There’s much buzz around agile these days, and with good reason. Organisations that adopt agile ways of working tend to see increases in time to market, fewer product defects, increased productivity and improved employee engagement.
In my experience, one of the inhibitors of agile adoption is that it is perceived as complex and inaccessible by non-technical leaders – especially for those in a non-software development environment. Agile practitioners sometimes tend to throw around terms like scrum, retrospectives, tribes and demos. The list of agile technical jargon is immense.
A few months ago, I found myself presenting to about 50 leaders over Zoom. They had asked me to attend their monthly leadership meeting to deliver a presentation on Agile and why so many organisations were adopting it outside of technical functions. I started strong, then found myself unconsciously diving into the jargon of agile. I could virtually see their eyes glaze over. I had missed the mark – it wasn’t an excellent presentation.
The trouble with being a practitioner is that you often forget that not everyone has your vocabulary. When you’re in the trenches, it’s hard to see the bigger picture and realise that while agile may be a great thing for teams, nothing will change if leaders can’t understand it.
I licked my wounds and went back to the drawing board. It was time to find some new terminology and come up with an approach that spoke their language. I sat in a conference room with my team. I asked, “How do you describe the benefits of agile – without mentioning any agile terminology?”. Like typical consultants, much coffee and mentos were then consumed. One of the team then said, “A better question is how do we make this approachable and easy for leaders to understand – getting to the real underlying benefits?”. After about an hour of brainstorming, we came up with what we believe are the six “superpowers” of agile – linking them to the behaviours and practices that teams need to implement.
A few weeks later, I was back in front of that same client. In preparation for their transition to a scaled agile operating model, I was helping to deliver a town hall presentation. This time I could tell we had hit the mark. They were engaged and started to connect the dots on why agile ways of working make a difference to teams, organisations, and customers.
This blog post will cover some of the main benefits that make agile so great – without using technical jargon or going into the gory details of agile operating models. If you are an experienced agile practitioner, then this article is not for you. If you are a leader interested in exploring and understanding the underlying benefits of agile, then read on.
Predicable value delivery
One of the significant advantages of agile is predictable delivery. Traditional projects deliver value upon completion. There are many challenges with this approach. Agile is different because it promotes the concept of incremental delivery of value. This means that businesses can predict when they will receive value. Hence, the company and its stakeholders have a clear idea of what to expect. It does this via the concept of “sprints”. A sprint is a short period (usually between 2-4 weeks) where teams work on small work packages to deliver value and demonstrate progress.
Reduced organisational risk
When a team or organisation begins a project, it is almost impossible to know everything required at the start. In any project, there is a degree of uncertainty – and this uncertainty leads to risk. The challenge with traditional approaches to project delivery is that they rely on a “stage-gate” approach. Stage gates fix requirements and designs too early, making adjustments too late and costly as new facts emerge. This approach delays learning.
By contrast, agile reduces risk by embracing the uncertainty inherent in any project. It does this by rolling with changes and making adjustments as they emerge, leading to a more flexible organisation that can quickly adapt when new information becomes available. The iterative approach built into agile (by sprints) facilitates learning. It allows for continuous, cost-effective adjustments towards an optimal solution. This means that as new knowledge emerges, you can correct your course every 2-4 weeks – moving closer towards the optimal solution.
Empowering your employees
One of the core agile principles agile is that everyone on the team, from the top down, is treated as an expert. When team members are empowered and given responsibility for their work, they become more engaged in what they do because it’s no longer just a job. Instead, they feel they have more input into what work is completed day-to-day. Agile also moves critical decisions closer to the customer, empowering knowledge workers who do the actual work to plan what is important and deliver work. Ultimately this leads to increased employee and customer satisfaction.
Increased transparency
Agile makes it easier for teams and organisations as a whole to be more transparent. Increased transparency means that not only do teams have access to information about what is happening – but rather anyone can see how work is progressing. This transparency helps foster accountability and increases trust in the team, which makes for better collaboration.
