Recently we started a project where my new client was bemoaning: “we’re never going to deliver an accurate sales forecast until we get people to use our CRM and put in accurate data.”
He pointed out that the company had tried a myriad of ‘fixes’ that included purchasing all types of bolt-on technologies, putting in new sales processes, and hiring/firing sales people. Most fixes did produce short term gains – see the Hawthorne Effect – but within a quarter or two gravity takes over and they were back to the same problems.
The foundational question - why do so many companies fail to correct their bad CRM data?
I have worked with hundreds of companies over the past 14 years on how to eliminate missing, bad, or dirty data. Here is a simple ‘Rule of 3’ list of what to do to uproot data challenges.
1. Identify of the source. The first step is to determine the source of the inaccurate, incomplete, or inconsistent data. Don’t ask for too much data, and make sure the MVI (minimum viable information) you require is accurate at each stage in the sales process.
2. Eliminate workarounds. Reinforce your CRM platform as the ultimate source of truth. Stop any external workarounds or manual processes to ‘fix’ the data. Avoid implementing any quick fix, bolt-on technologies that only result in making your bad data - prettier. Workarounds often become the ultimate scapegoat that allows managers and sales teams to discount the value of accuracy in your CRM platform.
3. Minimize uncertainty. Provide continual inspection of the MVI required by sales stage. Run all forecast and pipeline meetings directly out of your CRM system. Follow your inner detective: just the facts.
Once completed, take the following proactive steps to break the gravitational pull and ensure ‘good data’ continuously makes it into your CRM platform.
Document what good data looks like.
Look back over the past 4 to 8 quarters for those opportunities that have been Closed/ won. Determine which attributes and metrics have the highest impact on winning to establish your company’s unique Optimal Opportunity Profile (OOP).
Prioritize where to start.
Take each late stage (proposal, negotiation, etc.), ‘must win’ opportunity and apply your unique OOP to determine which opportunities are, and are not, aligned to where you historically win. For each opportunity, identify bad, missing or insufficient data that when corrected will optimize your probability of winning.
Assign accountability.
Clearly define who is accountable for correcting the data quality issues and establish a time frame for correction. Create reports to monitor that the data is corrected and hold these individuals accountable for ongoing data quality. Empower front-line managers to have the ultimate accountability for pipeline accuracy.
Create a holistic training regime.
Provide comprehensive training upfront, and periodic quick training sessions so that every individual knows their role in ensuring data quality across your sales process. Establish performance metrics that enforce the benefits of good data. When there is accountability, fewer errors will occur.
Establish your CRM as the ‘Only Source of Truth’.
Begin and end all sales and marketing reviews within your CRM platform. Create dashboards and early warning reports that align to your identified MVI information to quickly identify if data is missing, or data quality is deteriorating.
Dirty-data results in wasted resources, lost productivity, failed communication—both internal and external—and wasted sales and marketing spending. Your business might already be planning to tackle its dirty-data problems. If you follow the steps outlined, you will address the core changes needed to affect positive change where it is needed the most.
