Digital Leadership Community Round-Up: Communicating with the Board

Tom Schwieters (Vice President)
Chris Weston (Principal, European Client Advisory)
Marc Dowd (Principal, European Client Advisory)

IDC’s Digital Leadership Community met on September 30 to discuss “communicating with the board of directors — tips for getting to the top table in your organisation”. We had a lively discussion with contributions from many of the participating CIOs. There was a range of ideas and examples shared on how to best manage the few precious moments that we have in front of our boards. The overwhelming goal of optimising the messaging and its delivery was to position IT as a strategic part of the business and to avoid the board perception of the CIO as the laptop, iPad or (God help us) BlackBerry fix-it person.

What to Communicate

The content presented to the board should be focused on the possibilities of new technologies to improve the outcomes of the business, major technology risks to the business or the performance of the IT function. In many cases the board expects the CIO and IT to be visionaries and to provide inspiration for what technology can do to improve business outcomes. No one in the organisation understands the technical aspects of technology better than IT, and in many ways no other function has such a broad view of the processes in the business. Highlighting major cyber risks, IT security threats or post-incident reporting to the board are often key elements of the CIO’s job. Regarding IT security and technology risks in general, CIOs should make sure they position the non-negotiables and explain their criticality and potential impact on the business.

In terms of reporting on IT performance, the message should be focused on outcomes for users of technology and on top-level reassurance that all core systems are stable (if indeed they are stable). Are the users happy? Have they got the right tools? Does their technology support their effectiveness, productivity and well-being? Is IT helping to move the business forward or is it acting as a blocker? Simple satisfaction surveys, supplemented with face-to-face interactions, can measure these outcomes.

How to Communicate

This is where real artistry is needed, and the participating CIOs contributed some excellent ideas. The importance of pithiness, style of language, showing rather than telling and drama are all important elements in effective communication with the board. Barring a catastrophic cyberattack or other such calamity, the CIO has at most 15 minutes to shine in front of the board. For this reason, it’s critical to keep the message short and to the point. Time invested with key board members beforehand can help prime the topic and reduce the need for as much explanation at the board meeting itself. Also, if you received any questions from the board prior to the meeting, make sure you answer those ahead of time, to save time on the day. The words chosen also matter greatly. Avoid jargon or acronyms, if possible, and define them if they are necessary. Focus on business outcomes, not technical details. Be honest and open in your messaging and style of delivery.

One CIO emphasised the importance of showing rather than telling — demonstrating new functionality on an iPhone, for example, or switching off the meeting room lights unexpectedly from a smartphone to demonstrate cyber-vulnerability. Many people are more receptive when they see the phenomenon itself rather than simply hear about it. A bit of theatricality can help emphasise a point, whether it’s a dramatised (but factual!) rendering of the Colonial oil pipeline hacking and resulting societal fallout and impact on that company and board, or the successful digitisation efforts of a competitor or player in an adjacent industry and how that has impacted revenue/stock price. One extreme example of showing rather than telling: the CIO of a major European car manufacturer brought his entire board to Silicon Valley for a series of meetings with large and emerging tech vendors and venture capital investors to develop a sense of the creativity, urgency and importance of technological change.

Of course, our meetings with the board will be that much more effective if we have developed strong relationships with board members outside of the meetings. To that end, the CIO should make efforts to meet with each board member to get to know their personality, priorities and areas of expertise and influence. During these meetings, the CIO can share their views on the role of technology in the business and the opportunities to grow and optimise the business with the use of technology. These meetings will also enable the CIO to determine the digital maturity of the board member, and can serve as a form of personalised digital training for the board member.

IDC Digital Community Roundup — Balancing Run/Grow/Transform

Chris Weston (Principal, European Client Advisory)
Marc Dowd (Principal, European Client Advisory)

What follows is a summary of the meeting of the IDC Digital Leadership Community (DLC) held on September 16, 2021. CIOs and other digital leaders from across Europe combined their experience to talk through the competing pressures of run/grow/transform for their businesses and IT teams.

The reality for many digital leaders, as articulated at the start of our conversation by one CIO, is that there is a genuine struggle to find the capacity in IT teams for anything beyond the “run” element of this triangle. There was general agreement about this issue but also an understanding that all sides need attention. Another opinion, aiming at the fundamental question of the CIO role in this, was that the IT team’s influence on this has shifted a lot since the run/grow/transform idea became widely known. Business teams increasingly select and configure technology platforms independently that need continuous maintenance and improvement. A CIO can and perhaps must influence — but not direct.

How to achieve this is a well-known journey and one that is regularly followed. A culture shift is still needed to maintain alignment with a fast-changing business environment and help shape demand coming to the IT teams from their colleagues. This requires CIOs to carve out time to maintain relationships and stay ahead of the curve in their business and their industry, not to mention benchmarking and checking that their approach meets the right needs.

