Gartner estimates that by 2020 more than 50 percent of major new business processes and systems will incorporate the IoT and that there will be more than 35 billion things connected to the internet. The connected enterprise has tremendous business potential; by mining IoT data, organizations can identify new ways to drive operational efficiencies, capture new revenue opportunities and improve the customer experience. However, companies must ensure that their information management strategy can support the data deluge fueled in part by the IoT and other emerging innovations.
The ramifications of an incomplete or poorly executed business intelligence program can cripple even the most successful of organizations – running the gamut from inadequate customer care and inaccurate operational insights, to business-critical errors impacting the C-suite.
The key to truly capitalizing on IoT data is a well-established, integrated information management strategy. In this slideshow, Information Builders shares four considerations underpinning the “golden rule” for data analytics success – harmonize, visualize, operationalize and monetize – as well as tips for avoiding common missteps.
Building Data Analytics Success
Click through for four factors organizations need to consider to drive data analytics success, as well as tips for avoiding common mistakes, as identified by Information Builders.
Organizations need to harmonize all critical data assets, including Big Data from sensors and other IoT devices, to ensure that the business has simplified access to trusted data. The first step is to put a system in place to integrate data and ensure its integrity. Take stock of data and where it’s stored, including customer data warehouses, CRM platforms, financial systems, public internet data, etc. And, don’t forget to include unstructured data sources such as social media, location, mobile and machine generated/IoT data. (An estimated two-thirds of unstructured data sources are not being used for strategic decisions making.) Ultimately, this data should then be brought together physically or virtually and be cleansed to ensure accuracy and completeness.
The holy grail of harmonizing data, however, is developing a master data management (MDM) strategy. MDM extends beyond tactical data quality to ensure consistency of data values as well as allow the organization to get a 360-degree view of their customers, partners, and operations.
Nearly 60 percent of organizations consider their data to be unreliable, which doesn’t bode well for extracting any value from BI and analytics. As trite as the saying may be: junk in, junk out.
If data isn’t integrated, various departments operate in a vacuum, drawing conclusions based on incomplete or different data. Have you or your cohorts ever presented different answers to the same question at a meeting, then spent hours trying to justify your information? If information is harmonized across the organization, business leaders can eliminate hours of data reconciliation and tracking data lineage and, instead, focus on executing strategic initiatives.
An organization with harmonized data doesn’t reap measurable benefits until they can “see” what it’s revealing about the business. Organizations should visualize their data, empowering users to identify trends, risks and opportunities. Data visualizations enable end users with limited experience in analytics to process and take action on information – a key driver for the rise in self-service analytics.
Software is becoming smarter, helping front-line employees gain insights from data without dependence on highly skilled data scientists for reporting requirements. This is particularly valuable for smaller organizations that may not have the budget for an in-house data scientist. It’s crucial, however, that IT collaborate with the various user groups and their respective departments to create strong data analytics and governance policies.
A pretty picture is great but if it doesn’t present information that is useful and easy for the end user to digest then it’s unlikely to be adopted. When designing visualizations consider these context questions first:
- Who cares about this data?
- How will they use this data?
- Do these stakeholders all use the same language when talking about this information?
Context is key. The visualizations built for the C-Suite will likely differ from a shipping specialist as it should showcase the information that impacts their jobs.
Now, give everyone the power to see clearly. The value of data is made greater by the number of people who have access to it. Don’t limit data access to the C-suite, business analysts and managers. Extend your data ecosystem to the front line by equipping every employee to make data-driven decisions on the job.
Note: One mistake that organizations often make is providing analytical tools – essentially a blank slate – that can seem overwhelming to business users with little or no experience in analyzing data. Tools can provide quick answers to operational questions, but BI and analytics adoption is still only typically 22 percent. To truly operationalize insights, a BI strategy should include the implementation of a comprehensive environment that delivers insight, but also goes one step further by empowering users to act on that insight to create impact. One way this can be accomplished is through the use of precise, super-focused BI apps and content that enable continuous monitoring of key metrics and indicators.
The final and most important keystone in the “golden rule” for IoT — and all — data analytics success involves extending access to data beyond the firewall to customers and partners. For partners, this means providing them with insights that help them to better serve your organization and your customers by identifying opportunities to reduce costs, provide new services or streamline operations.
Savvy organizations know that the battle for customer loyalty is won online. Analytics-rich and highly interactive web applications and interactive e-statements will become crucial tools for improving the customer experience. In fact, Gartner predicts that the next three years will see dramatic growth in customer-facing analytics – and for good reasons. Insights on market trends and performance against cohorts are just two examples of how data can fuel new sales, cross-sell or upsell products and services.
The onslaught of data isn’t going to slowdown. As sensors, automation, RFID, and other digital technologies are increasingly embedded in processes, it will become even more crucial that organizations not only capture, but also understand their data and its underlying trends. Those that can master data’s “golden rule” will be prepared to harness the data explosion to become more competitive and profitable.