in this post I wanted to talk about some of the broader technical capability & understanding & concepts Delivery Managers in 2023 will need to consider, when they take on their respective projects. From cloud management & orchestration to sustainability, the days of pushing a Gantt chart around have gone. Read below my thoughts on what DM’s need to know about in 2023.
What skills will a DM need in 2023?
It’s not a surprise to many I’m sure, that I’m thoroughly immersed in everything tech related. From going to events, to speaking to people on the Podcast (https://podtail.com/en/podcast/the-delivery-manager-daily/ ) & the work I’m fortunate enough to do as a consultant. I get to speak to businesses, leaders & engineering teams from around the world understanding their tech challenges in digital & tech transformation. I get exposed to it all & that gives me some perspective to write this post.
I also take care of delivery people themselves. As part of that pastoral service, I develop Learning & Development pathways in part, based on what is going on in the industry. The types of challenges clients want to or need to solve in 2023, will heavily dictate the types of work consultancy firms take on & therefore the types of projects Delivery Managers will need to manage. This is all linked & if you’re in any way responsible for managing your capability or service line, this post is for you.
I wanted to outline the skills then, the concepts & notions I think Delivery Managers need in 2023.
Value Stream Management (VSM)
Companies & clients are more mature now in their thinking around both ‘value’ & the notion of MVP (https://www.mariosblog.co.uk/all-about-lean/ ). Subsequently this has trickled down into their operational processes. Consultants need to be aware of the Value Stream(s) within a business, but also how to identify them & how to map them visually & in a coherent way for teams to assess, analyse & improve. Delivery Managers need to be fluent in this often BA’esque activity & understand how to identify value & also identify waste & inefficiency.
Further reading: How to map value streams in 10 easy steps
Modern software delivery techniques that implement AI
Along with the hugely popular topic of ‘AI’ at the minute generally, Delivery Managers need to understand the different types of AI & how that’s being used in the SDLC. From Chat GPT baked into Microsoft CoPilot (https://www.theverge.com/2023/3/22/23651456/github-copilot-x-gpt-4-code-chat-voice-support ) to innovations in AIOps, Delivery Managers will really need to understand both the cultural & technical elements of how AI is changing the way software is built.
Further reading: Implementing AIOps & the AIOps state of the nation
Compliance & Assurance
Shadow IT is back with a vengeance. So is massively un-orchestrated cloud sprawl. Engineering teams deploying solutions across multiple cloud platforms, no documentation, little testing. A secure & compliant SDLC is something companies need to be on top of, in the light of growing data costs & breaches. Delivery Managers need to understand & value the importance of governance & assurance as-you-go & NOT at the end of the project if at all.
Further reading: Deloitte Whitepaper – Assurance in the cloud
Everything as a service (XaaS)
Clients & organisations will continue to off-load their workloads to third party applications & AI driven services, rather than upskilling employee’s or hiring. I see this with huge take up of Microsofts Power Platform & the very apparent Microsoft Dynamics engineer skills shortage. Delivery Manages should understand what these platforms are, how IaaS & PaaS works, how they are built & subsequently how they are deployed. I often get my Delivery Managers to have fundamental cloud skills certification across all three major platforms.
Further reading: TechTarget’s guide to XaaS
Clients & organisations have more responsibility than ever before to demonstrate sustainability across their people, process & technology. Delivery Managers need to be mindful of their delivery approach & how to be carbon efficient along with being technically aware of the various sustainability tools offered by cloud vendors to ensure efficient time-optimised workloads. For more discussion on Sustainability, why not check out my podcast, Carbon Agile here & my post on Medium here
Data and more accurately big data is a massive challenge for clients. They want to hyper personalise leveraging Ai & ML. They have data sprawl everywhere & want it in one place to apply data science to it to create actionable insights. Delivery Managers need to understand the lifecycle of data, how its ingested into Data lakes, ranked & sorted & cleansed. Its also worth a mention on the cost of storing this data inc cloud compute workload costs, how that impacts sustainability & pipeline process in both AWS and Azure.
Further reading: https://blog.hubspot.com/website/big-data-challenges
What are the pro’s & con’s of specialising
In consultancy there’s a battle between the purists who’ve committed to their craft for decades, obtaining experience & certification in relation to their field. They don’t respond too well to being told they need to be more ‘t-shaped’ Alas, in consultancy the drive to be a swiss army knife & the value that brings a consultancy firm versus those devoted to one ‘thing’ or discipline.
I recently did work with a group of folk who managed groups of folk & the notion of t-shaped versus specialism was something talked about. If you’re a consultant, you have to accept being genuinely t-shaped (not to be confused with consultant bullshitter) is a valuable proposition. I enjoyed reading McKinseys research on the subject you can read about here