Successfully Implementing Commercial Mathematics

We have grown Biarri based on successfully bringing the power of mathematics to bear on business. We try hard to make operations research easier for business to digest.  Over the last few years there are a few things we have learned that are worth pointing out.

1. Target businesses that need analytical support and know they need it. Many businesses now have lots of data but that they lack the analytical ability to utilise that data. The businesses we target understand that smart decisions are based on ‘results gleaned from algorithmic insight and executed with the confidence that comes from really doing the math’. ‘Analytics’ is now part of the business improvement conversation however you need to target businesses that have complex problems that are solvable and need solving. Additionally, we have always had better success when the problem has a clear owner who will benefit directly from solving the problem.

2. Differentiate your offering. ‘Optimisation’ and now ‘Analytics’ are overused terms. As applied mathematicians we can certainly bring some real science to the table. But this is not enough. What has emerged as very important is our ability to make the mathematics digestible. We have tried hard to deliver ‘Accessible Optimisation’. We believe optimisation is only powerful if it is:

• Easy to apply to real world operations
• Easy to understand (intuitive)
• Easy to access (usable)
• Affordable with minimum capital spend
• Fast and reliable

3. Focus on implementation practicalities. You need to keep your eye on the basics of project management. Some of the key issues for us have been:

• Work hard to keep the scope tight by focusing on the 20% of features that deliver 80% of the value.
• Use simple frameworks that everyone can understand. All our custom models and tools use a simple linear workflow/logic around a smart engine.
• Stay close to your customer and practice the art of no surprises.
• Excel is useful for modelling. It is available on every desk top, flexible, familiar, easy to use and accepted by non-technical managers.
• Develop and implement prototype models quickly and have a simple way of upgrading them when needed.  For example, we always keep our prototype engines separate to the front-end so we can easily port them to different solution frameworks.