One of our community members working in a fast-scaling start-up spent some time explaining his experience where run/grow/transform was compressed to one activity, which he described as like changing the tyres on a car while it was moving. With little legacy and transformation as a daily fact of life, the key issues were making the right foundational decisions around technology and architecture so that scaling is possible.

As a view of the future, this was a useful perspective. As a counterpoint we heard from a CIO in the middle of a large, transformational modern workplace programme to evolve the management of IT and the needs of the business, including hybrid working. Business growth in that case requires business and IT transformation, and this brings into doubt the whole question of grow and transform as discrete activities, given the digital nature of most business activities now. The progression from on-premises tech, to co-located, to public cloud has compressed these aspects, meaning that transformation becomes less painful but constant. In the start-up space there was a feeling that IT teams lose the requirement to deal with physical items and “DevOps-style” skills become more of a focus. A different approach to budgeting and cost monitoring was also in evidence with far fewer “project” style costs appearing.

During the discussion we noted that transformation was ubiquitous. In the insurance sector, for example, we have seen traditional businesses sparking work around open data, AI for fraud detection, insurance as a service, etc., and this needs a focus on coding and data skills throughout the organisation. This is just one example of what is happening in companies of every size and type.

Any discussion involving digital leaders will also touch on security, and this is where we ended, with a discussion around the ownership and leadership needed to ensure that risks to companies are mitigated effectively with security issues being communicated and decided at the right level, built into the transformation effort.

Once again, the conversation and debate in our Digital Leadership Community was of the highest standard and a lot of great insight was shared. If you would like to join our conversation, please get in touch with us or find our IDC Digital Leadership Community group on LinkedIn.

Do We Really Need (More) Coding to Have Successful Data Scientists?

Giovanni Cervellati (Research Manager, European Software Group)

In a world that is moving fast towards simplification — in everyday life and in the workplace — the analytics industry is ready to move away from requiring its workforce to expend most of its energy on writing lengthy, complicated code strings.

The analytics software market has long offered easy-access solutions for enterprises. With data scientists increasingly focusing on real-time insights or predictive analytics, we cannot afford for them to concentrate only on the technical side.

What You Don’t Expect: No-Needed Programming on the Rise

Nowadays, people are keener and keener to have more insight with less effort. This is true for both everyday life and the workplace, and it’s happening faster than we might think.

Think about how much time and effort you would have spent 10, 20 or 30 years ago carrying out a task — it would almost certainly have taken much longer than it would now, and the time it takes has reduced decade by decade.

You’d think the same is happening in analytics. It’s obvious, right? Unfortunately, no.

The analytics world is somehow following a counter-intuitive trend. While platforms have long been providing easy-access solutions to the labour market’s analytics needs, use of open source platforms has surged, requiring data scientists to have coding skills.

The huge rise in frameworks leveraging Python, R and other language applications has reached the point where people identify the data scientist job as a “high-code-employee” rather than a person with deep knowledge of statistics and machine learning algorithms or processes.

Companies and universities have rapidly adapted to this, and are teaching programming languages as part of their analytics courses. As a result, the need for code-skilled professionals has also increased, widening the gap between highly skilled analysts and data scientists and business-literate employees — in some ways, exactly the opposite of what is going on in the outside world.

But why has this happened? The reason for switching from user-friendly software to a code-based application has often been the free access to it (most are open source) and its guarantee of continuity without being kept in check by vendors. The surge in open source software in analytics and ML has led to this unique situation where high-code applications have been taking advantage of classical, low-code applications over the past few years.

The game-changer in the whole analytics and data market has been the move from legacy on-premises solutions to the cloud. Initially, cloud providers further strengthened the code-loop because they were focused on professional developers and have been bundling open source analytics tools and frameworks widely for some time. They like machine learning workloads because they use a lot of compute cycles and data storage, which they can charge for and because they get analytical capabilities for free. The recent implementation of many no-code platforms in the cloud may slow down this trend or at least provide an alternative.

The Path to Data-Driven Enterprises Must Be Simple

In today’s volatile, fast-changing business environment, it’s critical that companies have the best possible analytical capabilities. Whether it be more focused on descriptive, visual analytics or predictive analytics through machine learning, enterprises need fast, easy analytics to speed up their journey to becoming a data-driven enterprise.

The trend towards improving data literacy and data democratisation doesn’t fit with this trend to high coding tools. There is a need for employees who can use and understand the business’ data and take advantage of insights.

To become an intelligent enterprise, you should focus on creating a data culture. This culture should permeate the entire company, with people at the top. Employees should speak the same language, and data scientists are no exception. Leveraging the investments in technology can free the company from cultural silos, leading to better communication with employees more comfortable with data. Viewing data scientists as “nerds” doesn’t make things easy — implementing a widespread data culture will shorten the distance between people in the enterprise, and user-friendliness and natural-language software must be a big part of this. Data scientists themselves can change their approach from “what do you want from the data?” to “you may need it”.

