Galvanising Change in Corporates: The Transformation Lifecycle

Many times over my career so far, I’ve opted to work in roles ‘on the edge’, often between established business units or sectors. Serving as a bridge or interface between them. Collaborating and sharing ideas from one context into others. And/or building new functions to galvanise change. Through experience, I’ve honed skills in identifying what inherent assumptions are being made by different parties and where interaction has broken down. In fact, silos in businesses originally develop for good reasons: the given area needs to become more specialised to extract greater value and efficiency, putting in place more procedures, governance and structure to do so. Over time though, it ringfences itself too much, atrophying in place and unable to adapt to changes around it... 

In this article, I explore how established organisations can change successfully, and the stages a new ‘initiative’ or function goes through as it becomes a greater part of how the business operates. Driving adoption of new technologies or approaches across a business (and/or industry) are examples: too early and the sparkle could fizzle out, too late and you’re left far behind. Becoming data-driven or digital-first, say. Another is product development, introducing new solutions (perhaps backed by new organisational capabilities built or bought) to lead the business into the future. 

Successful collaboration requires that we know enough about each of the disparate worlds to build trust with all of them, encouraging them to look up and outwards in pursuit of new opportunities, to make decisions, and to take sustainable action. Helpful skills to galvanise change include: an ability to connect the dots plus technical depth in one or more areas for credibility, communication, relationship building to cooperate across functions, and critical thinking (especially matching a possible solution with a business problem). At a team-level, you want a multi-skilled group, experts from different domains working together with innovation drivers familiar with design thinking and agile methods. 

A significant part of change in a business is about bringing the people along: evangelising a new direction, shifting mindsets, promoting adoption of the new approach/product/service/technology, hosting training & demos… And, these days, a meaningful proportion of my work involves these ‘change management’, ‘transformation’ and modernisation elements. Many people naturally have anxiety about how changes might affect their own careers, and the effort involved in upskilling themselves. I very much believe human intelligence will continue to be needed (in addition to the automation and speed that artificial intelligence can bring) in order to ask questions, identify problems, think of possible answers – perhaps some not encountered before – and create solutions. The visibility of an ‘innovation’ team, and its ongoing business achievements, is crucial to winning hearts and minds. 

The affected people should be part of the process of proposing new ideas – great ones can come from enhancing existing processes as well as exploring emerging technologies and experimenting. And, it’s not really surprising too that an innovation process shares strong similarities with a product development lifecycle: aspects such as concept, feasibility, exploration, experiment, design, pilot, build, pricing, signoff, launch, ongoing management… Many processes include go / no-go gates too where ideas are shelved to focus resources on more promising ones. 

I’ve seen these thoughts play out in different contexts, such as pricing & product development, financial reporting, investment management, and data science & analytics functions. It’s true that change may be prompted by different drivers (regulations, competitors, technology and more…), however, the organisation needs to evolve new ways of working, perhaps new departments or operating models, to respond. Read more to follow along as I unpack how the functions evolve over time / the different phases organisations go through, from early activity to intermediate to advanced, by which stage it becomes business as usual.

The Early Days
Sometimes change can be sparked within a business by individuals with deep subject matter expertise they combine with a broad understanding of different domains – often referred to as T-shaped. ‘Wizards’ who can do multiple things well (for example, investment management and data science, or actuarial science and accounting), which allows them to spot opportunities and threats, and interact credibly with specialists in separate domains. 

Attempting to drive change alone is incredibly tough, and fraught with risk. Selecting a great project that demonstrates what the future could be is crucial – its success should make the organisational case for investing more heavily. In some ways, this is similar to how a start-up might seek a Minimum Viable Product (MVP) to gauge market response and obtain funding to scale. In fact, one of the (high risk) ways for a small team to disrupt their industry through better technology and a better user experience might be to found a start-up… Once they’ve demonstrated value, they may then be bought by an incumbent. Fintech/Insurtech/Othertech companies can be great sources of skilled talent and can allow established players to gain speed in return for investment. Where they remain external, start-ups can form part of an ecosystem that brings outside perspectives, adding value as a supplier or partner to the corporate. 

Failure is a big risk, especially without organisational support (or even an organisation actively fighting to reject the new approach!). And, if the project doesn’t work, the organisation won’t want to invest resources or willpower in alternative models. So, pioneers can inadvertently set an organisation back years… However, if they do succeed, it’s important that they establish infrastructure to keep the new things running and up-to-date. The data science models, freshly launched products, or sophisticated technologies need supporting structure and processes. These are often not priorities for pioneers though! 

Initial Organisational Activity
To increase the chances of success, it’s important that there is support from the organisation i.e. stealth mode is not advised. Especially in larger organisations, any initiative is highly unlikely to get far without senior management support / political buy-in, alignment with the business strategy, and complementary structure. But, not so much structure that it stifles all adaptability.

The management or C-suite support will assist the initiative to raise the major (and long-term) commitments it will need: both financial and human resources. It will also help to identify how the new technology/capability/approach will form part of, and amplify, the organisation’s long-term business objectives. 

Early on, three focus areas should be:

• building the team of connectors (including appointing strong leadership) to seed the new function
  
• developing supporting processes to foster collaboration, and
  
• finding (and scoring) quick wins.

To implement the desired change successfully, identify people with sufficient understanding of all of the different silos who can build (or already have) credibility with them individually. The leader of this bridging team is key, and their most important role at this stage is to identify (and prioritise) areas of the silos which can benefit, and build the technology/product/change roadmap. To some extent, the new team exists to encourage ongoing collaboration between different functions who don’t yet see the value in working together.

