At the early stages of a project we following a design thinking process to uncover requirements in a creative efficient way. We use design thinking tools such as:
Any project, whether a report, a data collection and analysis task, or software, will touch some or all of our teams: Maths, Software development, Design and UX, Quality assurance, Product Management, Food & Nutrition. Our team functions are described below.
Our maths team’s experience spans many different domains and technologies. To understand their work we recommend you visit the analytics project process page. The models they produce are wrapped in software by our development team.
Our software team ensure that the a project is correctly broken down into into managable work packages. They work also with the client to decide how agile a project must be, that is, how much we can be sure of requirements up front, and how much we need to build first and then validate. Projects where the end-users’ requirements are well defined at the beginning run quicker in most cases.
Our inhouse design team practice user centered design. We engage real users in our research. We prototype versions of the product to validate assumptions. This process is repeated until we have a final prototype before development starts.
All new models and software pass through a quality assurance cycle. We practice Test Driven Development. This form of development means that the quality of your product is better and upkeep is less expensive.
We dedicate a Product Manager to ensure the requirements accurately reflect the needs of the customer. The product manager will ultimately take responsibility for the delivery of a successful product.
Our software and modelling solutions benefit from our Expert Models platform.
We can quickly build out user interfaces appropriate to the data science domain, including file management systems, editors and wizards.
Our systems are built on a cloud based architecture that scales up in real time. As your usage become more intense machines activate to meet that need. For resource intensive projects this means we can control costs by reducing inefficiencies.
Our platform is cloud based. Cloud based systems are far easier to protect than on premise. Some of the reasons are:
Regarding data, we can protect your data by various means such as granular view permission and obfuscation.
We think a lot about project metrics to help quantify the benefits to our clients and to help use improve our services. We aim to keep feedback loops as short as possible to optimise learning reinforcement. Some of the metrics we include are: