purely how I would understand and differentiate them).
Complicated:
- Production and/or installation of a sophisticated equipment
- Car repair required by a professional, specializing in that area
- Proceeding with a complicated surgery by a doctor in a hospital
- Job seeking for roles where you have a strong expertise in.
Complex:
- Innovation of a system for ease of assembly of a sophisticated equipment
- Designing a concept car based on clean energy
- Modernizing hospital operations to reduce medical waste
- Pursuing a career change in an unknown industry
Case Study Analysis.
So, if we look back at the first version of the goal we set above, we can assume that it operates more or less in a predictable environment, because the success will largely depend on the expertise of engineers, project managers, financial managers and other operational managers. They will be responsible for coordinating and executing the plan—something they have (hopefully) done successfully in the past. While risks still exist, the SMART goal appears achievable within this setting, especially since it has a defined end point.
In contrast, the second version introduces innovation and experimentation, bringing with it a higher degree of unpredictability. If the company pursues initiatives it hasn’t undertaken before—such as local resource extraction or improved modularity in assembly—it enters a complex environment filled with many unknowns.
In this scenario, success cannot be measured solely by predefined outcomes. Instead, it is evaluated through lessons learned, insights gained, and experience accumulated—allowing for a deeper, more adaptive sense of progress.
Sticking only to measurables and a fixed timeline, and simply asking “Did I meet my goal in 2030?” would not be smart, as this alone does not fully reflect success or failure.
What many of us miss also is that not every measurable truly reflects goal success. The confusion often arises from expecting to measure a ‘Dream goal’ in a complex world. This doesn’t mean SMART goals shouldn’t be set in this environment — rather, they should be used differently. In a complicated world, SMART goals point to a fixed end station; in a complex world, they act more like a navigation system, helping us stay aware of our direction. In such an environment, the fear of failure around innovation and learning diminishes, since progress is not strictly tied to strict metrics.
3. So when is the SMART not smart?
What makes setting a SMART goal not smart is having the wrong expectations about it. The following examples I tried to illustrate through the lens of predictabile & unpredictabile environments:
3.1. When you create experiments in the predictable world…
a) Your goal is to design a landing page, business card, or something similar—something you’re experienced at. The goal is simple for you. However, your colleagues might treat it as a fun team-building activity full of brainstorming and co-creation. This can lead to misaligned (non-agreed) goals: you’re aiming for simplicity and results, while others focus on the process and authenticity. What seems like a simple, straightforward task to you can quickly become a chaotic project delivery.
In such cases, experiments and brainstorming in a simple world can be frustrating—especially when your vision is focused on getting things done on time. Therefore, when setting up experiments and co-creating in a predictable world, your SMART goal starts fading away.
b) Another example is when non-experts make decisions for experts. I spoke with three architects—from different companies—who all quit their jobs after successful careers spanning 5 to 10 years. They all said the similar thing: their instructions and guidelines are often ignored by construction companies. One of them added, “Why would people follow the instructions of doctors but neglect mine? I am an expert as well!”
In this case, the implementers neglected the expert’s vision, making some of their Specific metrics irrelevant. While you created and expected predictability through the given instructions, the partners adapted them according to their own visions.
So what these architects often struggled with was the inability to create or innovate something truly new. Frustration arises because construction companies tend to avoid ideas that haven’t been implemented before — aiming to minimize risks and costs, which is normal for the predictable environment. As a result, they often dismiss architects’ those decisions that are less about safety and more about creativity.
3.2. When you expect predictability from the complex world….
Now, imagine the opposite: the environment is complex, but goals expected like in the predictable world. The SDGs 2030 (Sustainable Development Goals) are great examples of the complex environment. Even if they are measured, time-restricted, and specified with 17 different goals and sub-goals, it is difficult to have a clear vision of what the world would look like when all are achieved by the UN members. The approach here is to learn from what has been done and to adjust for the future 2050 milestone.
Those who get stressed because targets aren’t met by the deadline are expecting the complex world to behave like a complicated one. But even if the targets are far from what was planned, it doesn’t mean the goals have failed (or will, since we still have five years).
In the settings of the complex world, SMARTs serve as a navigation system and not an end station. Success is not measured solely by predefined metrics. This can be very disappointing for those who prefer discipline and control. The best is to self-reflect and be aware of own limitations, such as the ‘agile is not my thing’.
To conclude, the true benefit of goal setting comes from using additional questions (as given in the second section) to better understand the specifics of the environment. It may represent a dream goal rather than a fixed end goal and it might be your navigation system rather than an end-station.
Thank you!