The CFO's journey to digital maturity starts with defending against threats. The next step involves laying solid foundations. The building blocks? Systems and data.  

Leading-edge technology has the potential to radically transform business performance and it can be tempting to rush into implementation. However, to harness capabilities such as GenAI and automation, organisations must first ensure they have strong core systems, data management and quality data. ‘Walk before you can run' is the motto for success.  

“At the start of our journey, we prioritised gathering high-quality data and ensuring it is easily accessible to the business as it is crucial for making informed decisions and driving business growth.”

CFO, The Old Station Nursery 

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Looking to invest in technology?

Mark O’Sullivan, Head of Technology and Digital Services, shares what finance leaders should consider when looking to invest in technology. 

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Pillar one: Enterprise systems

The prize for getting enterprise systems right is competitive advantage. In our digital CFO survey, almost 100% of respondents said that core systems, such as ERPM,  are a critical enabler of business strategy, yet only half said they were highly satisfied with how their current applications perform.

The benefits of successful systems investment are many: an improved control environment, reduced cyber/data risks, automated and consistent processes, better analytics and insight, and an improved experience across customers, suppliers and employees.

So, how can companies avoid failure?

Principles of successful systems implementation

System failures often result from missing one or more of the five principles for successful implementation.  

1. Clarity of vision

Be clear on your 'Why?’ Your starting question should be, 'What needs solving now and in the future?' A clear grasp of this avoids technology for technology's sake.

At the outset of any implementation, there is a significant risk of over-scoping the programme and underestimating the time and resource required to deliver. Gather all the data you need to make decisions on change management, data migration, and integration architecture.

Plan in detail what you need to achieve and by when. If you get the vision right at the beginning, it will support effective decision-making throughout the programme.

2. Engaged and aligned leadership

Leaders at all levels of an organisation must be aligned with the objectives, methodology, and plans for the programme. Even if this is happening at the start of a programme, it can often drift through the course of delivery. Establishing and maintaining a consistent voice for the programme provides the strong foundation for good cross-functional collaboration.

In post-programme reviews of failed implementations, we often see senior stakeholders positioning themselves outside of the programme because they want to separate their personal brand from the risk of failure. Leaders must remain engaged and available to support solving issues and challenges during delivery.

3. Focus on the wider operating model

Too often, businesses expect new systems to be a panacea for all their back-office issues. The reality is that the broader operating model needs equal (if not more) focus. People, processes and technology are mutually dependent, and it is essential to consider how they interact when designing a system. 

Work alongside the implementation partner to define the resources, skills and experience that will be needed. For certain key resources, you will need to ensure their time is protected and not done alongside a day job. 

4. Engaging your people

Implementing systems, such as modern Software as a Service (SaaS) solutions, calls for carefully considered change management. Success lies in the adoption of new functionality and processes. Bringing business users on this journey requires more than training and comms: they must understand why their role is changing and how that benefits them personally.  

One of the common failings of systems implementation is that all of the change activity is compressed into the final couple of months of the programme. Setting up your programme for success requires early planning of the change activity and consistent focus on various stakeholder groups throughout.     

5. Effective governance

There is no one-size-fits-all when it comes to effective programme governance. It must be tailored to the systems being implemented, the business culture, and the nature of resources used. Too often, companies set up a Programme Management Office and use a set of delivery templates taken from the 'last internal project'.  

Successfully delivering systems implementation requires careful consideration of the governance model. Establish clear and measurable entry/exit criteria for milestones and delegate decision-making authority within the levels of the structure. Getting your governance model wrong can lead to a lack of control or a programme stifled by an inability to make decisions and keep to time.   

When working with third-party implementation partners, it's crucial to choose those with a strong relationship fit and the right technical experience. This ensures problems are resolved quickly and effectively during programme delivery. 

Mark-O-Sullivan
"Effective pre-implementation planning can materially de-risk investment in new systems."
Mark O’Sullivan Partner, Head of Technology and Digital Services

Pillar two: Data 

Organisations face challenges in managing data effectively as regulatory expectations and operational complexities grow. 

A recent FCA and PRA report on artificial intelligence shows that four out of the top five current risks are related to data. This will likely lead to more regulatory scrutiny to ensure that data used for mandatory reporting is accurate, timely, and well-governed. 

However, many organisations struggle with siloed data structures, fragmented data sources, and a lack of clear data ownership. This not only creates compliance risks but also hampers strategic decision-making and creates a lack of trust in data reporting.  

Are you prioritising automation over data?

As businesses embrace automation, AI, and machine learning, the need for high-quality, well-structured data becomes even more critical. Without this in place, automated processes will simply amplify errors.

Yet, many firms have legacy data frameworks that can’t support agile decision-making and innovation. The challenge is made worse by privacy regulations, cybersecurity risks, and the sheer volume of data generated daily.

It’s easy to argue the investment case for automation as it has a tangible ROI. However, CFOs must potentially work harder to demonstrate that data quality is vital to sustainable success. By treating data as a strategic asset from the outset, organisations can unlock greater efficiencies, insights and returns from their digital investments.

testimonial client avatar
"Organisations need to reframe their view of data governance and management from a brake to an accelerator that helps you move faster with error-free automation."
Nikhil Asthana Director

Five ways to get data right 

1. Governance and ownership 

A clear governance framework with accountability for data ensures that financial data is accurate and consistent, while reducing risks in reporting and decision-making. 

2. Privacy, compliance, ethics and risk management  

Finance leaders must ensure data meets ever-changing privacy, compliance and ethical standards.

This means following financial regulations, maintaining audit-ready records, and implementing strong controls to prevent financial crime and fraud.

Organisations must focus on data security, access controls, and ethical data use to protect information and comply with privacy laws.  

3. Quality and integrity 

Data quality is often one of the weakest controls in business, leading to costly errors, inefficiencies, and reputational damage.

Finance teams must implement strong data validation, cleansing, and monitoring processes to ensure accuracy, completeness, and reliability in financial reporting. 


4. Advanced analytics, AI and automation

Leveraging AI, automation, and analytics can improve forecasting, fraud detection, and financial planning. However, these technologies require a strong data foundation to deliver meaningful insights and drive efficiencies. 

5. Scalability and future-proofing  

As organisations grow, their data strategies must evolve. Finance leaders should design adaptable data architectures that support future business needs, digital transformation, and emerging technologies. 

Laying the groundwork

With systems and data in check, CFOs need to move their focus to the skills and people who will unlock the potential that digital developments bring. The next insight in this series will explore this in more detail. 
 
Equal investment in systems, data and your people will set your organisation up for success in their digital transformation efforts.  

Hub

The CFO’s journey to digital maturity

Support for finance leaders to advance through the four stages of digital maturity.

    *The CFO Digital Survey is an anonymous questionnaire for 300 CFOs at businesses with £50 million-£1 billion annual revenue (mid-market) and 200 CFOs/GFCs at businesses with more than £1 billion annual revenue (large corporates). The data was obtained in June 2024.

    All respondents come from UK-based businesses across a range of sectors and regions.