Talk to two different business users in two different departments and ask them what they think about the quality of the customer master and you might be surprised to hear that you hear two completely divergent views.

How does it happen, that two different people in two different departments using the same customer master data might have differing thoughts on the quality of the data? The answer might lie in the simple fact that for the two different groups, the needs and effectiveness of the data that is held might meet the purposes of one group but not another.

This dichotomy often stems from where the data originated, it may also stem from the different levels of rigour that the two different groups apply to the maintenance of the customer master. It could even be this way, because of the CRM, ERP, POS or CDP systems that are in use.

The order-to-cash process is pretty well understood in many circles as the process that involves a combination of sales operations, elements of logistics for fulfilment and the accounting function in the collection of the payment either at the time of order entry or through a post-delivery or at-time-of-delivery billing function.

In a nutshell, OTC is where your organization receives, processes, and completes customer orders. Most often it is used in reference to sales on credit. As a function used by a great many organizations, it is a crucial function for organizations that sell goods and services The effectiveness of the OTC cycle is often gauged by financial metrics and measures. These measures and metrics help businesses understand their sales performance and cash flow. Common measures are revenue volumes, margin contribution, personal performance, Days Sales Outstanding (DSO) and bad debts.

Describing and elaborating on these aspects is beyond the scope of this piece but suffice to say that a great deal of these measures are bound up in the quality of the customer master data that your business has on hand and leverages in the sales order cycle.

An important thing to also remember is that many companies fail to recognize the correlation between the quality of their customer data and the health of their cash flow.

Tracking and analyzing customer master data helps manage the whole length of sales cycles and provides insights into opportunities for optimization that should be explored further.

Customer master data issues in the OTC are probably considered most critical in the B2B sector but unfortunately, customer data quality-related issues are pervasive across all sectors and B2C suffers some of the exact same challenges as B2B.

Here are some elements of the data quality that are worth considering as a part of the OTC cycle.

Data fit for purpose

Even If the customer master data record is adequate for issuing an invoice or receiving payments, the customer master data record could nonetheless be incomplete or incorrect for the purposes of other departments like logistics, service, support or marketing. Since invoicing and payment processing typically occurs only periodically, and in some cases maybe even only once a year (annual subscription); there’s a risk that the rest of the organization could encounter a data problem at any time.

This is particularly prevalent if the customer audiences are regularly changing their contact details or if the needs of the business are expanding and require the build-out of more data to better serve the customer. Early customer data acquisitions may fall far short of immediate needs and now there is a mad frenzy underway to work out how to fill in the blanks.

Refining the message

Marketing’s automation of routine tasks is essential for organizations to remain ahead of competitors and remain relevant to audiences. Data is required to drive those automation. For the automation to be effective, the data needs to be of great quality and sufficient detail that the messages can be appropriately personalized. If the data is incorrect, inadequate or missing, marketing’s automation efforts will fail to hit the mark.

By using customer master data effectively marketing teams can make a difference at the top of the funnel. Conversations between analysts, MessageGears, and business leaders reveal that 90% of business leaders feel that digital messaging mechanisms like emails, mobile phone messages and messages through other platforms like Facebook and Whatsapp are extremely important when compared with other marketing activities, principally because they can be customized.

What next?

Given these challenges in perspective, in particular, it is important to therefore work out how to resolve the gaps in data quality and missing data or fragmented data that are needed by the rest of the business.

Regardless of their size, companies often recognise poor quality data issues, but they don’t necessarily understand how they can improve the situation. In fact, in 2017, Gartner stated that the average financial impact of poor data on companies was around $15 million per year, several years on, we can expect that that number has grown. Adopting a customer master data management program helps minimize the disconnect between the needs of departments and the effective improvement of customer master data quality.

Pretectum’s approach to helping in this area is with a cloud-based customer master data management platform that allows different parts of the business to hold records of customers that align with specific functional needs but at the same time service the wider needs of the larger business. Only through the democratization of the customer master records is it possible for cross-functional departments to recognise, identify and leverage the best possible customer master data records to drive business opportunities and effectiveness in the communications, service and support of the customer.

The Pretectum CMDM platform allows the users of the system to retain their own distinctive data without contaminating or compromising the data of other groups, but at the same time allows them to share a common understanding of the customer, a single customer view if you will. This approach can be adopted in a decoupled or tightly integrated way with existing systems of record through integration.

Inaccurate or incomplete data means that teams spend more time researching and confirming contact information than actually engaging in higher-value work like selling, servicing or supporting customers. Today your teams could be spending as much as a third of their time negotiating with bad data rather than with customers and prospects.

Contact us today to learn more about how the Pretectum CMDM could be of benefit to your business.