The explosion of data, coupled with tools used to collect and analyze that data, has fundamentally transformed how we communicate, collaborate and innovate. Every employee now has access to some level of analytics, helping to guide strategic decision-making and processes. Yet, while we’ve made great strides in data democratization, businesses struggle to master data centralization. And, as a result, are housing siloed treasure chests of knowledge that remain largely untapped.
Over the last five years, the complexity of data consolidation has grown in parallel with the expansion of SaaS and unconventional sources (e.g. Google Docs, Quip, social streams, text). The average business is now using around 60 different SaaS applications. Each of these, producing analytics that speak a unique “data language” with their own set of metrics, properties and taxonomies.
This proliferation of available information fueled an organizational shift in 2016. Businesses were encouraged to design data-driven cultures, infusing data within every level of the company, product or service. Even something as simple as sending a cup of coffee can now be analyzed to determine revenue impact and conversions!
We have incredible data at our fingertips, but many businesses have failed to make the progress they anticipated. Why? Because amidst the excitement of adding new tools, sources and applications to the analytics repertoire, they neglected to develop a structure that ties it all together. The omission of a data integration strategy is the root cause of two harmful, potentially fatal, problems:
1) Data Consolidation is a Precursor to Customer-Centricity
In 2017, an estimated nine out of ten companies will compete on the customer experiences they deliver. It’s safe to say that you’re one of them. While you may claim to be a customer-centric organization, is your data customer-centric as well?
If Zappos doesn’t have the product their shoppers are searching for, they’ll take them to three competitors’ sites to help locate what they want. AirBnB’s algorithm centers around the customer experience by calculating listing quality, ease of booking and personal preferences in their search results. In both of these examples, the behavioral data intertwines with the marketing, sales, customer success data and beyond. This is the essence of truly customer-centric data.
Many teams work toward objectives that aim to enhance the customer experience. But, they rely on their siloed views of the customer to meet those objectives. And, to quote the great Abraham Lincoln, “a house divided against itself cannot stand.”
Patchwork data environments rarely speak with one another or integrate together. Teams can analyze the data made available to them within their own tech stack, but are unable to see how it impacts that of other departments and ultimately, the customer experience. Making the transition to customer-centricity is critically linked to data-centricity throughout the organization.
2) Precious Time Stolen from the Productivity Pool
Companies are spending significantly more time attempting to collect, move, store and optimize data than they are actually gaining insights from it. In fact, data professionals dedicate as much as 80 percent of their time just trying to make raw data usable. This doesn’t include other departments that also spend time trying to gain value from their data.
What if even a fraction of that time was returned to your business? Employees could focus on analyzing, asking questions and discovering new opportunities. Leveraging a solution that takes the manual labor out of data integration will free up the minds of your organization to focus on innovation rather than aggregation.
All issues and drawbacks aside, there are unexpected benefits of data consolidation that should be considered. Consolidated data acts as a precursor to innovation, insight, customer-centricity and knowledge sharing. Let me explain:
A Catalyst for Team Collaboration
In a survey conducted at the Global Leadership Summit in London, 34 percent of business leaders responded that by 2020, more than half of their company’s full-time workforce would be working remotely. This explains the popularity of cloud-based tools designed to enhance cross-company communication and collaboration such as Slack, Asana and Trello.
But, what tools are available for data collaboration? As workforces become more global than ever before, employees need the ability to collaborate on analytics as seamlessly as they communicate through Slack.
With data integrated accurately and holistically in one place, all corresponding details, touch points and facets become common knowledge. Any employee can analyze the customer experience, examining it from different perspectives, personas and vantage points. They can quickly optimize, measure impact and evaluate performance leveraging the minds of the entire organization.
Fueling a Culture of Transparency
Transparency is de rigeur in the “always-on” connected internet age. While companies embrace cultures of transparency in many organizational aspects, data transparency remains a largely unrecognized business priority. Data consolidation can act as the crux for fueling this type of transparency.
When I spoke with Derek Rey, the VP of Marketing and Business Development at CloudApp, he explained the impact they felt after integrating their data. “Everyone talks about “transparency” in their organizations. Consolidating our siloed data allowed us to realize a new level of this much sought after openness. Every department was able to see exactly how their actions impacted that of others. This brought a new level of collaboration and teamwork to CloudApp,” he said.
Developing an integration strategy and placing that data in the hands of every employee provides them with the necessary framework to inspire divergent thinking, make unexpected leaps and challenge the status quo.
The Next Frontier for Differentiation
Exceptional radiologists separate themselves from the average with their unique ability to identify what are called, “incidental findings.” These incidental findings are abnormalities, illuminated through a scan, revealing a problem the physician wasn’t initially seeking. The early diagnosis of an incidental finding can be life-altering, and in some cases, life-saving. But, without first taking the scan, the problem wouldn’t be identified.
In the same light, data consolidation helps employees to see new problems and ask questions that would have otherwise gone unnoticed. It delivers clarity, giving teams the ability to develop solutions that nobody previously imagined. They can compare, measure and test, exploring limitless solutions and possibilities. It’s in this environment that creativity flourishes.
Being data-driven in 2017 will not be about collecting as much information as possible, but rather, unifying that data in a way that is accessible, collaborative and transparent. The software that measures the ROI of a cup of coffee wouldn’t be possible without an integration to your CRM. Zappo’s unparalleled customer service would fall short without the merging of behavioral and marketing data. In thinking more about how these tools can intertwine, companies’ will discover missed opportunities and new ways that they can serve their customers.
As our insatiable appetite for data grows, so too will the need to master data centralization. Luckily, strategic resolutions like Woopra are more streamlined and less costly than ever before, and the benefits are too vast to ignore.