A data-driven enterprise will look to any effort to make data and its use more understandable, more widespread and easier to use — breaking down the walls that keep technical jobs separate from other professionals.

The “Smart” Data Scientist in a Low-Code Enterprise

Relying on code-based applications for analytics and machine learning is making it harder to become a data-driven enterprise.

I have been a data scientist for almost 15 years, and I know that focusing on line-of-code errors makes the job harder, more frustrating and sometimes impactless. Coding is not natural and it’s not easy to use, and it makes the analytics work both more time consuming and harder to understand. You can just lose sight of the main goal.

The era of smart working is already here, and the pandemic has accelerated the move towards it. Home offices, digital transformation and agility are now everyday concepts in today’s companies.

In this scenario, a smart data scientist is not a high-code specialist, but someone who can seamlessly find insights, trends and patterns in the data, and use their knowledge to interpret it in the best possible way.

Technical vendors are pushing their easy-to-use, innovative new solutions. With the new software, you can solve most machine learning issues and tasks even with limited technical knowledge: experts’ added value can almost exclusively come from their ability to understand the big picture of analytics and the “good-looking” results you can get from the data. AI is also moving in this direction, giving access to fast and easy information through natural languages or simple acts.

By investing in these new solutions, an enterprise can open the way to seamless, broader data knowledge and leverage data scientists’ experiences to achieve the best results.

Now is the time to rediscover the power of simplicity: in an over-simplified world, analytics should no longer be “just for the few”.


To learn more about our upcoming research, please contact Giovanni Cervellati, or head over to and drop your details in the form on the top right.

Balancing Run vs Grow vs Transform in the Digital Age

Chris Weston (Principal, European Client Advisory)
Marc Dowd (Principal, European Client Advisory)

There is a challenge faced by business leaders every day — how to prioritise their time and energy investment in three areas:

  • The day-to-day running of their business, ensuring that customers are satisfied and that the work that is done is profitable
  • Opportunities for growth, be that looking into the existing customer base to become a bigger part of their spend, finding new customers in existing markets or expanding into new ones
  • Reorganising and transforming their business to better reflect customer demand, improve processes or even to take advantage of new technologies or suppliers in their market

The IT world has recognised these three aspects for some time and there has been an understanding that CIOs also need to balance them to support the organisation and increasingly to inform the business of the most effective mix of these efforts, whether that is through things like opportunities for efficiency through automation or a new technology that enables expansion into adjacent markets. However, the pace of change in recent times, even without the effect of the COVID pandemic, has blurred the line between the grow and transform investments to the point that it is almost foolish to speak of one without the other.

Organisations are finding that being closely integrated with their supply chains and their customers is no longer an interesting experiment; instead it is becoming an essential aspect of being competitive. Growing your business requires the adoption of new ways of working with these stakeholders and the adoption of fast-moving digital channels that lead to constant transformation. So, it’s worth considering your own situation and reflecting on whether these two aspects of grow and transform are distinct or tightly linked.

In our advisory work at IDC, we can see many organisations choosing a product management approach to help deal with this conundrum of how to manage these priorities. Product management has a laser focus on customer needs, and this helps to align all business stakeholders around the true reason for a product — whether that is an internal system or something used by customers or suppliers. Really good product teams don’t wait for requirements to be handed down from above; rather they are constantly working with all their stakeholders to understand how their product will evolve and building the business cases for this work to fulfil both the grow and transform agendas for their organisation.

Of course, this is not the only way to tackle this question, and it’s certainly not a silver bullet. In more traditional structures CIOs have to take a step back and have honest conversations with the people they serve in all parts of the company, from the customer-facing end user to C-level colleagues, to really understand what the impact and value of their run service is and the opportunities or requirements for growth and transformation. Often a business can articulate a strategy and this is underpinned by a level of funding that can be leveraged by IT. Conversely, some CIOs tell me they don’t have the budget to do it all, which is certainly a position I sympathise with having been in that situation myself. The answer is always in prioritisation. Sometimes this is a painful process, but it must also be informed by the real value of the priorities being discussed — foundational technology is often unsexy but without it the shiny, customer-facing investments can end up out on a limb and quickly lose their appeal.

If you are struggling with this balance, it’s important to realise that you’re far from unusual in this and that the tension between these requirements is a natural part of a growing and evolving business. It isn’t always possible to solve the puzzle to everybody’s satisfaction. To get there, or even close, is a team game that requires the whole company and their leadership to work together and agree on the plan, and the timescales, that are being worked to. A successful CIO can be the catalyst for this agreement by pulling all the threads together in their own road map.

Managing the tension between run, grow and transform will be the subject of our IDC Digital Leadership Community session on Thursday September 16 at 4pm BST/5pm CEST. Join us and your peers across Europe to discuss the best approach to this difficult problem.