White Paper

BY WAYNE W. ECKERSON

AUGUST 2021

Actionable Intelligence The Next Frontier in Business Intelligence

RESEARCH SPONSORED BY DOMO

THIS PUBLICATION MAY NOT BE REPRODUCED OR DISTRIBUTED WITHOUT ECKERSON GROUP’S PRIOR PERMISSION.

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About the Author Wayne W. Eckerson is an international thought leader in the data and analytics field since the early 1990s. He is a noted speaker, sought-after consultant, and widely read author. Eckerson has conducted groundbreaking research studies, chaired numerous conferences, and consulted with numerous organizations around the world during his 25 years in the field. Eckerson has also written two books: The Secrets of Analytical Leaders: Insights from Information Insiders (2012)

and Performance Dashboards: Measuring, Monitoring, and Managing Your Business (2005/2010) He has degrees from Williams College and Wesleyan University.

About Eckerson GroupEckerson Group is a global research and consulting firm that helps organizations get more value from data. Our experts think critically, write clearly, and present persuasively about data analytics. They specialize in data strategy, data architecture, self-service analytics, master data management, data governance, and data science. Organizations rely on us to demystify data and analytics and develop business-driven strategies that harness the power of data. Learn what Eckerson Group can do for you!

About This ReportResearch for this report comes primarily from numerous briefings with software vendors. This report is sponsored by Domo, who has exclusive permission to syndicate its content.

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Table of Contents

Executive Summary ......................................................................................................................................................................... 4

The Rise of Actionable Intelligence .............................................................................................................................................. 6

Actionable Intelligence Strategies ................................................................................................................................................ 7

Recommendations: From BI to Actionable Intelligence ....................................................................................................... 16

About Eckerson Group ................................................................................................................................................................. 18

About the Sponsor ........................................................................................................................................................................ 19

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Executive Summary Contrary to popular opinion, data is not an end in itself, nor is analytics. Their purpose is to support profitable business actions: minimize stockouts, avert churn, fix products before they break, alter a product mix or design as customer interests change, and so on. The next frontier in business intelligence is to turn data and insights into action that drives business value. This is the definition of actionable intelligence, and business intelligence (BI) vendors are working feverishly to help their customers achieve this goal.

Every organization needs a robust business intelligence platform to monitor, measure, and manage past performance to determine whether it’s on track to achieve its goals. However, past or historical information is not “actionable”. By the time a report is delivered, it’s too late to change the outcome. Organizations now want BI platforms that empower business users with information so they can take constructive action while there is still time to change an outcome.

This report describes three major strategies employed by BI vendors to support actionable intelligence. One strategy accelerates access to data so users can analyze and act faster; another automatically generates insights so users don’t have to; and the third triggers actions, allowing machines to augment or automate human decisions. Within these three strategies, there are ten technologies that BI vendors are employing to help companies turn data and insights into action:

Accelerate Data

1. Federated Queries. The ability to capture up-to-date data from any source.

2. Embedded BI. Tools that make it easy to embed analytics into operational and other run-the-business applications.

3. HyperIntelligence. The ability to surface insights by hovering over text or charts in web pages and applications.

4. Custom Apps. Through software development kits (SDKs) and application programming interfaces (APIs), BI vendors empower developers to build applications that blend operations and analytics into a single user-driven workflow.

Accelerate Insights

5. Automated Insights. Tools that automatically run correlations against dashboards and query results to supply additional insights and recommendations in real-time.

6. Business Monitoring. Tools that automatically monitor tens of thousands of combinations of business metrics to detect anomalies, identify relevant correlations, suggest root causes, and recommend actions.

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7. AutoML. These tools help business users generate analytical models that identify patterns that can be used to optimize business processes.

Trigger Actions

8. Scripted Transactions. Technology that enables BI tools to update transaction systems and close the loop between analytics and actions.

9. Automated Writebacks. BI technology that moves the output of SQL queries into one or more operational applications without the need to write scripts or work directly with APIs.

10. APA. Analytics processing automation uses a single, integrated platform to create, manage, and automate data pipelines and the delivery of custom apps.

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The Rise of Actionable IntelligenceThe purpose of business intelligence (BI) is to “turn data and insights into action”—a process that experts call actionable intelligence. This BI mantra, which was once a pipedream, is now becoming reality.

