Artificial Intelligence
Will GenAI bring us greater operational agility?
14 November, 2023 | Written by: Christopher Dabrowski and Pavlos Konstas
Categorized: Artificial Intelligence
Share this post:
It has been quite an exciting summer for tech in government, with the buzz around Generative AI rippling across Whitehall. 80% of all public and private sector organisations will have incorporated AI into their business processes during the next three years. GenAI raises some interesting questions about whether the public sector can effectively use it to meet stretching ambitions, and even bigger ones about whether departments have the ability to respond to this kind of transformation at pace.
A recent poll from the IBM Institute of Business Value (IBV) found that 60% of government leader respondents believe that the frequency of shock events is likely to increase in the future. About 70% of them also believe that these types of events are likely to increase in intensity and impact. GenAI is just one such shock event.
But are we ready? Does our hierarchical approach to programme governance and delivery enable us to adapt well enough and fast enough? Looking at the current situation in government departments, there are a few observations one can make:
- Clarity of purpose is often lost in overly complex requirements and expectations that further overcomplicate already complex tasks. This leads to multiple misaligned KPIs and conflicting priorities.
- Change seldom reflects a true interlock between strategy/policy, transformation, and actual operational improvement. Change needs to happen within the business, not in isolation or as a standalone function, but infused through the entire organisation.
- Portfolios are mostly assurance bodies that rarely “lead change” by helping sequence and prioritise releases to deliver against wider organisational goals. These layers can often lead to a proliferation of retrospective reporting rather than a culture of highly engaged, constant forward-looking analysis.
- Federated delivery often leads to less alignment between strategy, transformation, and operational benefits rather than greater effectiveness. Organisations cannot afford to have both federated delivery and federated processes. There needs to be a balance.
We believe that transformation leaders need to ask themselves four big questions to make effective decisions that both drive delivery and accommodate change:
Do I understand the system of work within my portfolio/programme/workstream? Leaders need to align governance, resources and behaviours to the nature of the work. An office move generally means a team operating in waterfall, while rolling out a user-facing digital service often means working in agile. There is a strong argument for hybrid governance. Understanding this means you can choose the right methods and use them to drive governance, behaviours and decision-making.
Do I understand which levers drive performance in my specific context? Leaders need to use a range of interventions across leadership style, governance, ways of working, org structure, tech strategy, talent, and measures setting.
Am I clear on what I am trying to change and why? The hurly-burly of delivery can often lead to a drift away from the original purpose of the work. Being clear on the specific change we are trying to make, how that will impact operational metrics and improve the experience of both employees and end-users is critical. Yes, most programme have multiple users, but this can’t get in the way of a simple narrative on purpose and outcome.
Am I prioritising my capacity in a way that delivers my target outcomes? In a resource constrained world, we need to think critically about our target outcomes and result metrics and constantly reassess the best use of resources to achieve them.
Change needs to be led by people who are passionate about what they deliver and have the insight, domain expertise and gravitas within their organisation to mobilise coalitions and enable change. This can mean policy, operational delivery or digital leaders in addition to Programme Directors (PDs) acting as Senior Responsible Owners (SROs) or Programme Directors.
Asking these questions, rooted in a clear understanding of each organisation’s system of work, is essential to delivering transformed services in a consistent manner. And indeed, embedding agility in how departments operate. It means rising above the false dichotomy between agile and waterfall to deliver effectively given the constraints of resource, time and political ambition.
Coming back to our original question, will GenAI bring us greater operational agility? It depends on how leaders embed operational agility in the enterprise through a clear focus on the system of work, nature of change and command of key change levers.
What do you think?
Learn more on CEO Decision making in the age of AI and Resilient Agility – IBM’s Seven Big Bets
Partner, Enterprise Strategy Consulting
Associate Partner, Enterprise Agility Leader UK & Ireland
Converting website traffic into happy customers with a smart virtual assistant
With a long track record of guiding companies across various sectors through digital transformation, IBM Business Partner WM Promus is now focusing AI innovation. Eileen O’Mahony, General Manager at WM Promus, explains how her company helped a UK-based commercial finance brokerage enhance customer experience, and develop new sales leads using IBM watsonx and IBM […]
Reducing the time taken to write regulatory submissions – Introducing our Accelerator
The Case for Generative AI in Regulatory Acceleration Generative AI and automation are now enabling digital transformation across biopharma, allowing radical reshaping and automation of core processes – and focusing human effort where it is required. Companies embracing this approach across the whole organisation are deriving significant competitive advantage and transforming the way work is […]
Impact on Data Governance with Generative AI – Part One
Many thanks to, Dr. Roushanak Rahmat, Hywel Evans, Joe Douglas, Dr. Nicole Mather and Russ Latham for their review feedback and contributions in this paper. Introduction As artificial intelligence (AI) and machine learning (ML) technologies continue to transform industries and revolutionise the way we live and work, the importance of effective Data Governance cannot be […]