Science and analytics can help sharpen sales and marketing capabilities
One of the country’s leading pharmaceutical marketers was struggling to maintain its market share in the face of increasing competition. Its sales performance across its 2,000 territories was erratic and seemingly unpredictable. Like most organisations, it had simply focused on comparing the performance of its sales teams to external benchmarks, resulting in a generic view of performance rather than producing meaningful insight into what drives success in its organisation with different cultures, products, sales models and incentives.
Until one day, when the sales head realised that the answer lay in truly understanding what made his best sales performers tick. The company used an instrument that helps organisations determine what drives these higher performers, by measuring performance along three dimensions — personality, competencies and behaviours. The tool included a set of 46 sales personality attributes, 50-plus sales manager competencies and 50-plus sales representative competencies, thereby enabling a company to determine accurately what combination of specific personality factors, competencies and behaviours correlated with high sales performance. The resultant insight was invaluable and was used extensively across the various stages of hiring, training and promoting in the organisation to build a high-performing sales team. This includes:
# Pre-hire screening of new sales people who embody the traits of high performers.
# Customising development plans for every member of the sales force.
# Providing training for each sales person to help close his or her specific skills and competency gaps.
# Implementing a more informed process for promoting sales representatives to sales managers.
# Coaching to individual and specific requirements.
Think that sounds like a story out of management fiction? Think again. Organisations across industries are now waking up to the power of science and analytics, applied to the domain that until now has remained closest to an art form — sales.
The science of selling
As the business environment has grown more challenging with each passing year, companies of all kinds find themselves under mounting pressure to grow and grow profitably. Yet sales — the chief instrument for growth at most organisations — continue to fall short. In fact, numerous research studies indicate that many sales organisations struggle to master high-performance selling: Having a deep understanding of what customers value; managing and deploying new capabilities; hiring and developing talent; and getting the maximum return on these investments.
As the example above shows, the tide is turning. Powerful new options for improving sales performance are emerging that enable companies to take a more scientific approach to selling — specifically, using new analytical tools to complement their sales people’s intuition, judgement and experience and enable more effective, fact-based decisions.
Imagine applying the above approach from a 2,000-strong pharma sales organisation to a 200,000-strong insurance agency sales force! Is there an alternative to managing such a large sales organisation effectively? Can gut-feel and judgement suffice?
Marketing has also embraced analytics, starting with sample-based consumer research and expanding into other areas such as segmentation analysis, brand attitude and brand awareness research. More recently, sophisticated techniques for advertising- and promotion-effectiveness analysis, price-elasticity analysis and media-mix optimisation have helped marketers optimise their marketing investments. These techniques have also given marketers a much keener understanding of customer needs, behaviours and preferences, enabling them to target more precisely and allocate resources more effectively.(Click for table)
So what about sales? Pockets of analytical support for sales certainly exist in some companies. The most common uses of sales analytics include mining of prospect databases (arguably a marketing function) and providing sales reps with analytically-driven customer segmentation schemes. However, compared to other business functions, the use of analytics in sales is still in its infancy — not surprising, perhaps, given the number of obstacles to bringing more science to selling. These are:
# Attitude: The prevailing wisdom at many organisations has been that analytics and selling do not mix. Instead, these companies have relied on the good instincts and strong relationships of experienced, well-connected sales reps.
# Data: Traditionally, the sales function has been less data-rich than other functions, particularly marketing and supply chain management.
# Tools and techniques: Until recently, few tools and techniques were available for supporting sales analytics, and those available have not gained widespread acceptance.
# Inactionable insights: Companies that experimented with sales analytics often found it difficult to make analytical insights available to the sales force in an actionable manner.
# Additional B2B challenges: In business-to-business industries, where sales efforts target other businesses as opposed to end-consumers, applying analytics is more challenging: B2B relationships are generally complex, long-term and contractual, and the “customer” is not a single individual but rather multiple decision makers and stakeholders.
Demand for analytics
Sheer necessity has also contributed to the growing demand for sales analytics. Apart from the obvious trends of growing product complexity and range, and increasingly demanding customers, the most pressing reason today in almost every industry is attrition. Sales talent is increasingly finding that their employment market is a borderless world — it is not limited by industry. As new economy industries like insurance, telecom and retail attempt to grow rapidly, they target talent from more mature sectors like FMCG, pharma and consumer durables, driving up the rate of attrition everywhere. Sales reps turn over faster today, which limits the level of experience and customer intimacy within the sales force. This lack of product and customer knowledge also forces heavier reliance on tools and analytics.
Our own experience is to consider the traditional end-to- end sales process in its entirety, from customer segmentation and planning through to post-sales support to identify the most critical blind spots. As shown in Figure 1, common blind spots in the sales process undermine performance. In these areas, sales reps often base their most important decisions on personal judgement and intuition, rather than on facts and insights. Judgement and intuition, of course, are useful qualities to have. Stemming from experience, they can be highly valuable, accurate and even indispensable. At the same time, judgement and intuition are significantly enhanced by analytics, enabling better informed decision-making at critical points in the sales process.
A wide range of analytical tools exist today to address these blind spots, and are starting to be used by pioneers in this field to truly differentiate their sales capabilities.
Another interesting example is the use of churn or customer retention analytics in the ultra-competitive telecom sector. With the imminent arrival of regulatory changes, such as mobile number portability (MNP) and newer technologies such as 3G and 4G, the telecom sector is bracing itself for a period of intense customer churn. With the explosive speed of growth during the last decade, Indian telecom companies have not invested adequately in customer service and retention. Significant customer churn is a reality in the pre-paid business, and an imminent threat in the post-paid domain. Here again, a leading telecom provider is pioneering the use of analytics techniques to provide it with valuable insights — to understand reasons for customer churn, identify patterns, help define segments based on consumer behaviour, and help drive targeted campaigns to retain the most valuable customers.
Last, a few thoughts on managing change. A key success factor in bringing a scientific approach to selling is how well analytics capabilities are integrated into day-to-day sales processes. The importance of this cannot be overstated — in a sales context, it is much important to get this right compared to, say, a marketing context. Sales reps have little time or inclination to delve into complex analyses and insights. This does not mean that a company should skimp on rigor. However, it does mean that insights should be packaged and delivered in the most streamlined, user-friendly manner possible.
By applying analytics to key areas across the sales process, an organisation can provide the objective data that can help sales people make more informed, fact-based decisions, use their time more effectively, and boost the overall contribution of the sales organisation.
Deepak Malkani is lead (talent & organisation performance), Accenture
