Business leaders are operating in an environment of limited resources, limited time, and other business constraints. It’s a fact of everyday life for business leaders: you need to make tradeoffs for optimal resource allocation. Constraints make these business decisions more complicated. But that doesn’t mean that constraints are “bad,” or that you should see them as an obstacle to your success. Instead, business constraints are something that need to be faced head-on, examined, analyzed, and dealt with.
With the right strategic analytic approach, business constraints can actually be helpful to your business performance by giving you a framework to innovate. If business constraints are a “box” of limits on what you can do, they also present a kind of creative freedom within that box. When you know the defined limits of what you’re working with, you can start solving for constraints within that box. Constraints give you focus and motivation to find a way forward.
Let’s learn more about how business constraints affect your business performance – and how you can use them to boost your success.
Business Constraints: What They Are and How They Work
Business constraints are real-world rules, boundaries, and limitations that affect your business operations. These constraints can include material resources, budget limits, or product design specifications.
Business constraints are also used in predictive modeling, such as parameter constraints, structural constraints, and data constraints. Imposing constraints on a predictive model helps make sure that the model provides useful and interpretable results that are not too complex or overfitted to a certain data set.
Every business leader has to make informed business decisions based on the real-world constraints that they’re facing. You can do that with guesswork and hope your outcomes are successful. Or, you can leverage data analytics and factor the constraints into a predictive model to identify optimal decision paths with cost-benefit analysis that takes all your variables into account and achieves constraint satisfaction.
What Life Is Like With and Without Constraints
It might sound better to run a business or manage a project that has no constraints, where the sky’s the limit to pursue ideas and develop solutions. But recent research from the Harvard Business Review shows that business constraints can be useful for innovation.
When there are no constraints, people tend to follow the “path of least resistance” in solving problems. Constraints can provide useful boundaries that help people focus, synthesize information, and develop new solutions.
For example, the Harvard Business Review article explains how GE Healthcare created a revolutionary MAC 400 Electrocardiograph (ECG) machine, by imposing strict constraints of time (18 months), budget ($500,000) and product specifications (the ECG should cost $1 per scan and should be battery-powered and portable for rural locations).
Another example is how Jony Ive, former Design Chief at Apple, created a constraint on the design of the iPhone 4. He required the design team to use a specific type of scratch-resistant aluminosilicate glass; all other design and production decisions had to work around this limitation.
In the same way that children need limits to help them grow, business teams also need guidelines to help them innovate – with creative focus and cost-effective discipline. Business constraints can help your team focus their thinking, manage costs, and ship projects on-time and on-budget.
How to Leverage Business Constraints
Constraints are not your enemy; they can be a helpful guide that gives your team a clearer framework to focus and succeed. Constraints can be leveraged to ensure that business leaders have data-driven information in order to make business decisions.
By understanding constraints, analysts can create better predictive models, and provide analytics to business leaders, who can then make a truly informed decision based on logical conditions.
For an example of how this works in a business analytics solution: Analytic Solver® makes it easy for users to add real-world constraints to their optimization or stochastic optimization model. The constraints are bound on the variable that reflects reality. They express real-world limits. A constraint is always going to have a formula in it, such as “less than” (<) or “equal to” (=).
Building real business constraints into your modeling and optimization projects can help you get better visibility into the true cost-benefit analysis of your business decisions. It can also help you build better relationships with business stakeholders to get buy-in for high-level decisions.
Real-World Example of Solving for Business Constraints: Canadian Football League
The Canadian Football League (CFL) used Analytic Solver® to optimize their game schedule, which included nine teams playing a total of 81 games across a 20-week season. Multiple objectives vied for priority in building the schedule:
- Revenue: the most lucrative time slots must be assigned to the largest revenue-generating teams
- TV Ratings: optimize TV ratings
- Rest Days: all teams must be given an equal number of days off before their next game
The League ultimately decided to optimize the schedule for Rest Days, so the teams would be relatively equally rested, and would create a more competitive, exciting product on the field. In order to optimize the schedule for this strategic goal, the CFL used several business constraints within Analytic Solver®, including:
- Game times must be viable for the most viewers in all four Canadian time zones
- Since all CFL games are broadcast on the same Canadian TV network, overlapping double-headers were not allowed
- Each team must have at least five days of rest between games (except for a few specific instances)
- All traditional rivalry games must be played on Labor Day
By working within these known business constraints, the CFL was able to create a season schedule that was optimized for its most important strategic goal: competitive, fun-to-watch football between well-rested teams. But the CFL didn’t stop there. They took the “rough draft” schedule back to negotiations with teams and TV broadcast partners, listened to their feedback, and made adjustments benefiting all parties.
The optimization model, and subsequent schedule, required flexibility. Games between high-profile rivalries were moved to Saturdays in order to optimize TV ratings. Trevor Hardy of the CFL, optimization modeler, believes that scheduling is “25% science and 75% art.” Using Analytic Solver® and his knowledge of the model components, he adjusted the model to be, perhaps, less mathematically perfect, but more perfect for the business needs of the CFL and its stakeholders.
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