With the advances in technology over the last two decades, Finance leaders can now benefit from a powerful set of tools to collect and analyse data, and to report and gain actionable insights about their businesses. That means both one-off and ongoing IT-run costs are increasing, and in its latest report, Gartner forecasts IT spend to grow a further 5% in 2022 alone.
Based on their 2021 cross-industry analysis, 64% of finance organisations plan to invest in cloud-based enterprise resource planning (ERP), 57% in advanced data analytics, 45% in data storage, 44% in robotic process automation (RPA), 13% in artificial intelligence (AI) and 3% in blockchain. This huge swell of interest in tools to digitise Finance results from the need to get proactive, actionable insights to inform strategy that organisations can now achieve via digital transformation.
Getting this digital transformation right helps generate new go-to-market strategies, and creates better understanding of your customers, employees and the markets you operate in. Finance functions also benefit from this as digital technology can start to eliminate the inefficiencies of traditional finance activities and support a better partnership between finance and operational business units.
Although technology plays a key role in unlocking these potential benefits, the journey is not a straightforward one. Successful digital transformation is much more than just deploying a new digital technology for the business. As consultants, we spend a lot of time helping organisations choose and implement the best-in-class digital platforms and have seen a common set of pitfalls that customers can face in their transformation journey. While there are many factors that can affect these big transformation programmes from methodology to the technology itself, there are three which we see tripping up digital programmes time and again:
- The existence of vast quantities of data does not mean that it is usable
- Communication is key, however; not enough by itself without change management practices
- The organisation’s ability to accept and adopt the change is dependent on its operating model’s readiness
The existence of vast quantities of data does not mean that it is usable
Over the years organisations realised that gathering data provides them with valuable insights to predict trends and customer behaviour, and overall create a higher performing business. While this is all true, many companies find themselves “drowning in data” and not able to gain necessary insight to improve their business. The rise of big data trends and a continued push for gathering as much data as possible – combined with a slower stand up of strong data governance practices – have created huge data quality issues inside organisations. Data has become incomparable, unstructured, and duplicated with multiple sources. Even with the most advanced analytics tools, it is nearly impossible to gain meaningful insight.
This issue has a direct impact on the quality of digital transformation initiatives. According to Experian, even though 87% of organisations are aware that data quality is essential for the success of digital transformation projects, 68% of companies still struggle during the transformation project simply because they have poor quality of data. New systems and processes introduced during a digital transformation programme often rely on the source data. Therefore it is critical that source data is meaningful and of high quality in order to achieve the intended value of the programme.
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