The Last Mile of BI. Actionable intelligence closes the “last mile” of BI. In the early days, we gave users data and BI tools and called it quits. We assumed business people knew how to turn data and insights into value, but we’ve discovered that’s not always true. Then, the size of BI deployments and license costs grew and business leaders began expecting more value from their BI investments. Today, BI vendors recognize that delivering data and insights is no longer enough; they must help customers turn insights into action that drives business value.

From Decisions to Value. In the BI world, action equates with “decisions”. This is why BI tools were once known as decision support systems (DSS). Yet, a decision by itself doesn’t generate value; it’s the action that follows a decision that matters. The action can be swift: “Order new supplies to avoid a stockout”; or slow: “Reengineer this business process to improve efficiencies and lower costs”; or somewhere in between: “Reduce prices by 10% to increase demand and grow revenues.” Actionable intelligence uses data and insights to drive decisions with measurable outcomes.

Actionable intelligence is when data and insights lead to decisions with measurable outcomes.

Our consulting clients universally recognize the importance of delivering actionable intelligence. For example, a global manufacturing company wants to arm its sales force with predictive data that identifies customers likely to churn in 2 or 3 months while there is still time to turn them around. A university wants to develop a data-driven application that helps students select majors, co-ops, and global programs before they’ve invested valuable time and money. A financial services company wants automated alerts whenever a change in regulations affect their compliance policies with recommendations for changes.

Intelligent Machines. Machine learning plays a large role in actionable intelligence. Until recently, we never thought a machine could replicate human decision making. But now we have infobots, autonomous cars, computerized trading, and hundreds of other intelligent devices that take innumerable actions based on data inputs. Companies now use these AI-driven systems to manage and optimize every business process and augment or automate actions.

Some of these AI-powered machines augment human decisions by generating recommendations that humans can either accept or reject. Many financial services firms use fraud detection systems that capture potentially fraudulent transactions in real-time for a human to verify. Others automate

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those decisions, especially in processes where inputs and outputs are well-known and the scale is too large for humans to contribute in a meaningful way. For example, e-commerce companies use online recommendation engines to automate cross-sell and upsell offers at the point of purchase.

Some AI-powered machines augment human decisions… while others automate them.

Role of BI? Unfortunately, these AI-powered applications typically require teams of data scientists to build, evolve, and maintain an army of architects and engineers to support. So, where does this leave the everyday business user who needs to analyze and act on data? Can an executive, manager, or front-line worker use a BI tool to accelerate insights, make effective decisions, and take action that delivers tangible business value? Can companies transform their reports and dashboards into augmented or autonomous intelligence systems? In short, can BI tools support actionable intelligence?

Actionable Intelligence StrategiesBI vendors have made great strides in the last 30 years. They’ve made it simple to create and consume reports and dashboards; they’ve made it easier to find, prepare, clean, and manage data; they’ve embedded their output and functionality in other applications via APIs; and recently, they’ve infused their products with AI. But can the next generation of BI tools reach the pinnacle of analytics and deliver actionable intelligence?

Three Strategies. BI vendors are pursuing three strategies for implementing actionable intelligence. Not surprisingly, they mirror the BI mantra (“turn data into insights and action”). The first strategy accelerates data, the second automates insights, and the third triggers actions. Today, most BI vendors accelerate data, some automate insights, and a few trigger actions. Within these three strategies are ten technologies or approaches for delivering actionable intelligence. (See figure 1.)

Enterprise Suites. Although no BI product supports all ten capabilities, some BI vendors are now part of larger software organizations whose product lines encompass both operational and analytical functionality. For example, Infor embeds Infor Birst, its unified data and analytics platform, within its suite of operational applications (e.g., ERP, financial, human resources, risk). It also pairs Infor Birst with other functional applications, such as Infor Coleman, which offers AutoML and robotic process automation (RPA), and Infor Mongoose, which offers custom apps via low code/no code capabilities.

