Guest post by Jonathan Patterson, DWF Ventures’ managing director and head of development
DWF has embarked on a 30-month Knowledge Transfer Partnership (KTP) with the University of Manchester, with the ultimate aim of transforming how the business uses data and harnessing that data to provide greater value to clients through efficiencies and analytics. This is the second in a series of quarterly blogs on how the KTP is developing. Read the first here.
One of the best pieces of advice we got before we embarked on the KTP was to invest time in choosing the right expert to lead the project. Not only do you need to find someone with the right technical expertise, they also need to be able to make the shift from academia to a business environment.
With that key point in mind, we thought it was a good opportunity to introduce Dr Mayowa Ayodele, the data expert that is leading the DWF KTP.
Mayowa is a data process and applications scientist with a PhD in computational intelligence, which focused on applying evolutionary algorithms for solving optimisation problems.
Mayowa’s interest is in real-world applications of evolutionary and machine learning algorithms, so we were delighted when she agreed to up sticks and move from Aberdeen to Manchester to join the KTP team.
Having been working at DWF now for almost six months, I asked a few questions about how her experience so far differs from her time in academia.
JP: How does data differ on a project like the KTP when compared to previous academic projects you have worked on?
MA: Usually when you work on more academic projects, the data tends to be perfect and easily accessible. One of the challenges and differences on an industry project like the KTP is it tends to be the opposite.
Data is imperfect in many ways, with missing or incorrect data and also more complex data structures make data less accessible. That means there is often the need to make calculated assumptions about missing data.
JP: Do you need to apply a different focus or approach when working on a KTP?
MA: The focus when working in academia is often on improving state-of-the-art result and showcasing the findings in highly-regarded conferences or journals. Similarly, in terms of approach, knowledge of practical application and business-specific knowledge is often not of particular importance.
On a project like the KTP at DWF, the focus is on providing a quick and robust solution with results that are easily accessible and useful for day-to-day business, which requires a high degree of business and industry understanding.
JP: Are there any other major differences between working on this KTP project compared to other academic projects you have worked on?
MA: The biggest difference, beyond the pace of the project and the need for industry and business knowledge, is probably the range of tools and past documentation that is available.
When working in a university, there are a wide range of programming tools available and detailed documentation relating to previous work done and data descriptions. When working inside a corporate business there tends to be less software to work with, as there will be preferred technologies for specific functions, and detailed documentation about past approaches is harder to find and interpret.
We listened to the advice and invested the time to work with the team at the University of Manchester to find and recruit the right lead for the project. Six months in and with Mayowa on board and adjusting well to the switch to industry, that effort is really paying dividends.