Data is a key resource – if not the resource – that powers modern business. Yet, unless it is in a homogenized package, its benefits are limited, thus limiting what industries – especially the accounting and lending industries – can achieve for its clients.
The power of data is well known. However, full adoption has been slow, despite the indisputable fact that data is the key to becoming a future ready business.
What is Data Standardization?
Data standardization is the process of transforming data from disparate sources into one consistent format, allowing confidence in the completeness and integrity of the data.
The ability to create consistently formatted data is crucial for accounting firms and lenders because of the large amounts of data from different sources that are received. Data standardization is a cost-effective way to build trust and reliance on data, as it inherently ensures that the data is complete. Further, it is cost effective because users are only working with one set of data regardless of the source.
Why Data Standardization?
Competitive Advantage: Data standardization is a critical step towards improving data quality. It enables businesses to move from data compilation and formatting to the higher value work of data analysis.
Businesses that can analyze data more effectively and reliably, are better able to compete with larger companies and provide added value to their clients. One way smaller businesses are doing this is by partnering with third party technology companies.
Cost Savings: The use of technology to gather and standardize financial data provides a considerable time savings. Operations also benefit from streamlined workflows. As businesses save money through the process, the capacity to serve more clients increases, leading to a positive impact to the bottom line.
Collaborative Analysis: Standardized data is ideal for collaborative analyses, by enabling groups to work from a unified perspective and define clear and robust parameters from which to review and test data in order to form objective conclusions.
Planning and Implementation
Some businesses understand the need but struggle to determine whether they will have the capacity. A key to success with any data analytics project is planning. This includes setting objectives, deploying the right data analytics tools, importing data properly, and determining the output.
Set Objectives: Before looking at any tools or speaking to suppliers, it’s important to establish the project goals and focus on what information shared with clients. A lack of focus can result in costly inefficiencies.
Deploy the Right Tools: After establishing objectives, determine the tools needed to deliver the project. Will the firm invest in internal infrastructure or opt for a cloud-hosted solution? What software will be used to analyse the data? How much data will be pushed through the software? Is it suitable for that amount of data? How will the insights be displayed?
Import the Data: What data is required to complete the work? More importantly, where is the data stored? A business could collect data from uploaded backups or CSV files; however, this method may not be accurate, thereby putting the firm at risk of incorrect analysis. Connecting directly to client accounting packages and databases will offer the most accurate and real-time information.
Determine the Output: After the data is imported, it is important to determine how this information will be displayed to the business’ stakeholders and to the client. In such a visual age, clear graphs and charts are effective in highlighting key concerns. The quality of data imported is important. The more data there is, the more insight a business can provide.
The Importance of Data Standardization
The transformation to become a more digitally based business is essential to becoming a truly service based provider. This is an essential and natural step to take, as most businesses work to understand their client’s needs.
The analysis of standardized data helps the business to take an independent, non-biased look at their client’s financial data to provide meaningful advice. Most businesses develop specific domain expertise across one or more industry verticals, and the ability to analyze, compare and benchmark this data across several companies within that vertical places the business in a unique position to provide sector wide insight and guidance.