By Thomas Tuchscherer, CFO & VP of Corporate Development, Talend
Self-service data preparation, defined as the process of collecting, cleaning, and consolidating data into one file or data table for use in analysis, is often referred to as the next big thing. In fact, Gartner recently predicted that “by 2017 most business users and analysts in organisations will have access to self-service tools to prepare data for analysis”.
The most positive news about the new focus on self-service data preparation is that it goes beyond the office of the CIO. It represents a significant step forward for data-driven organisations as a whole. If done well, it will allow everyday business analysts to put data to work in their operational context whether they are in sales, marketing HR or indeed in finance, where its benefits are perhaps most compelling of all.
Most finance departments would concur with the views of Philip Howard, research director at Bloor, who states: “Extracting value from data has historically involved a lot of time and effort – especially when it is disparate and from multiple sources. And far too much time and effort has been spent just getting the data ready to be analysed rather than in the analysis process itself.”
Liberating the Finance Team
The tasks for hard-pressed finance and accounting teams are seemingly endless: formulating income and cash flow statements; extracting trial balances; adjusting the nominal ledger, preparing full sets of management accounts, maintaining accurate sales and purchase ledger databases. It all represents a major burden on these departments who today often face hours of work cleaning up data in excel or ensuring everything is in the right format.
This is of course, a typically a cumbersome, complex and unwieldy process and can also be error-prone which is a serious problem for any business. Mistakes in an income statement will have a severe impact on the balance sheet and cash flow statement. A simple transposition error can lead to a serious misstatement of the accounts as a whole, if not identified and rectified quickly. Moreover, if you chuck high volumes of bad data, such as incomplete contact information, into your purchase ledger database, for example, you’ll end up gaining a reputation for late payments and putting your business’s reputation at risk.
Fortunately, with the advent of self-service, data preparation applications, this burden is now being alleviated. The ability to explore, cleanse, enrich and combine data in minutes, instead of hours, allows accounts and finance staff to apply their own unique domain expertise and work directly with the data that’s relevant to their own specific objectives.
By simplifying the whole process, this capability represents a huge step forward from using traditional spreadsheets within accounts and finance departments, helping empower business analysts, even those with no IT background, to get data into the format they can effectively use to generate business insights. Even without an IT skillset, finance and accounting teams can start working on their data while avoiding having to create complicated formulas, write code or complete the same tasks over and over again.
That does not mean that the IT department no longer has a role to play as a support function or that accounts and finance departments should always work in isolation, however. The best self-service tools should foster collaboration, effectively providing a sound way to reconcile IT and finance and accounts so that they can unlock data collaboratively.
Yet, being able to use the latest technology to streamline the whole process and reduce the time taken to prepare data from hours to minutes will clearly help finance departments wrest back time from the laborious process of cleaning and crunching data and allow them to spend it instead on driving critical strategic tasks like financial planning and analysis and risk management.
In short, the ability to help finance staff access, cleanse and prepare their data quickly, enables those workers to spend more time on the high-value task of extracting insight from the data and sharing that back with the business. This is critically important because analytics can be the driver for competitive differentiation for an entire company and the ability for finance to act on data quickly will increasingly be the key determinant for success for many businesses.