Teams use many techniques and tools to drive transparency, from daily stand-ups to visualising work through Kanban boards. A daily stand-up is a short, daily meeting where team members discuss what they have done and what work is left to do – and most importantly, what is currently blocking them.
Agile is also well known for the visualisation of work via Kanban boards. A Kanban board is a visual representation of the work happening in a team. You can see what tasks are waiting or being completed. This gives everyone on the team visibility into how much work needs to be done and by which person.
Continuous improvement
The marketplace continues to be demanding – with new startups disrupting established players and increasing customer demands. To address this, organisations are constantly seeking new ways and best practices to improve. Part of the reason I love agile is that continuous improvement is baked right into the process. Continuous improvement is achieved in an agile team through the use of retrospectives. At the end of every sprint, teams reflect on what went well and where they can improve. Through this process, any team member (including managers) can offer suggestions on how work can be done more efficiently or productively to achieve better results next sprint. This “inspect & adapt” approach means that teams can learn from their mistakes and progress in a more sustainable way.
Increased alignment between teams
I have seen individual teams trying their best; however, the overall organisation is not aligned to deliver effectively. When implemented at scale, Agile can help align teams through techniques such as Program Increment (PI) planning. PI planning is about aligning with the agile team’s shared goal of delivering value. This means that there is agreement on what work is valuable in an agile organisation and how it should be delivered instead of having independent projects with no alignment (which can often lead to duplication of effort).
Start Experimenting
Agile is an emerging trend in business, and for a good reason. It’s been successful with global companies such as Walmart and GE. Still, many smaller organisations have also found agile ways of working beneficial. Some benefits include increasing value delivery predictability while reducing organisational risk and empowering teams by making them more aligned. It might be time for you to start experimenting with a few essential practices that can help make agile work well within your own company culture. My recommendation would be to begin with inspecting and adapting your work every two weeks. This drives immediate benefit by shortening the learning cycles inside your organisation.
If you haven’t been keeping up with current events, the next wave of digital disruption is upon us in the form of artificial intelligence (AI). For experienced leaders who’ve already weathered the disruptive impacts of Web 2.0, e-commerce and mobile technology, this may feel like yet another industry trend we need to come to terms with. But the truth is, artificial intelligence is a seismic shift that will completely transform how we both work and live.
From healthcare to transportation, AI will empower us to make more informed decisions at an unprecedented scale. If you’d asked us two years ago which sectors wouldn’t be severely impacted by AI, we would’ve mentioned STEM, the creative arts and empathy-based healthcare. Yet, in the past six months, we’ve seen all three experience the powerful effects of AI. On the surface, AI promises greater productivity, streamlined processes and limitless innovation. But this promise comes with caveats, as concerns emerge about potential job displacement, compelling organisations to adapt their structures and strategies. This article delves into the layers of AI’s impact in the workplace, exploring its influence on knowledge workers, organisational design and the pivotal role of the C-suite.
The AI-Driven Shift: A Complicated Transition
While AI’s transformative potential is undeniable, it brings with it many complexities that greatly impact the workforce. On the one hand, AI presents an enticing prospect of automation, alleviating the burden of mundane tasks and enabling employees to concentrate on high-value, strategic work. On the other hand, these advancements also give rise to real concerns about job displacement and the widening skills gap as the demand for AI expertise skyrockets. And the question of whether the number of new jobs AI creates will surpass those lost remains to be seen.
Beyond the individual level, organisations are grappling with the AI revolution, often finding themselves ill-prepared to navigate this transition. A lack of readiness, caused by either underestimating the reach of AI or struggling to keep pace with its rapid evolution, means a strategic re-evaluation among those in leadership positions is needed. We saw this denial during the previous wave of digital disruption, resulting in unprepared incumbent players displaced by new, more agile organisations that embraced or embodied the emerging technology.
