If your work is anything like ours, your team occasionally faces design challenges that are resistant to even your best efforts. That’s because the real challenging problems always require you to push yourself into an unexplored creative space. And that’s not easy.
To help us in these moments, our team frequently reflects on our previous work to identify successful strategies we’ve used in the past. With these ready at hand, we are never at a loss about how to move a project forward – no matter how complex and challenging it may seem.
Here are just three of our design strategies that you might find useful.
Strategy 1: Start with what’s simple to reduce costs
Ask: What is the simplest solution that would solve this problem? Then progressively evolve your idea by adding more complexity.
For example, imagine your organization wants to increase collaboration. On this first strategy, you shouldn’t start by designing a brand new office space, replete with windowed meeting rooms, foosball tables, and a feng shui foyer.
Instead, start by taking an afternoon to simply remove cubicle walls. This might achieve the intended effect at a fraction of the cost.
If that doesn’t work, next try reorganizing workstations within the new open concept work environment you’ve just created.
The idea is to keep adding complexity until you see the changes you want to bring about.
By starting with what’s simple you are creating a prototype which you can then incrementally improve until the problem goes away, rather than over-investing in something that won’t work. This is a great way to reduce costs in your problem solving process.
Strategy 2. Begin with the end in mind to avoid wasted effort
This is a well-known problem solving tactic within mathematics and physics. But it’s an equally good strategy for designing workplace solutions.
Just ask, “When our solution is in place, what will be different?”.
Decomposing a problem into its constituent parts reveals what’s really important and immediately makes it more tractable. While keeping the big picture in mind, you can then focus your efforts on these critical elements.
Imagine you want to reinvent your performance management program. The crucial question to ask is, “When this new program is in place, what about our culture will be different?”.
Answers might include, “Employee improvement will be a continuous process, not an annual event,” “People will cooperate rather than compete with one another,” and, “Managers will coach employees.”
These answers quickly isolate the most important factors in designing your solution – regular performance conversations, a cooperative mindset, and coaching support. You can then focus on these elements first, since they will deliver the biggest return on your efforts.
In general, by starting with the end in mind, you are able to surface complexities early on and use your problem solving energy more wisely.
Strategy 3. Reduce uncertainty to save time
At the start of a project, the information you need to design an effective solution falls into one of two categories:
- What you know
- What you don’t know
Strategy 3 says to quickly learn what you don’t know. When you do that, you’ll reduce uncertainty about the problem, which will streamline your design and accelerate the time it takes to get to a solution.
Data is king on this strategy.
For example, we recently helped a global client improve their knowledge management system. Early in the design process, we realized that there were too many possible solutions, and we lacked data that would help separate the wheat from the chaff.
Upon some reflection, we concluded that we needed to know more about employees’ informational needs. Knowing that required getting on the front lines with them and observing their work.
So our applied science research team reduced that uncertainty by job-shadowing a sample of employees.
Ironically, the data we collected from this activity pointed to a solution that both our client and our team initially favoured the least! This insight meant that our client was able to avoid wasting precious time having us explore a solution that was never going to work.
The upshot is that by reducing uncertainty early on, you are able to quickly decide (with a high degree of confidence) which solution to pursue and why. This can save you a lot of time.