Because big data reveals insights not uncovered by other methods, it can make collaboration easier. Here's how that's possible, plus four strategies for leaders who want to bring teams together.
In 2015, Queens University of Charlotte conducted a survey of U.S. managers and employees that revealed that 39% of employees felt that people in their organizations didn't collaborate enough, even though nearly three quarters of surveyed employees viewed teamwork and collaboration as highly important.
Since then, collaborative project management software and social media-style HR and administrative systems have been used to stimulate better collaboration between business units and departments. Unfortunately, the departmental silo problem persists.
"Companies tolerate silos because fixing this issue requires some very fundamental changes, and that feels risky and difficult," said Johann Wrede, global vice president, strategic marketing for ecommerce software company SAP Hybris.
In many organizations, the silo problem is most evident between marketing, sales and customer service. This silo disconnect impacts companies because no one in the organization sees the entire customer experience, which can jeopardize customer relationships (and revenues) if folks are unaware.
Knocking down silos is also an area where big data and analytics are uniquely suited to help.
Chris Rothstein, co-founder of Groove Labs, an inbound-outbound sales platform, and a former sales manager at Google said, "When we began analyzing our customer data at Google, we asked ourselves, 'How do we get to better sales numbers by using this data?'"
Rothstein said that he and his team began to use analytics so they could look at certain factors such as which industry sectors were most likely to use a service. "What we began to do with the data was to build profiles of customers who were most likely to buy our services," he said.
The value to sales was immediately evident. Sales no longer felt marketing was just dumping leads over the wall without qualifying them for likeliness to buy. This helped marketing gain credibility with sales, and it built a case for closer collaboration between the two.
At the other end of the spectrum is customer service, which is usually viewed as a cost center by businesses and has little credibility with sales.
"Instead of the traditional view of service, imagine a customer service manager walking into a super salesperson's office where the salesperson has a 90% commit from a customer, said Vala Afshar, chief digital strategist for Salesforce. "The customer service manager tells the salesperson that she has just completed analytics on sentiment, and that the last net promoter score on that customer was pretty low. The recommendation from service might be that the sales person put in a call to that customer, which could save the sale."
Sales again sees the value in actionable insights from big data and analytics that service delivers. The analytics build a case for ongoing collaboration between sales and service.
What big data and analytics strategies can business managers use to break down functional silos in the company?
Evaluate your big data assets
Companies still struggle with sorting out through all of the big data that they are storing. Until they get the bottom of the data that they have under management, they will not know the data they have and all of the ways that they can possibly use it. Now is the time to inventory your various data sources and the data they contain so you can determine the data stores the are still untapped but that could bring new value.
Challenge departments to develop and share responsibility for the same objectives
When different company departments work together on the same objective, they gain greater insights into how they can help each other, the quality of their big data queries, and the company overall. If the objective is to retain customers and build revenues from these customers, sales can be selling and service can be tipping sales about which customers are happy and which aren't before the calls are made. Meanwhile, marketing can be learning from sales about about which products customers like best, and what future product enhancements customers would like to see.
SEE: 60 ways to get the most value from your big data initiatives (free PDF) (TechRepublic)
Develop new algorithms and queries that deliver actionable insights
If customer sentiments over social media aren't matching recent sales results, there could be product flaws or brand perceptions that customers are struggling with but that the sales force is unaware of. Unfortunately, sales is unlikely to get a heads up about this unless someone is marrying unstructured social media sentiment data with transactional sales history on customers in various demographics.
This is where collaboration between marketing, sales and service really pays off because departments can pool their knowledge so they can come up with insightful questions of their big data that reveal breakthrough information. For instance, instead of asking which areas products are selling the best in, companies could also be asking if their customers are satisfied with recent purchases. They could then bend the answers from both questions to come up with insights into whom of their existing customers is likely to reorder and when.
Measure for results
If you can't link improvements in revenue, customer retention, product quality, time to market, and other tangible elements to your big data and analytics work, you aren't going to make inroads in tearing down department silos, either. At the end of the day, employees and their managers want to see analytics results that help the business, further their careers, and assure them that the jobs they have today will be there tomorrow. Your chances to contribute to these universal hopes are exponentially increased when big data and analytics can probe new areas and combinations of data for breakthrough insights that make business better.
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