Adding to the intricacies of this transition, governance, regulation and ethics present further challenges. As AI continues to permeate business operations, concerns about privacy, data security and ethical use of AI have taken centre stage, and regulators are scrambling to keep up. Many governments around the world are still struggling to grasp the very concept of TikTok, let alone comprehend the complexities of the impact of AI on the workplace and society. On the flipside, though, corporations find themselves in a unique position to self-govern, developing robust ethical frameworks that will guide their AI implementations now and into the future. C-suite executives, then, have an extraordinary opportunity to drive AI strategy and ensure it aligns with emerging regulations and ethical standards.
Navigating the Impact of AI: The Burning Question
Amidst these formidable challenges, a pivotal question arises: “How can C-suite executives effectively assess the impact of AI on the workforce?” Addressing this complex puzzle calls for more than a straightforward approach; it needs a comprehensive strategy that brings together the technological finesse of AI with the intricate dynamics of the human workforce.
Scenario Planning: Anticipating the Unknown
In our experience collaborating with clients, we’ve come across a diverse range of perspectives about the impact of AI on the workforce. While some perceive AI as a threat to their businesses, others recognise it as an incredible opportunity. We firmly believe that predicting the future is an impossible task, and it’s also unnecessary. The strategic tool of scenario planning is a much better way to navigate the uncertain terrain of AI transformation. By envisioning various outcomes and preparing suitable responses, organisations can address potential vulnerabilities and seize opportunities, whether by embracing automation or adopting AI-driven business models.
Typically, we develop three to five scenarios for each client, outlining the conditions needed for each to occur. Then we comprehensively assess the positive and negative impacts of each scenario on the business. In formulating responses, we often discover a common subset of actions applicable across all scenarios. The beauty of this approach is that it doesn’t require the ability to predict the future. In fact, these ‘no regret’ actions foster consensus within the executive team, as they establish strategic flexibility regardless of the scenario that ultimately unfolds.
Redesigning the Organisation for AI
In recent years, we’ve witnessed the convergence of strategy and organisation design to the point where they’re now almost indistinguishable. This has also corresponded with an excessive emphasis on talent. While talent is undoubtedly crucial, we firmly believe in the adage that “even a flawed system can outperform the most skilled individual”. As a result, we consider organisational design to be essential for all leaders striving to align their organisations with their strategic objectives. By investing in organisational design, they can create work environments that not only promote the growth and success of their talent but also reduce obstacles along the way, decreasing frustration.
When considering the impact of AI on an organisation, it’s crucial to acknowledge the necessary adjustments to its design. As AI will influence various aspects of organisation design, including ways of working, incentives, talent management and structure, integrating it into daily operations and strategies requires a comprehensive reassessment of capabilities, team dynamics, collaboration and decision-making processes.
To drive performance, leaders must identify any necessary roles and skills and determine the most suitable organisational model for managing operations integrated with AI. It’s also important to consider critical questions: How will decision-making authority be distributed among teams? What roles are required for data collection, analytics and operational execution? How can potential conflicts over resources, data ownership, skills and capabilities be avoided or resolved?
Unveiling these answers will shed light on the distinct challenges and opportunities that AI presents for each organisation. In reality, reshaping an organisation for AI is not a one-time endeavour; it requires an ongoing process of adaptation and evolution. Our approach has always encouraged leaders to treat organisation design like product design – managing ‘release cycles’ of iterative change rather than opting for a drastic overhaul. As AI technologies advance and mature, organisations must continuously adjust and refine their structures, processes and cultures. It’s undeniably a formidable task, but one that can yield substantial rewards for enhanced efficiency, innovation and competitiveness.
