First and foremost, we listen to our customers. This might sound obvious but we frequently inherit failed projects where the previous contractors basically didn't listen and tried to impose solutions.
We know what technologies exist and how to apply them and at what cost but we are not experts in our customers' businesses. They know what they need, they know their domain. We co-construct together our solutions based on our respective expertise.
Most of the time, when our customers ask us to solve a problem, it is only the tip of the iceberg. With our experience and knowledge, we can help our customers to find the real pain points.
We systematically think about scaling our solutions and about reducing their costs. Basically we treat our customer's problems as if they were our own. The solutions we propose are the solutions we would apply ourselves.
We don't jump into big projects that take months or even years. We find the bottlenecks and use the Pareto principle:
The Pareto principle (also known as the 80/20 rule, the law of the vital few, or the principle of factor sparsity) states that, for many events, roughly 80% of the effects come from 20% of the causes.
We cut the problem into sub problems and always agree with our customers about a feasible schedule that reassure them (and us).
We know exactly what is possible or not with the new technologies. If we don't master some technologies that are better suited to solve our customers' problems, we do tell them so. Either we find the right partners with such knowledge or we redirect our customers to our competitors and tell them the pros and cons of working with them.
Some customers have their own preconceived ideas about solutions and/or technologies. If we have a good reason not to follow their directives, we inform them and try to convince them with rational arguments why we think so.
While we always keep ourselves up to date with the latest technologies (often inventing them ourselves!), we perfectly understand that our customers don't necessarily need them. Sometimes a rule of three is better than a neural network.
Because we also use Operations Research, we can propose solutions right away even if the data is scarce or not exploitable. If there is data, we'll use it but we can help our customers gather data the right way.
In the same vain, we adapt our solutions to our customers' infrastructures.
Solutions in Operation Research, Machine Learning and even more when both fields are combined are very effective but come with a certain level of complexity. Any solution needs to evolve and to be maintained. From the beginning, we discuss with our customers how this maintenance can/should be done whether done internally or by us.
When we accept a project, we don't accept failure as an option. We give it our 110%! Sometimes there is a risk associated to the project. We assess this risk with our customers and find ways to mitigate those risks.
While we always research the state of the art to solve a problem, we often reuse known and well tested solutions. Sometimes it might be worth to reinvent the wheel but not without a very good reason!
Our solution are very effective but often the employees that need to use such solutions don't see the big picture and are lost. This is normal. We give you two examples.
We know that good solutions can only be effective if people using them are convinced of their relevance.
Nowadays, the trend is to construct solutions that constantly improve themselves. We provide several such improvements mechanisms. The more our customers use our solutions, the better they become.