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Figure 1. Actionable Intelligence Framework for BI Tools

© Eckerson Group 2020 Twitter: @eckersongroup

Embedded BI

HyperIntelligence

Assisted Insights

Business Monitoring

AutoML

Scripted Transactions

Accelerate Data Trigger Actions

Federated Queries

Custom Apps

Automate Insights

APA

Business Value

Automated Writeback

Accelerate Data One way to deliver actionable intelligence is to shorten the distance between data and action. If tools can deliver data faster, people can react more quickly to events, improving their chances of converting data into business value. Fast access to data is a cornerstone of actionable intelligence.

Fast access to data is a cornerstone of actionable intelligence.

Federated queries. Many BI tools can query multiple source systems directly, rather than a data warehouse, and join results on the fly. This enables business users to get the freshest data possible and take action quickly. Federated queries mimic a data warehouse but without the expense and time required to model, transform, and load data into a physical repository. In this way, federated queries shorten the distance between data and action.

Reporting vendors, such as Information Builders (now owned by Tibco) and Actuate (now owned by OpenText), were the first BI vendors to query source systems directly and federate queries across systems. Cloud BI vendors, such as Domo, Infor Birst, and Zoomdata (now Logi Analytics Composer) support query federation, largely out of necessity since most customers can’t put all their data in a cloud repository. Federation offers a convenient exit ramp for off-cloud queries.

Today, there is such high demand for near-real-time data that most BI vendors support federated queries, including Tableau, Yellowfin, and MicroStrategy. There is also an emerging class of SQL data lake products, both open source and commercial, that support federated queries, including Amazon Athena, Apache Presto, Starburst, and Dremio. And new self-service workbenches from Promethium, DataClarity, and Knowi rely heavily on data virtualization engines to find, connect, profile, query, and prepare data

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wherever it resides in the organization. Data virtualization builds a semantic layer on top of a query federation engine to create a unified view of disparate data sources.

Embedded BI. Another way to accelerate data is to move BI output closer to the action. BI vendors do this by embedding charts, tables, and analytic functions inside other applications, such as operational systems or internal or customer-facing portals. Embedding insights into run-the-business applications blends analytics and operations in a seamless way and eliminates the need for operational workers to toggle between two applications. While federated queries shorten the distance between data and action, embedded BI shortens the distance between insights and action.

Another way to deliver actionable intelligence is to move BI output closer to the action.

There are many levels of embedded analytics. The most basic is to generate “embed” code—or HTML snippets—that customers can use to embed static charts or tables into an iFrame on a web page. Another approach is to programmatically execute BI functions through a client-side (e.g., Javascript) or server-side (e.g., RESTful) application programming interface (API). This enables customers to add “live” or interactive charts, tables, and reports inside applications.

Embedded analytics is a huge new market for BI tools, fueled by the growing number of software-as-a-service (SaaS) vendors and traditional enterprises that want to monetize data. Some BI vendors only sell to the embedded market, including Exago, Izenda, and Logi Analytics1. Others have a built-in market with their parent companies. For example, Infor Birst, SAP BusinessObjects, Tableau CRM (Salesforce), and Oracle Analytics are embedded within their companies’ enterprise software applications, creating an environment that seamlessly blends operations and analytics.

Custom Apps. A third approach to embedding is to offer a GUI-based development platform that makes it easy to build custom applications that blend operational and analytical components. For instance, a customer might build a mobile app that schedules a salesperson’s daily visits to customers based on their location and likelihood to buy and gives them one-click access to customer history. These one-off applications enable companies to reengineer and optimize business processes and can give them a competitive edge. Consequently, many BI vendors, including Qlik, Domo, SiSense, SAP, Oracle, and Alteryx, now devote considerable resources to software developers who want to build blended applications. (See figure 2.)

1 To evaluate embedded BI products, read our report, “Which Embedded Analytics Product is Right for You?”

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Figure 2. Custom Analytic App from Domo

HyperIntelligence. MicroStrategy takes a unique approach to embedded analytics. Rather than embedding a chart, table, or dashboard, it embeds hyperlinks into text and tables inside web pages and applications. Clicking a link pops up a custom card that contains summary information about the highlighted data element. (See figure 3.) HyperIntelligence is ideal for sales and operations workers who need split-second access to contextual information to close a sale or fix a problem.

