The usage of data is a prominent goal for the digital transformation of business models. The amount of information we have to oversee is growing rapidly. Data is created from every action taken by every Internet-empowered device, and it’s only going to develop. A full 90 percent of data in the world today is only 2 years old. 85 percent of CEOs say they put a high value on data analytics for their company (PwC, 2015).
EY’s approach for leveraging accounting insights through analytics start with data too as it forms the basis of management. Reliable data is needed by businesses to make strategic decisions. Analytics can be beneficial to both clients and organizations. Some of the benefits include greater confidence in financial reporting as it allows organisations to identify hidden patterns, trends and anomalies in their data resulting in deeper understanding through 100 percent coverage of transactions and identification of risks that matter. (EY, 2018, p.9). EY’s globally integrated data capture and extraction tools like data cleansing, scripts, data standardisation and deduplication algorithms save the team’s valuable time and efforts by identifying data anomalies across industries.
On the contrary, transformation to analytics is not always easy to accomplish. Tom Lefervere claims that high costs, a time-consuming change process and software integration are common obstacles to smooth digital transformation. He also believes that the impact of digital transformation is not only limited to a firm’s core business but also the role of employees working in accounting and financial services (Lefervere, 2019).
Tricia Morris says that the future belongs to the Intelligent Enterprise. Those who are able to act on insights and change the client experience and be the first to find and convey new plans of action will be the disruptors. Those who are unable to will be the disruptors in a period of quickening Digital Darwinism. As per Tricia’s stats, 85 percent of the enterprise decision makers surveyed feel that they have a time period of just 2 years to make consequential inroads on their digital transformation before they have any financial bearings. Only 38 percent of the executives feel that their business leaders completely utilizing their analytics initiatives. Insights driven organizations are growing at an average of more than 30 percent each year and are 23 times more likely to acquire customers, 6 times as likely to retain them and as a result be 19 times more profitable. 60 percent in the finance function say that they use data to drive long term strategic planning and find new opportunities to fund business growth (Morris, 2018).
Its clear from the above statistics that organizations that want to succeed must be able to identify transformational possibilities before they become evident and act on it actively.
Data governance is a comprehensive way to deal with the manner in which you manage, gather, use, and store information. A decent data governance program incorporates a cross-useful group, a specific set of procedures, and an arrangement to execute and screen those procedures. There are consequences to not having an effective data governance program. In the absence of a data governance program, the decisions made about key data systems are made by an association of staff who “own” the system. When there are different owners for systems (which is very common), the result is inconsistencies in data availability, collection, usability, integrity, and security (Association Analytics, 2019).
According to EY, data governance is an increasingly strategic issue for the board as a host of new cyber and privacy requirements have gotten their attention and have opened discussions about data governance to include data usage, privacy considerations, and information security. These laws and regulations such as the Europe’s General Data Protection Regulation make companies and their boards more accountable for breaches and compliance failures related to data altogether (EY,2018, p.).
Deloitte stated that it would be sensible to add a chief data officer to the job description, someone with the passion and the clout to drive continuous data improvement, to deliver insights and services to the business instead of being distracted by questions of data integrity and completeness (Deloitte, 2019, p.20).
In an era of a digitalised world, companies are struggling to find the right blend of digitised skill sets and business intelligence to embrace and adapt to the pace of change, largely due to the digital knowledge gap in their workforce. Wayne Eckerson, business intelligence and analytic expert, has introduced the term ‘Purple People’ for team members who are able to combine the red tech speak with blue business speak translating between data scientists and decision makers.
Data intuition skills is one such skill. It covers how to apply and interpret data to solve most pressing challenges, asking the right questions about data at the right time and developing subject expertise pertinent to areas to bring in critical thinking and scepticism. Another core technical skill is the knowledge of programming tools and languages such as python, SAS and key tools to aid data wrangling including Power Query and relational databases (SQL) are becoming increasingly important as well (ICAEW, 2019).
REFERENCES:
PwC. (2015). Data-Driven: What students need to succeed in a rapidly changing business world. Retrieved from https://cpb-us-w2.wpmucdn.com/sites.gsu.edu/dist/1/1670/files/2015/08/pwc-data-driven-paper-1wdb00u.pdf
ICAEW. (2019). New skills for the Digital Era. Retrieved from https://www.icaew.com/technical/technology/finance-in-a-digital-world/work/new-skills-for-the-digital-era
EY. (2018). Accounting analytics. Retrieved from https://www.ey.com/Publication/vwLUAssets/ey-accounting-analytics/$File/ey-accounting-analytics.pdf
Lefevere, T. (2019). Digital Transformation in Accounting: Redefine your core business. Retrieved from https://www.silverfin.com/en/blog/digital-transformation-in-accounting-redefine-your-core-business
Morris, T. (March 2018). Infographic: The Role of Data in Digital Transformation. Retrieved from https://www.microstrategy.com/us/resources/blog/bi-trends/the-role-of-data-in-digital-transformation
Association Analytics (2019). What happens when you have no data Governance?. Retrieved from https://associationanalytics.com/2017/03/30/what-happens-when-you-have-no-data-governance/
EY. (2018). Data Governance: Securing the future of financial services. Retrieved from https://www.ey.com/Publication/vwLUAssets/EY-securing-the-financial-future-with-data-governance/%24FILE/EY-securing-the-financial-future-with-data-governance.pdf
Deloitte. (2019). Crunch Time V: Finance 2025. Retrieved from https://www2.deloitte.com/au/en/pages/finance-transformation/articles/crunch-time-v-finance-2025.html
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