It is estimated that companies spent over a trillion dollars last year on digital transformation with one of the key objectives being to make data more accessible for staff. However, even with the significant investment made in digitisation, 62% of people still rely on others for their data while the majority of companies complain that data is trapped in legacy systems. Disconnected data in finance act as ball and chain, tying down your staff as they spend inordinate amounts of time in spreadsheets to meet the demands of the business, regulators and customers.
In this post, we will discuss why it is so difficult to connect data from disparate and legacy systems and why the pragmatic approach needs to be the use of automation to help finance staff unshackle themselves from the burden of disconnected data.
A recent survey found that large companies use over 500 different applications at any given time. Some may argue that nobody needs 500 systems, however, the reality is that many of these tools are critical to keeping the business running.
Within most organisations today, you will find a scatter of technologies including legacy systems, core applications like ERP and CRM and a bevy of specialised tools and platforms aimed at addressing problems across the organisation. Some of these tools run on-premises while others are on the cloud. In fact, 85% of companies today are running on multiple cloud vendors.
In addition to "getting the job done", applications generate and store data that is often needed by finance departments for reporting and analysis. However, this data is often inaccessible, with 62% of people stating they rely on others to get their data. What's more, around 76% of companies complain that their data is "trapped" in legacy systems. Disconnected data in finance is an unfortunate reality, believed to be costing upwards of $140 billion dollars each year in wasted time and lost opportunities.
You can be forgiven for asking why the problem of disconnected data in finance even exists. Every organisation has its unique challenges, but some issues are facing most large companies when it comes to their data:
Pain point #1: How do you get the data out of the systems?
Legacy systems are thought to make up around 70% of all software used in large companies. Antiquated and rigid are probably two words that most people would think of when asked to describe their legacy applications. These systems also represent a significant challenge when it comes to data as they often do not have readily available APIs or data abstraction layers making it difficult to interpret and access data. What's more, projects to modernise legacy systems are often expensive and slow due to the often out-dated programming language of the system and the subsequent shortage of skilled programmers to do the work.
Pain point #2: What do you do with the data once you get it out?
Putting the difficulty of data extraction aside, you then need a place to store all of that data and make it accessible to the business. Data Warehouses are a popular, but expensive and rigid choice. An enormous amount of "pre-processing" effort goes into cleaning and modelling data before it gets to a data warehouse to ensure the data is accurate and usable by the business. The HR cost for maintaining a data warehouse starts at $430k per year.
Some companies have also invested in Data Lakes on the promise they are cheaper to build and maintain than data warehouses. The cheaper cost of data lakes is partially due to skipping the pre-processing work needed for Data Warehouses, effectively making them giant buckets (or lakes) of raw data. There are no shortcuts, however, as technical staff are then needed to clean and model the data from the Data Lake before it is usable by the business.
What is the result of the pain points above? For most companies, it means having a long-tail of requests for data to be made available in data warehouses and their BI tools while staff are left using spreadsheets and manual processes to bridge the gap caused by disconnected data in finance.
For CFOs, many of whom are under increasing pressure to evolve and focus more of their resources on analysis and communication, the challenge of disconnected data in finance is like sprinting with a ball and chain. The image below shows a typical finance team:
Finance staff (in the blue box above) are spending an inordinate amount of time gathering, cleaning and processing data in spreadsheets so that they can respond to requests for information from the business and other stakeholders. This reliance on manual, spreadsheet-based effort can often result in missed deadlines and, painfully for many finance leaders wanting to grow, missed opportunities to focus time and energy on more value-added areas such as doing more analysis and sharing insights with the business.
Some of the less obvious or immediate impacts spawn from the fact that for most companies, the blue box in the image above is a black box. That is, most people don't know how finance staff turn the data they collect into information that they then place in front of management and regulators. This lack of visibility can result in severe and embarrassing errors, and bottlenecks as interdependent processes become utterly reliant on the small handful of staff who understand how to process the data.
During a meeting, a CFO of a large public company said to us that "in five years, it will be a sackable offence to be using a spreadsheet". Five years on, the spreadsheets are still there, but the CFO is long gone.
The pace of change in today's business world is staggering. A by-product of rapid change is that IT systems are often left chasing shadows. By the time IT can adapt to a change, the business, its customers or regulatory environment may have already shifted focus. Spreadsheets have become the default way for finance teams, in particular, to react to the more immediate changes.
Companies around the world are investing $1.3 trillion in digital transformation projects in the hope that it will make them more agile. However, the challenge of legacy systems remains. According to Deloitte, 43% of companies believed that integrating existing platforms was a significant barrier to their digital transformation ambitions. McKinsey recently stated that almost 70% of digital transformation projects would fail to meet their goals.
In the meantime, finance staff continue to plug the gap by spending 25% of their day in spreadsheets. Finance leaders, therefore, must be pragmatic. By all means, we should be working towards a digital utopia where all systems and data connect seamlessly to one-another and staff have real-time access to high quality and democratised data. In the meantime, however, automation is a powerful tool that will allow finance teams to unshackle themselves from the burden of manual data work and will enable them to spend more of their day on analysis and communicating insights with the business.
Disconnected data in finance is a pain borne out of an abundance of legacy systems and rapid change in the business and regulatory environment. The investments in digital transformation will, in time, simplify the data landscape for many companies. However, this will not happen overnight, and rather than suffering from manual spreadsheet processes, the pragmatic finance leaders will invest in automation to unshackle their staff and allow them to focus more of their time and energy on analysis and communicating insights.
If you'd like to learn about the challenges facing finance leaders who want to automate, read our whitepaper.
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