Credit: Luke Chesser

Why data should be considered a corporate asset

Successful businesses thrive on data. Whether it’s customer data, machine data, financial data, or metadata, businesses that successfully collect, manage and leverage their data using a CRM system have a huge advantage over their competitors that don’t.

The business case for strong data management

A recent report by Validity Inc. asked organisations globally how important they consider their company data, how confident they are in its quality, and what operational benefits they saw as a result of effective data management. Overall, the report found that when data is properly captured and managed by an organisation, and employees across all departments and levels are invested in maintaining its integrity, the commercial benefits are far reaching.  

Looking into this further, the report found that the top 8 per cent of respondents who had “high” or “very high” confidence in their data produced more accurate sales forecasts and achieved higher lead-to-customer conversions. 

And just as the top performing companies enjoy financial benefits, those that don’t have a good handle on their data suffer commercially. Validity’s research revealed that 42 per cent of companies estimated an annual loss in revenue ranging from 5 per cent to more than 20 per cent due to poor quality CRM data. Even more worryingly, 52 per cent responded they didn’t know exactly how much revenue they had lost because they “can’t measure it or manage it.” Therefore, it’s not a stretch to suggest they may be losing even more than 20 per cent. 

What’s important to understand about high quality data and its effective use is that technology is only one part of the puzzle. Yes, it’s important to have a CRM system, but people and processes are key to ensuring that data entered into the system is not only high quality, but is utilised strategically to achieve better business outcomes. 

A recent panel discussion with data experts Ben McCarthy and Lucy Mazalon from The Drip, explored the inherent link between data quality, adoption and productivity, with each element affecting the next. It’s a bit like the chicken and egg scenario — data quality is needed for user adoption, as users won’t engage with a system if they don’t trust the data to be accurate. Conversely, the data won’t be productive if it isn’t up to date and correct, which requires human input.  

While it can be difficult to know where to start in becoming a data-driven organisation, fortunately, the strongest performing companies share some common practices which are outlined below.

Top performers have strong data governance processes 

Data governance encompasses the people, processes, and technology employed to manage a business’ use of data. It’s therefore important to establish a standard for data that fits the business’ particular needs and processes, as well as a plan for enforcing and supporting that standard. 

Becoming data-driven begins with defining what each of these foundational elements mean to the business and putting a framework in place to achieve data quality and privacy by design. A key goal in data management should be to simplify processes where possible. More process automation means fewer steps that end users need to remember, creating less friction and resulting in a more proactive approach to data best practices. How various businesses decide to construct these processes really comes down to what works best for them. 

Their leadership prioritises CRM data quality

The support of C-suite leaders in data management projects is instrumental to its success. If you are trying to engage company leaders in a data management strategy, you need to speak their language when demonstrating the negative impact poor data quality has on the company’s bottom line. 

Validity’s research demonstrated the impact poor data quality has on sales forecasting and lead conversion. Just over a third (34 per cent) of organisations with poor or neutral data quality were able to generate accurate forecasts, which has significant flow on effects to budgeting and operations. In that same organisational group, only 15 per cent were satisfied with their lead to customer conversions rate based on their CRM data. 

When you deliver the data importance message in terms that demonstrate a financial impact, it’s far easier for executives to understand and value, and they are therefore more likely to commit to driving a business-wide effort that prioritises best practice data management.

They have a cross-functional ownership of data quality 

Strong data governance also requires investment and accountability from representatives across all functions and levels of the business. Any department that accesses your CRM data will have different views on how best to use it, and they all need a seat at the table.  

A cross-functional management team for data governance and strategy is key to keeping on-track. High performing organisations recognise this, and 29 per cent said data quality is the responsibility of a full-time cross-functional team. By taking into account multiple perspectives from across the business, it’s far easier to gain a full picture on the life cycle of the company’s data — including how it’s collected, managed and used — and to identify business risks and challenges specific to various departments.

No matter where you operate, the success of businesses is increasingly determined by the volume and quality of data that powers them. Top performing businesses realise this and have long thought of and treated data as a valuable corporate asset that must be maintained and invested in. While there isn’t a quick fix that ensures data quality or a one-size-fits-all strategy for data management, companies have nothing to lose and so much to gain by committing to a companywide approach to being data driven. 


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