Big data is now omnipresent. It is embedded into our day-to-day lives as the hard-wired DNA that fuels our business processes and decisions. Data-driven cultures went mainstream in 2016, with organizations scrambling to establish data strategies that enabled all employees to make better informed decisions. Yet despite all of the hype, the majority of organizations still have a long way to go before realizing the potential that big data holds.
A new report from the Mckinsey Global Institute, The age of analytics: Competing in a data-driven world, revealed, “most companies are capturing only a fraction of the potential value of data and analytics.” In an age where deeper, more meaningful insights have become a competitive necessity, it will be imperative in 2017 to embrace and fully utilize the data trends that will drive your organization into the future.
We’re predicting six technological advancements this year that will enable organizations to reach new levels of personalization, collaboration and synchronization.
1. Analytics Solutions Mature Into Collaboration Tools
With the rise of remote workforces and cross-continental teams, tools that enable seamless employee collaboration have saturated the software market. But, with all the new communication and project management solutions, data collaboration still takes place primarily within Excel spreadsheets or data scientist teams. In 2017, integrated analytics solutions will release features that allow departments to collaborate on data as effortlessly as they chat through Slack or comment on Quip.
2. Data is Democratized Throughout the Organization
For years, the ability to access data has been a privilege reserved for statisticians, business analysts, operations specialists and data scientists. Meanwhile, the rest of the organization was left with limited insight into metrics that reveal how their day-to-day activities impact business results. For those that considered some form of data analysis a necessity for success, they often had to suffice with taking a number and waiting patiently in the data breadline for an analyst to prioritize their request.
While most businesses have made massive strides in the availability of company data, 2017 will require that every employee be given access to at least some level of analytics. Solutions that empower teams will real-time, integrated data will be a prerequisite for businesses seeking to boost efficiency, responsiveness and information parity.
3. Predictive Analytics Go Mainstream
Predictive analytics were all the rage in 2016 yet, despite all the hype, the majority of businesses have yet to tap into the potential it holds. While comprehensive analytics solutions can provide insight into the current state of business, predictive analytics reveal the future. Leveraging existing, new and historical data, it forecasts future events, behaviors and trends.
The evolution and application of predictive analytics in 2017 will run in parallel with the progression of machine learning. By applying automated algorithms, organizations will be able to predict a specified persona’s likelihood to purchase, churn, champion their brand and more. Ultimately, allowing for greater optimization, highly-targeted messaging, a 360-degree view of customers and more accurate forecasting.
4. Less Time Collecting Data – More Time Acting On It
The CEO of Pneuron shared that, “70 percent of an enterprise project is spent identifying, aggregating, moving, storing and optimizing data before a single penny of value is created.” The sheer abundance of available information has imposed time-consuming processes that demand tremendous effort prior to gaining insights and value from data. But, 2017 will present a convergence of trends for the massively accumulating amounts of data and accelerated analytical methods that produce meaning from that data. Because of this, organization’s will be able to spend far less effort to collect and aggregate their data and more time gaining actionable insights from it.
5. Centralized Data Powers Hyper-Relevant Personalization
The number of actively analyzed data sources continues to grow and is projected to rise 83 percent by 2020. As a result, everything from sending a cup of coffee to making a phone call comes with its own set of corresponding analytics. While these sets of data can provide insight to individual teams, they sit siloed and segregated from one another. This leads to an incomplete view of the entire customer experience and the inability to personalize and optimize accordingly.
Recognizing this gap, organization’s in 2017 will seek to integrate their disparate data sources within a single platform. Customer profiles will map every touchpoint throughout the customer journey and present an interconnected web of experiences. This union of information will enable hyper-relevant personalization, at a global scale.
6. Machine Learning Emerges as the Brain for Complex Algorithms
Over the last few years, machine learning has made impressive strides forward. Even Google’s core search algorithm is harnessing the technology to improve overall search quality. But, like predictive analytics, very few tools have embraced the possibilities that machine learning has to offer.
According to Mark Kamlet, professor of economics and public policy for Heinz College at Carnegie Mellon University, ”the power and capabilities of machine learning will grow exponentially. We won’t be the Jetson’s in 2017, but the pace of the impact will not slow down.”
We should expect to see machine learning emerge to fuel everything from product recommendations and enhanced user experiences to conversion rate optimization. It will become the brain that powers the algorithms that feed predictive forecasting and will support the development of future AI and IoT platforms.
While it’s beneficial to maintain a pulse on emerging data trends, it’s just as important to focus on those that will deliver immediate impact for your business. Organizations can quickly be swept up in wanting the latest and greatest technology, while ignoring the implementation of a strategy that ties it all together.
According to IDC, 90 percent of the unstructured data is never analyzed. Building analytics into the DNA of your organization’s business processes will require the structuring, centralization and democratization of customer data. This should be the foundational element that all new trends build upon. In mastering this, you’ll be prepared to quickly blend new technological advancements into your structural makeup and will be poised for rapid disruption.