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How an Integrated Data Analytics Platform Can Help Tear Down Silos and Spark Collaboration

Posted by Jon Lexa on Thu, Jun 04, 2015

Are your employees communicating effectively? Find out how one company got everyone speaking the same language.

ITL_SignalCentral_Silos_in_the_Workplace_GP_2015_V1.1The larger a company gets, the more siloed it can become, and relying on happy hours, retreats, or top-down mandates are not enough to break these silos down. No matter how hard leadership tries, people have a difficult time getting on the same page when they all have different business objectives. And no company is immune. Even Apple has struggled with silos. Steve Jobs, in an effort to deconstruct silos, set up Apple's headquarters to encourage "collisions," or interactions between people who may not have necessarily interacted. 

For most companies though, altering the physical space isn’t enough. Encouraging collaboration in a digital environment is just as important. This can be challenging, as teams have different communication modes, geographies, and objectives. Additionally, we’ve found that teams are often operating on different data sources, making collaboration even more difficult since there is no single source of truth. Given how data can be used as a mode of communication, the emphasis on having a common data source is critical for achieving an effective collaborative environment. Teams will otherwise spend tons of time reconciling differences in data rather than collaborating. One way to work around these obstacles and encourage effective collaboration is to create a shared digital workspace using an integrated data analytics platform.

Here’s how one Fortune 500 Company stumbled onto this revelation…

A large global product manufacturer faced significant challenges in overcoming silos among Marketing, Commercial Planning, and Product Management. Over the course of scaling up, the organization’s structure evolved in a fragmented manner, partly because of geography but also because of a lack of collaboration. Each group became more concerned with its own mandate and less concerned with the company's vision. Product Management wouldn’t talk to Marketing, Marketing had to communicate through Commercial Planning to talk to Product Management, and so on. You may be thinking, Wow. That's completely dysfunctional. How do they even operate? Surprisingly, this company pulled in $18 billion in revenue last year and has been in existence for over 40 years.

Although its top-line number is worth writing home about, the existence of silos resulted in a significant waste of marketing expenditures. One specific example of this inefficiency occurred when Marketing wanted to know what products to focus on. They asked Commercial Planning, who then met with Product Management to come up with various options. Product Management then acted independently and implemented a pricing strategy that undermined Marketing’s strategy. This dysfunctional behavior prompted Marketing to think of ways to circumvent the process and get their own view on potential demand. Ultimately, none of this behavior was beneficial for the company since it did not result in a cohesive strategy that aligned teams with the broader goals. Their system was broken, and the mechanisms in place to encourage communication and collaboration were failing.

Coincidentally, the company was implementing an integrated analytics platform at the time to ingest data from all parts of the business. The initial goal of the platform was not to bring teams together, but to enable teams to conduct advanced analytics and build customer-centric insights on the company’s 55 million customers. The platform had two big features: the first feature allowed analysts to extract, transform, and load data from a variety of sources onto the cloud, build Signals and models, develop workflows, and reuse code; the other feature allowed analysts to manage solutions, explore data libraries, visualize Signals and their related entities, and integrate the analytics into standalone outputs such as dashboards or data feeds. While the first feature laid the foundation for scalable analytics development and testing, the second provided the overarching structure for sharing knowledge and best practices. Furthermore, the platform provided a single source of truth for data — something the company found immense value in because a single source allowed teams to finally speak the same language.

With teams sharing the same data elements, analytical capabilities, and best practices, they essentially shared the same data “watercooler.” This had a profound effect simply because they could now build on one another’s work. For example, when a marketing analyst wanted to show a visualization of revenue impact from the marketing campaigns, he built on Product Management’s revenue calculation function. When a product manager wanted to determine which products would need a pricing strategy, she leveraged the same forecasting algorithm Marketing used to determine marketing strategies. When Commercial Planning wanted to understand customer behavior trends, the team slightly tweaked the models created by Product Management during hypothesis testing of a new product feature. The true value of the platform had extended from providing a single source of truth to allowing scalable analytics development rather than reinventing the wheel each time.

Through sharing best practices and scaling models and code, teams were empowered to collaborate directly and indirectly, which benefited the company as a whole. In addition, each individual was able to perform at a higher level of productivity because he or she could build on top of other teams’ work. By investing in a collaborative data analytics environment that addressed the needs of all user types, the company enabled digital collisions and fostered an atmosphere ripe for innovation.

Our analytics platform, Signal Hub, can do for you what it did for the company in this post— plus a lot more. Visit our Signal Hub page or check out our newest white paper, which focuses on Signal Hub's ability to provide customer insights to help marketers achieve segment-of-one marketing.

 

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Topics: Signal Hub Technologies, Analytics