What Lies Ahead for Data and Analytics in 2017?

Rado Kotorov's picture
 By | January 05, 2017
in analytical culture, Booz Allen, business analytics, business benefits, Business Intelligence, business intelligence (BI), business outcomes, consumerization of analytics, Customer-facing, Data Access, Data Governance, data governance, data integration, Data Integrity, data products, Data Quality, Data Visualization, digitization, ETL, Expedia.com, In-Document Analytics, industry trends, InfoApps, InfoApps, information poor, Master Data Management, MDM (Master Data Management), monetized data, operational analytics, Operational Business Intelligence, operational decision-making, organizational behaviors, organizational cultures, organizational processes, pervasive analytics, Self-service, trusted data
January 05, 2017

Attend 5 Hot Trends in Data and Analytics, on January 10, where I will be discussing 2017 trends in more detail. Register here.

Each year, we deliberate where BI and analytics are taking us as the role of data becomes increasingly integral to businesses.

Where are we headed this year? 

The biggest shift will be a focus on business outcomes. It is no longer about new and cool technologies alone, but what business benefits are possible when the right technology is combined with the right organizational behaviors, processes, and cultures. Why this change in outlook? This brings me to Trend 1.

Trend 1: Building the new digital enterprise using automation. Industry 4.0, the latest industrial revolution, is becoming a reality with more than 50 percent of enterprises embracing digitization in new business and operational models. This is great news for business intelligence (BI) and analytics practitioners, as keys for Industry 4.0's success are trusted data, pervasive analytics, and building an analytical culture. This elevates BI and analytics to a strategic level in the enterprise, but it also puts the burden on practitioners to monetize data and analytics. No more analysis paralysis. The thinking will change to "analyze to monetize!"

How can we make this a reality with BI and analytics technologies? The next four trends are about enabling Trend 1.

Trend 2: Analytics in the digital culture revolution: democratizing BI for fact-based decision-making. Trend 2 is about operational analytics. We will have to convert all analysis into applications that support operational decision-making because profits and costs are made at the operations level. This requires a new approach. Booz Allen defines such applications as "data products." In the next phase of data products, the raw data and the analytics sources are hidden from the user because all he or she needs is to get the answers to inform decision-making. We call these products InfoApps™. They function like Expedia.com, a common web tool. On that site, users with no training can find all the answers they need to book a planned trip. Expedia democratizes booking by providing self-service advanced searches to people who have never been trained as travel agents. Similarly, operational users do not need to be trained as analysts in order to get the answers they need to make decisions.

Trend 3: Report consolidation: saving costs, improving BI adoption, and moving from reports to InfoApps. We have been drowning in data and reports. We call this "report rich, information poor." We have created a vicious cycle of reporting, rather than creating the right self-service for mass information consumers. This vicious cycle is the result of the push approach. Whenever a business user has a question, IT builds a new report. Users end up with hundreds of reports – so many that they can’t match the reports to their original questions. Why not move away from IT-centric reporting, and use the Expedia approach to consolidate excessive reports into a single, iterative InfoApp for users to find their own answers? Tools like Expedia provide access to thousands of data sources and data fields, produce hundreds of versions of reports on-demand, and require zero training. This winning methodology and approach for self-service is where analytics is headed.

Trend 4: The rise of customer-facing analytics: monetizing data and consumerizing analytics. The digital enterprise is not just about employees, it is also about building trust and loyalty with customers – and using analytics to do so. But this poses a question – how do you consumerize analytics? The answer is along the same lines as in the above trends: create data products that fit consumer needs. Think of the billions of statements that we send to consumers in PDF format. This leaves consumers powerless as they cannot analyze data in static PDFs. Why not enhance the document to create an interactive, analyzable, and sharable source of information? This is exactly what the trend toward in-document analytics does: it gives more power to consumers to analyze the data in each document in a self-service fashion – right there in the document without having to export or learn new tools.

Trend 5: Data management in the digital enterprise: master data management (MDM), data quality, and governance. Finally, there's no benefit to having data you can't trust. Hence, master data management (MDM), data governance, and data quality are must-haves for building trust and the digital culture. The greatest trend happening here is the realization that integration and extract, transform, and load (ETL) capabilities are foundational for the proper implementation of governance and MDM. The disciplines and the technologies are converging.

To learn more, please join me for our next webcast, 5 Hot Trends in Data and Analytics, on January 10, where I will be discussing 2017 trends in more detail.

Register here.