To support the new team to deliver, it should develop a (light) structure that best suits the people and the business i.e. the processes help facilitate the collaboration. This could involve meetings, workshops, co-location and more. Trial and error, and flexibility, are important i.e. find what works and do more of it to boost interaction. 

​The real test in this initial stage is whether the team can find and score quick wins, balancing the time required, cost, complexity and feasibility with the benefit to the business (through, for example, improved sales, lower fraud, better investment performance etc). Ideal first projects are ones that can deliver concrete and hopefully measurable results in a reasonable timeframe using capabilities that the team has confidence in. These early wins are vital to:

• reassure senior management that the right strategy is being pursued, to pave the way for more resources in future, 
  
• convince the silos that the new approach(es) can really improve things for them in practice, and 
  
• demonstrate the power of sharing ideas and collaborating.

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It is possible (for a wide range of reasons) that the attempts may fail. Management should think about this possibility in advance and have an exit plan in place upfront i.e. how much time and resources will it dedicate to its efforts before it ends the experiment?

One helpful model which shows different elements important in business transformation is that used by UOB Asset Management Ltd, an Asian asset manager. They call it the “four elements of digital transformation”, and shared it in Larry Cao’s paper for the CFA Institute on “T-Shaped Teams: Organising to Adopt AI and Big Data at Investment Firms”: 

• Solidify Dataset: the quality and reliability of data, data governance, data privacy and security 
  
• Sharpen Toolset: the technology tools, such as a sandbox to test ideas, and a data lake and enterprise data warehouse 
  
• Strengthen Skillset: the data-related skills and knowledge needed by employees, and the technical training required for this 
  
• Shift Mindset: shifting employee beliefs about and confidence in technology through training and resources (such as a learning portal)

The Intermediate Stage
The team will have a number of successful pilots achieved by the intermediate stage, and people will be more aware of the potential of the new approach(es). Important here is the function leader’s ability to leverage this handful of initial wins in different areas to gain credibility for the team across the wider organisation – senior management can be very helpful in socialising this too. 

Where successful, most organisations will spend an extended period in this stage, delivering value to the various departments or businesses involved. They will: 

• build out the team as the number and complexity of projects grows, adding more roles and high calibre specialists – this growth process is conceptually similar to what start-ups go through as they scale (family → tribe → village etc) 
• hone the processes for selecting and delivering projects and managing the successful ones on an ongoing basis e.g. setting up middle- and back-office operations

As they earn more leeway to take on higher-impact projects (which require more commitment and coordination), they will also be juggling multiple projects at the same time, involving different teams across the business. Prioritisation should be decided together with of all of the affected areas i.e. far more formalised than in the early stage.

One of the business design / operating model questions that tends to come up in the latter phases of this stage is where the expanding capability should be housed for best benefit. Elements of this are: 

• Should it be centralised in one team or not? 
  
• Should the team(s) be at business unit level, or regional/divisional level? 

It depends on the organisation. A simplistic rule to help guide the decision is where most of the interactions are taking place in practice i.e. if the majority of daily interactions are with a specific business function, it makes more sense to sit with them. This may be project-specific e.g. team members may move location over time as each project concludes. In fact, fluidity across functions can be a benefit, helping share knowledge and skills with more areas over time (and avoiding silo solidification). 

Where there is a more central team, they may play the role of a “centre of excellence”. Some aspects of this include setting the core vision & direction, demonstrating thought leadership (internally and externally), establishing and maintaining the ecosystem and infrastructure including policies and standards, defining minimum and best practices, overseeing all the programmes or projects, and helping develop new skills needed across the business through education and training. 

Generally, as operations continue to mature, multiple teams can be found within different divisions/subsidiaries/regions of a larger business. And, even more complicated is these multiple teams having their own hierarchy e.g. dotted line reporting structures.

Most Advanced
As you can tell, the complexity increases as an organisation becomes more advanced in adopting the (by now established) capability and embedding it in business as usual. In the advanced stage, the capability reaches its full potential, with all of the previous silos understanding each other far better, sharing their opinions openly and communicating more frequently as needed. 

It’s almost like the bridges it started are no longer needed… Under the hood, the machinery is all updated. Things are now truly integrated into the business and processes, from front- to middle- to back-office and from HQ to regional teams. Because the projects have become part of the organisation, structure and process are no longer the focus – they are ingrained. In fact, the danger is that things solidify too much again, losing the fluidity.

Success in the advanced stage also requires specialised skills, with deep subject matter experts who lead their fields – this is partly because the value is now well-established across the industry, and competition is fierce. The low-hanging fruit will all have been eaten. Talent has become critical, and the business needs solid people who deliver strong results consistently, researching and testing multiple ideas simultaneously as part of their day-to-day work. For example, in a data science context, this may include PhDs or advanced degrees in diverse computer science, mathematics & statistics, engineering and technology areas. The people pipeline is crucial, including training & development, to ensure that the skills are available when needed.

To reduce the risk of silos forming again, try to retain the multi-disciplinary teams and encourage the people to play interchangeable roles across teams over time. Incentive design can also help encourage collaboration i.e. based on overall performance, as can helping each professional to see how they contribute to the total picture.

If you’ve worked in functions such as those explored in this article before, what top tips do you have for others looking to build bridges between silos? Which structures or target operating models have you seen work best at different stages? How important were people aspects in your transformational initiatives?