The Emergence of the AI Vanguard: Chief AI Officer and Chief Data Officer
As organisations grapple with the complexities of integrating AI, there’s a growing demand for specialised roles to address these challenges. The rise of Chief Data Officers (CDO) and Chief AI Officers (CAIO) within the C-suite reflects this need. The CAIO acts as a strategic compass, ensuring AI aligns with organisational objectives and overseeing implementation across functions. In contrast, the CDO manages data as a strategic asset, ensuring quality, compliance and accessibility for AI initiatives. Together, they lead the charge in navigating the transformation, and driving AI development and deployment.
The specific roles of these executives, however, vary based on company size, maturity level and strategic objectives. Both positions require a deep understanding of data science and AI technologies. Their emergence is driven by the vital role data plays in this transformative process. Data, often called the ‘new oil’, undeniably fuels AI. To be truly prepared, it’s essential that an organisation handles data intelligently. This involves understanding data origin, implementing effective cleaning and storage procedures, and employing efficient analysis methods. Developing robust data management and analytics capabilities is absolutely crucial when preparing for the advent of AI. In an era where many organisations can access sophisticated AI models, proprietary data sets have become a critical competitive differentiator and they are vitally important in this landscape.
In many respects, the positions of CDO and CAIO represent a convergence of traditional Clevel roles. They combine knowledge usually held by executives from IT, operations, analytics and finance. By creating these specialised positions within their executive teams, organisations can reap the rewards of AI while managing potential risks. This also allows companies to drive innovation and gain a competitive edge in the rapidly changing technological landscape.
The advent of the Chief AI Officer (CAIO) and Chief Data Officer (CDO) roles significantly impacts the role of the traditional Chief Information Officer (CIO). While the CIO has historically managed data and technology, the introduction of CAIO and CDO roles brings a more nuanced division of responsibilities. We expect the CIO will continue to oversee the technological infrastructure of the organisation, ensuring its strategic alignment with business goals. Meanwhile, the CAIO will focus on embedding AI technologies into business operations and the CDO will primarily manage data governance and strategy. Together, the CIO, CDO and CAIO form a triumvirate working in unison towards a common goal: leveraging data and AI to drive innovation, efficiency, and strategic advantage. This collaboration requires clearly defined roles and open communication channels to ensure seamless operational and strategic integration.
Charting the Future: Embracing AI Transformation in the C-Suite
The potential of AI in the business world is significant, but its realisation ultimately depends on the C-suite. As the decision-making core of any organisation, the C-suite has the power to drive AI adoption and integration. As a C-suite executive, you’re responsible for developing and executing AI strategy, aligning AI applications with business objectives, and cultivating an AI-ready workforce. These crucial components require the executive team’s vision, commitment and leadership. It’s your role to champion the cause, overcome resistance and propel the organisation into the AI age.
But for AI transformation to truly succeed, it requires more than just technological upgrades and talent acquisition. A fundamental redesign of an organisation is needed – one that remodels its structure and processes, morphing it into an environment that supports AI. Shaping the organisation’s design is a powerful tool for the C-suite. By ensuring that the design aligns with strategic goals, leaders can encourage a culture of innovation and agility – principles essential for navigating the dynamic AI landscape of the future. So, while the road to AI maturity may have its challenges, the rewards it promises undeniably make the journey worthwhile. The future is here… and it’s time for the C-suite to take action!
Humanly Agile is business design practice that helps senior executives bridge the gap between strategy design and execution. We create organisation designs that enhance agility, and human-centred change programs that accelerate transformation.
Jamie Pride is the Managing Partner of Humanly Agile and a recognised authority on organisation design. He has worked with many Fortune 500 companies to help them develop strategies, structures and cultures which are ready for the AI revolution. With over 25 years’ experience in strategy design, culture change and leadership development, Jamie helps organisations succeed in the era of disruptive technology.
Peter Ryan is an Executive Advisor with Humanly Agile and has over 30 years of Big 4 experience in technology advisory, implementation and managed services delivery in Australia, Asia, USA and UK. His work has focused on defining technology strategy, designing pragmatic operating models and implementing complex advanced technology enabled solutions across multiple industries.
