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3 Tips to Improve Sales Data-driven Decision Making

By Dave Egloff | August 19, 2020 | 0 Comments

Sales OperationsSales Strategy and Design

Many sales analytics functions are quite busy churning report after report to their sales and non-sales stakeholders.  However, despite their level of activity, many organizations still struggle with data-driven decision making.

While it’s true that internal systems and corporate functions are growing more interconnected, there is a paradoxical challenge.  Reporting continues to get easier, but the volume of reports is not the key to improve the impact of insights.  Counterintuitively, more reports can lead to more noise instead of better decisions.

Here are three tips for sales operations leaders to improve how their organization leverages sales analytics for decision making:

Tip #1 – Improve Data Literacy

Data literacy is the ability to understand, communicate and contextualize data, including the underlying data sources and analytical methods.  Plus, literacy suggests competency in applying the understanding to gain business value.  Unfortunately, data literacy is a limiting factor for many organizations.

In a recent Gartner survey, sales operations leaders rated the level of sales data proficiency of their stakeholders.  Enterprise analytics, IT, Finance and executive sales leaders ranked at the top of the list.  Seeing executive sales leaders near the top was encouraging.  Unfortunately, the bottom three included sellers, HR and sales management.  This survey was targeting sales data proficiency, and still, sellers and sales managers were at the bottom falling below other key stakeholders.

Sales operations leaders must proactively develop strategies to improve data literacy like bolstering documentation, training and internal support.

Tip #2 – Compare for Context  

Sales operations should help their stakeholders by displaying current values along with targets.  They can even take a few more steps by illustrating:

  • Percent difference
  • Color-coded sentiment indicators
  • Recommended actions

As an example, let’s imagine that a sales manager’s dashboard shows a 2.8x pipeline coverage ratio – should they feel good about it?  It depends.  If the sales manager has a target of 3x, they are trending below target and need to get more deals in the pipeline.  By itself, 2.8x is less informative.  However, when it’s compared to a target, the sales manager has a better chance to understand their current performance and what they need to do.

A common question is “where can I get a good benchmark value?”  In some cases, sales benchmarks are well-known.  However, some benchmarks can be harder to find, especially if they are industry-specific.  If benchmarks aren’t attainable, sales operations should leverage past performance averages to show longitudinal trends.

Tip #3 – Align with a Use Case

As noted, sellers and sales managers were towards the bottom of sales data proficiency.  Besides training, documentation and support, sales operations leaders should design reports that align with how sellers and sales managers work.  In other words, the reporting should bend to the use case.  Unfortunately, users often have to bend to reporting.

Sales analytics use cases – like seller coaching, pipeline management and territory planning – have specific requirements based on how users function and the decisions or insights needed.  Sales operations are in a unique position to share insights to improve decision making while also reducing the administrative burden.

One savvy sales operations leader has his analytics team – specifically those designing dashboards – shadow key users.  As the analytics team appreciates the user experience, they can better design reports focused on driving specific outcomes.

More and more stakeholders across the entire organization are consuming sales analytics.  Sales operations leaders must embrace this new reality and recognize their opportunity and obligation to improve data-driven decision making.

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