In our recent blogs and in our video podcast series, The Undeniable Truth About 6 Skills Statistical Programming Heads Have that No One Is Telling You, we have already covered the skills of Strategic Mindset, Collaboration and Engagement. Another fundamental skill which every statistical programmer and function manager needs is being able to drive results.
Statistical programming functions produce a lot of output. Regardless of whether the output is tables, figures, listings, SDTM or ADaM datasets, ad hoc analysis or responses to regulatory agencies, they all need to be delivered according to tight timelines and in the highest quality.
So, how exactly do heads of statistical programming functions manage the holy trinity of quality, time and cost in their global organisations?
Del Jones (GSK) and Mike Carniello (Astellas) discuss these challenges in our latest podcast in the PHUSE series. Del and Mike share their great experiences of leading global statistical programming teams spread across multiple sites.
Watch Drive Results here: https://www.youtube.com/watch?v=66GJmf-jeUI
Statistical programming functions are measured according to the output they deliver. Mike shares a great analogy where he compares the roles of statisticians and statistical programmers with those of architects and builders. It is usually architects who design glamorous buildings; yet, none of these fancy houses could be built if the builders did not fully understand the vision of the architect. Statistical programmers build their output according to statisticians’ plans. Statistical programmers therefore need to understand which things work and how long tasks take.
Taking the house building analogy further, there are lots of different parts which need to be coordinated and delivered to ensure that the end product meets expectations. Bricklayers build the foundations; plumbers lay the pipes; electricians place the cables, and so on. Similarly, leaders of statistical programming organisations need to ensure that all deliveries are developed and validated and that they match one another. As a global head, it is of utmost importance to understand how deliverables are produced. Reasonably defined metrics help to guide teams through this process. Metrics also help programming heads to identify tasks which could create challenges in the overall delivery course.
Managing the change in these complex dependencies and with diverse teams is a challenging task. These days, change is a constant element in statistical programming deliveries. Regardless of technology or regulatory requirement changes, modifications need to be carefully introduced. Addressing the “why” helps tremendously in introducing changes to delivery processes and in keeping on track to complete everything within tight timelines. When you watch Del and Mike discussing this key skill, you will learn about the challenges in measuring performance and deliveries in diverse global teams.
If you want to dive deeper into engagement, there are several great resources available: William Craig tackles Leadership practices that drive results in his Forbes article. Jurgen Appelo, also in Forbes, explores how a scoreboard index might help to measure performance. While these articles are useful resources to learn about general performance measures and results-driven behaviours, data science teams today often need to be flexible and to be able to handle ambiguity. In his Data Science Project Management blog, Nick Hotz describes 10 Data Science Project Metrics which can help leaders to manage through the unknown.
Our PHUSE Education team is continually pooling educational material to help our community to explore these vital job skills further.
