“Over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth.” states the 6th edition of Domo’s report Data Never Sleeps. With data growing at the breakneck speed each day, companies are struggling to keep pace and derive meaningful insights that are critical to improve sales performance despite a growing rate of adoption of analytics technologies.
According to a study conducted by McKinsey & Company, “57% of sales organizations today do not see themselves as effective users of advanced analytics. In contrast, 53% of high-performing sales organizations rate themselves as effective users of advanced analytics.” The root cause of this discrepancy generally falls in one of three categories according to our research:
Lack of a well-designed analytics strategy
Few business leaders dispute the impact of technological disruption on business practice evolution. Unfortunately, companies can get focused on adopting the newest tools instead of focusing on carefully identifying strategic focal areas where technological support would yield the highest value. The foundational piece of advice for companies trying to successfully implement analytics tools is to consider the company’s strategic objectives, understand the core processes that need change and identify the key areas that would benefit most from supporting technologies such as analytics.
Once a strategy and roadmap is defined, the next step usually is to select the best tool for the job. A key consideration in solution selection is ownership. If self-sufficiency for business users is the main intent then selecting a tool that needs an engineering army to maintain detracts from the original purpose while adding more cost to the business. Prioritizing fundamental project objectives in the selection process prohibits teams from veering from the elemental criteria required for long-term project success.
Lack of communication & enablement
One of the main reasons analytics strategies fail is the lack of dialog between the decision makers and the solution users. A well-planned communications strategy is imperative to ensuring that intended users throughout the organization understand the new solution’s benefits for their individual roles. As a follow-up to the communications strategy is an effective enablement strategy that enables solution users to easily arrive at their “aha” moment and solidifies the tool’s value in their minds, thus increasing adoption and realizing the intended ROI.
With a robust strategy and the right solution, we have found four areas where analytics solutions help organizations improve sales performance:
1) Pipeline Management
“44% of executives think their organization is ineffective at managing sales pipeline” states a Harvard Business Review. For sales professionals, pipeline management is synonymous with easy access and visibility into relevant information to direct their next course of action. With the ability to integrate with CRM data sources, analytics solutions not only provide reps with a view into their current opportunities but also allow the rep to predict future revenues with clarity and help prioritize leads with the greatest returns. With the ascent of prescriptive analytics, reps can be pro-actively presented with top opportunities.
Democratizing sales analytics with additional factors such as expected quota attainment, commissions and bonuses based on opportunity forecasts provide sales professionals a comprehensive view into their sales activities from open opportunity to commission realization.
2) Sales Rep Performance Management
Sales performance scorecards are an easy way to monitor sales rep performance and identify the team’s top and bottom performers. Companies can also leverage analytics to determine the root issues behind the results and address performance gaps. Do bottom performers need more training to achieve defined targets or do consistent top performers point to a flaw in the existing compensation plan design? The answer to these questions can help organizations focus on addressing the main challenges that hinder expected results.
3) Effective Compensation Plan Design
A fundamental component in helping sales professionals achieve set targets is optimized compensation plan design. Are the compensation plans designed for fair participation or is there any presence of flaws that allow for a pay-for-performance disconnect where certain teams or individuals can game the system? Analyzing and monitoring for plan effectiveness ensures that the plans are paying for performance and any misalignment can be corrected appropriately. Additionally, organizations can also monitor the efficacy and relevance of different types of recognition and rewards systems for targeted audiences. An incentive for preferred parking may be much more enticing for an employee working in a busy downtown office versus a gift card.
4) Up-sell & Cross-sell Opportunity Identification
In recent years, expansion of share-of-wallet in the existing customer base has been a topic of much discussion for business leaders across the globe. Organizations are leveraging predictive and prescriptive analytics to maximize customer lifetime value through outstanding customer experience. A significant aspect of providing great customer value is proactively addressing the customer’s need for additional solutions in a timely fashion. Analytics can surface the required insight into customer needs and their propensity to buy for sales professionals to capture and maximize revenue-generating opportunities.
InnoVyne delivers BI solutions that help companies measure and improve sales performance, identify trends, and more efficiently achieve business objectives. Contact us to know more.