Erich Gerber,
There are numerous quantifiable benefits to analytics, including increased productivity and profitability. That’s according to consultancy McKinsey & Co, which notes that companies that use customer analytics extensively are more than twice as likely to generate above average profits than those that do not. McKinsey research found that adding analytics to operations to tackle Big Data can help companies outperform their peers by five percent in terms of productivity and six percent in profitability.
As the benefits of engaging in Big Data and Analytics (BDA) initiatives are evident, a study by IDC predicts that BDA related services marketing in the Asia Pacific region excluding Japan will rise from US$3.8 billion to US$7.0 billion in 2019. This projected growth is propelled by the increasing demand for analytics-related systems integration and Business Process Outsourcing (BPO) services.
" Leaders charged with making Big Data programs work need to understand and acknowledge this reality and develop specific approaches to build trust that overcomes the emotional resistance."
Another study by IDC states that Australia, Singapore and India are currently the most advanced countries in Asia-Pacific in utilising analytics tools and applying data-driven approaches for enhanced decision making. While placed in the median range, China and India display accelerating Big Data growth rates in relation to IT expenditure.
Such BDA initiatives have risen largely due to the region’s drive to build Smart Cities. In particular, BDA is a key driver in Singapore’s Smart Nation vision – critical to ensure seamless functioning and delivery of services in a highly connected nation and helping businesses seize new opportunities.
However, most companies struggle to overcome human behaviour - specifically resistance from sales employees to use the tools - according to the McKinsey article.
“Leaders charged with making Big Data programs work need to understand and acknowledge this reality and develop specific approaches to build trust that overcomes the emotional resistance,” the article notes. “That means more than just training employees to use technology to better engage with customers, the best leaders develop examples of what most effectively addresses specific concerns, creating a clear path of action and adopting new
The article goes on to note the most common behavioural obstacles from sales representatives to using BDA and how to overcome them:
1. Tool Fatigue
Sales representatives are often exposed to tools that despite claiming to provide significant benefits are far too complicated, the article notes. “First, note that studies show that the additional time associated with working with recommendations from analytics is insignificant or non-existent,” McKinsey points out. “Second, in many cases these systems can in fact save agents time by providing accurate recommendations for specific cases that, in the past, agents themselves had to do with outmoded software and little or no analytics support. One of the best ways to convince your representatives is to get them to commit to investing a small amount of time (less than 30 minutes) to test run a recommendation or run a simple query.”
Working with data analytics tools should be intuitive and easy for anyone. If analytics is complex and difficult, the user acceptance will diminish significantly.
2. Clinging to Intuition
Many sales employees are convinced that their intuition and experience can provide better guidance than analytics. Leaders can overcome this myth by showing how analytics can help them do their jobs more effectively and make more money, McKinsey advises. Clinging to intuition and “gut-feel” may not be as effective in closing opportunities, especially in an evolving environment where customers are creating conversations through a myriad of channels and platforms. Sales teams must be able to analyse the “tsunami of data” and to see patterns for predicting and reacting to changes, in order to remain competitive and successful.
“So, show them the earnings difference between a team that uses analytic recommendations and one that does not (if the example happens to show a marked improvement in the performance of previously ho-hum sales representatives, all the better).”
Using interactive dashboards, which can offer immediate snapshots of customer history and details that could otherwise be embedded deep in tables, numbers and spreadsheets, can be a game changer in being able to react to and tailor services to customers accordingly. As a result, sales teams can instantly identify customer purchasing habits and prompt targeted promotional offers, to quickly improve customer satisfaction.
3. Trust Issues
For many sales representatives and customer service agents, the notion that machines are replacing humans can create an obstacle when putting into place a new analytics initiative. It is critical to note that data analytics and the resulting insights can be effective success factors for sales people. The ability to predict the interests and needs of the modern day customer, who is comfortable interacting on multiple platforms, will be the key to long term success for the organisation. Machines performing the more redundant and routine tasks and complex problems demanding a human interface are issues that need to be communicated consistently.
Managers must train their sales and customer service teams to enable them to deal with this and recognise how accurate data and the ability to predict behavioural patterns, to cater to “crunch” moments or cyclical challenges, will help in growing customers’ loyalty through a positive and richer experience.
“One thing we recommend is turning top performers into allies and more importantly, advocates,” according to the article. “Top sales performers often have major influence within organizations. Getting them to work with the “meaty middle” - the 80 percent of representatives who are neither at the top nor the bottom of the pack - is critical because changing the behaviour of this large group will have the biggest impact.”
