Founder and CEO of Gotransverse. A 25-year veteran of global enterprise software with a focus on monetization.
Today’s businesses are suffering from a data glut, costing them money. Inadequate and erroneous data is making its way into business systems, preventing accurate billing and hindering growth. To stop revenue leakage from poor invoicing and to enable business expansion, businesses need to clean their data before they begin the billing process.
According to IBM (via Harvard Business Review), bad data cost U.S. businesses $3.1 trillion in 2016 alone. Gartner, Inc. estimates that poor data quality costs individual companies $12.9 million, and those costs are not just an immediate impact on revenue. Poor data quality leads to poor decision making.
The greater the billing volume, the more data must be processed—leading to more errors. As subscription-based and consumption-based businesses scale, so does the level of billing complexity.
• Billing data must be aggregated from multiple sources, increasing room for error.
• Data mediation/normalization is required to convert usage data into billable events; the greater the billing volume, the more complex the mediation.
• Complex business rules such as volume discounts, free trials, prepayment discounts, local taxes and partner payments can add another layer of complexity and potential errors.
To generate error-free customer invoices at scale, you must start with clean, readily accessible data.
Addressing The GIGO Problem
The global e-commerce market for subscription businesses is expected to grow from $650 billion in 2020 to $1.5 trillion by 2025 at a compound annual growth rate (CAGR) of 18%. Companies generally are not prepared to handle the data volume, accuracy and velocity required for scalable subscription and usage-based billing. Any problems related to insufficient data will result in inaccuracies scaling with billing. The losses grow as well.
Usage data drives subscription businesses. Whether the industry is energy, telecommunications, media, entertainment or retail, consumption of watts, minutes and media rentals need to be converted from the amount consumed to the amount to be billed. Inaccurate billing data is a leading source of revenue leakage. The billing engine needs accurate customer consumption data to generate accurate invoices. If the data is inaccurate, incomplete or outdated, the invoices generated will be incorrect and categorized as garbage in/garbage out (GIGO).
Most companies deal with data and billing inaccuracies manually. Staff must manually validate spreadsheets or other data sources, verifying that the data matches the invoice. Using manual measures to correct data inaccuracies is not scalable and is prone to its own set of errors. The best way to avoid the problem of remedying inaccurate billing is by starting with reliable normalized data.
Practicing Good Data Hygiene
Ensuring you maintain clean data from the outset is the best strategy for promoting scalable, agile billing. There are several best practices to consider.
Data is typically aggregated from multiple sources to create a single billing record. Incorrectly normalizing data is one of the primary sources of data errors. Be sure to have a data quality plan that consistently requires best practices and reveals the sources for dirty data. Check critical data entry points and standardize information whenever possible. Real-time data volumes tend to create noise, so the billing system needs to be fast and accurate.
Use a programmable billing platform that automates workflows and processes. Automate data transformation, synchronization, cleansing and classification. Also, address issues such as duplicate data and appending data records. The billing system must be programmable to accommodate data-process changes and promote billing agility. The goal is to ensure clean data flows into the system to power repeatable processes without errors.
As part of billing programmability, business rules must be adjustable. The business will evolve, and the business rules will need to change—including maintaining accurate and complete data for accurate billing and regulatory compliance.
The key to scalable billing is elasticity—i.e., adapting quickly to changing needs, including provisioning to match usage patterns. Native cloud-based billing can deliver limitless capacity and scalability with little lag time.
Using reliable data to power billing can also deliver reliable business intelligence. Analyzing billing data can inform decisions across the organization. Using data from billing and receivables can highlight trends such as product performance, customer engagement and business churn. Real-time billing data can be used for predictive analytics for forecasting and help with decision making about cash flow, inventory issues and unexpected changes in the market such as a global pandemic.
Applying proper data management and billing technology can deliver the scalability and agility needed for subscription billing. It is essential to correct errors and inconsistencies across data sources. It would be best to also eliminate or at least minimize the need for manual inspection of invoices. That requires a reliable billing engine that can process transactions and conduct invoicing quickly and at scale. Lastly, do not be beholden to how you’ve always done things. Use this as an opportunity to adjust business processes for maximum business agility.
Making data accuracy a priority can ensure more accurate billing, reduce revenue leakage and give you the foundation for growth and better business insights. Data is the fuel that drives today’s business performance and profitability.