6 Steps Toward a Savvy Big Data Collaboration

Customer Experience
Customer Experience
Organizations need to break down departmental silos and encourage company-wide collaboration to make the most of analytics resources

The sheer amounts of data that organizations have access to today can help them better interact with their customers and provide an improved experience. However, limited funds mean that several organizations are scrambling to find enough money to finance their analytics endeavors.

The trick, according to experts, is to align different departments and encourage them to share both the data they have access to as well as their budgets, allowing the entire organization to invest in projects that wouldn't be affordable by a single department. "One of the most significant obstacles to turning raw data into actionable intelligence is the fundamental lack of effective data sharing across departments and divisions of the enterprise," notes Scott Schlesinger, head of business information management at Capgemini North America.

However, the first step is for business leaders to choose the organizational model they want their company to evolve into. Zubin Dowlaty, head of innovation and development at Mu Sigma, explains that most organizations choose one of two models: a purely decentralized model where analysts and data scientists are employed by specific departments with very little visibility and communication with their peers in other sections of the organization; or a centralized model which allows the whole company to leverage the resources of a central analytics team. But Dowalty notes that some organizations are opting for a more advanced federated model, which finds a balance between the two extremes by building a network of analysts in different departments, giving them visibility into different data resources and access to a shared budget. While the latter is more complex to implement, Dowalty says this is the way forward, especially for bigger organizations which want to make sure their analytical resources are made the most of.

As experts note, not every organization is ready for such a culture of sharing resources and this requires executive buy-in to make sure that all the different departments are aligned and prepared to work together. Here are some tips that experts believe will facilitate the process:

  • Eliminate departmental silos: Despite the recognition that information silos can cause problems because of lack of visibility and lead to duplication of work, there are still many organizations grappling with this issue. Breaking down these silos and creating bridges between different departments is considered the foundation for a sound analytics strategy. Jon Ezrine, senior vice president and chief operating officer at Nexidia, recommends creating cross-functional transformation teams which are mandated to bridge the silos and have access to data housed in different departments. A major telecommunications company chose this route, when it created a team made up of representatives from customer care, marketing, and IT, allowing for more collaboration both between departments and also across different regions. AJ Gandhi, vice president of customer solutions at Lattice Engines, says business services company Wolters Kluwer worked to integrate data from its various business units, countries, and legacy systems, allowing the organization to develop sturdier analytics to help the organization figure the best cross-sell plays for the thousands of products across hundreds of thousands of customers, leading to win rates up to three times higher than before it implemented this approach.
  • Make data visible: While bridging silos is a great first step, there is still bound to be information housed in the different departments. Lattice Engines' Gandhi, says a foundational investment is in a centralized data warehouse. "You can't do much with Big Data until you link your various data sources and clean your most important data," he notes. Organizations need to make sure that this data is visible to other departments which can tap into it to make improvements to customer experience. "A lot of data sitting in different departments can be relevant to other departments," notes Lou Guercia, president and CEO of Scribe Software. "They just need to tap into it, making it essential to have visibility into the data that's already available, allowing them to determine what's relevant to them," Guercia notes. Such visibility can be facilitated both through dashboards that make the data visible across the enterprise or meetings between key executives who can share the findings of their departments.
  • Create a sharing culture: While sharing data is a start, organizations shouldn't stop there. Instead, they should also join their budgets to invest in both hardware and software that can provide cross-departmental benefits, notes Venkat Viswanathan, CEO of LatentView Analytics. Jon Ezrine, senior vice president and chief operating officer at Nexidia, makes the argument for cross-departmental collaboration by saying that if budgets are housed in different departments, there might not be the critical mass to embark on major projects.
  • Attain executive buy-in: Experts believe that the top echelons of organizations need to be aware of the need to align the different departments and also push for funds to finance data initiatives. "You need the CEO on board," stresses Viswanathan. Viswanathan says when the boardroom is aware of the need for an aligned data strategy it might push for the appointment of a chief data officer who can take charge of any organizational changes to make better use of data.
  • Demonstrate ROI: Business leaders are wary of spending money unless they are almost certain of a return. It is therefore imperative to demonstrate ROI. Ezrine notes that it's difficult to get budget freed up until sustainable ROI can be realized. Gandhi recommends starting small and achieving early wins which can be leveraged to make a point for increased investment in analytics. Anil Kaul, CEO of AbsolutData, recommends that organizations first determine how data will help them make money before making the needed investment. Kaul stresses the importance of clearly indicating the value that each department will be getting from a Big Data investment.
  • Create friendly competition: Erzine says some organizations struggle with internal rivalries, making it difficult for departments to work together. This is something that needs to be addressed. Mu Sigma's Dowalty recommends that companies use gamification to get their internal analysts to compete with each other and create a more efficient team.

Finally, organizations might also consider the possibility of outsourcing their analytics needs, but making sure that whichever company they hire can bring together the different departments and coordinate a strategy that makes the most of all available resources and is beneficial for the whole organization.