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Figure 3. Pop-Up Insights via MicroStrategy

Automate InsightsDelivering faster access to data is important, but it still requires humans to view and explore data, interpret the results, and generate insights before they can take action. However, a new crop of AI-powered BI tools automatically generates insights, filters the results, and presents users with actionable facts or alerts. These tools provide the same benefit as adding a dozen or more analysts, and they make existing analysts more productive by surfacing fruitful avenues for discovery.

These tools provide the same benefit as adding a dozen or more analysts.

Assisted Insights. Following the lead of ThoughtSpot, SAP, Oracle, Qlik, and Yellowfin, most BI tools now run algorithms in the background when users click on or hover over a metric within a chart or dashboard. The algorithms surface significant trends, anomalies, and correlations associated with that metric and present the most pertinent findings using natural language text. These features simulate what a business analyst might discover if asked to explore an issue. (See figure 4.)

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Figure 4. Assisted Insights with ThoughtSpot’s SpotIQ

Business Monitoring. Business monitoring systems work the same way as assisted analytics, but on a much larger scale and in a more automated fashion. Business monitoring tools are intelligent alerting and learning systems that run continuously on large volumes of business data. They detect anomalies, trends, and correlations across hundreds of thousands or millions of business metrics and present only the most relevant insights to individuals using simple text and visuals. (See figure 5.)

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Figure 5. Business Monitoring Alert from Anodot

Most business monitoring systems supplement insights with suggested root causes, which are usually strong correlations with the observed behavior. Many are planning to supplement their systems with better root cause analysis, predictions, and automated actions. (See next section.) By detecting subtle changes in the business before they mushroom out of control, business monitor systems reduce operational expenditures, improve customer experiences, and protect revenue. Business monitoring vendors include Anodot, Sisu, Outlier, Yellowfin, SAP, and ThoughtSpot.

AutoML. Automated Machine Learning (AutoML) abstracts the complexity of building, training, and running models so non-data scientists can apply the power of AI to everyday business problems. Although companies use traditional data science tools to build mission-critical systems, such as recommendation engines and fraud detections systems, they employ AutoML tools for the “masses” so they can apply machine learning to less complex problems. Over time, however, we expect AutoML tools to take over more AI/ML development within an organization.

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Over time, we expect AutoML tools to take over more AI/ML development within an organization.

Many companies embed AutoML models into BI reports and dashboards to deliver actionable information. For instance, a customer sales report might contain an attrition score, giving salespeople actionable intelligence on which customers to call in what order. Several BI vendors, including Pyramid Analytics, Alteryx, Oracle, Salesforce (Einstein Discovery), and SAP, have added AutoML to their BI products, while other vendors can import and run models created externally in other languages and tools. Many BI vendors partner with stand-alone AutoML vendors, including DataRobot, H2O, Big Squid, and cloud platform vendors (Microsoft, Amazon, and Google) to integrate advanced analytics.

Trigger ActionsAugmented Intelligence. By definition, BI tools facilitate decisions and don’t automate them. However, as BI tools incorporate more AI capabilities, they will become smarter; instead of delivering data or insights, they’ll generate recommendations that users can accept, reject, or modify. This is augmented intelligence, and it’s a fast-growing area of BI and analytics. Augmented intelligence is a steppingstone to autonomous intelligence where users trust machines to make decisions on their own without human intervention.

As BI tools… become smarter… they’ll generate recommendations that users can accept, reject, or modify.

Transaction Services. However, even before the advent of AI, some BI vendors introduced plug-ins so customers could write parameterized scripts to update a remote database, generate an alert, or take some other action. For example, a script might say, “If inventory for Brand X sneakers falls below 150 units, send a message to the purchasing system to order 50 more pairs.” MicroStrategy was one of the first BI vendors to offer a BI transaction service but others have followed suit, including Domo. Application suite vendors, such as SAP, Oracle, and Infor have made bidirectional updates between analytical and operational applications a core differentiator.

Automated Writeback. Most data flows into data warehouses and BI tools, not the other way around. Automated writeback (also known as reverse ETL or AnalyticsOps) reverses the flow of data: it takes the output of SQL queries from a BI tool that are executed in a data warehouse and moves it into one or more operational applications, such as Salesforce and HubSpot, or productivity applications, such as Excel, Slack, or Google Analytics.

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ThoughtSpot and Qlik are the first BI vendors to embrace this concept thanks to recent acquisition, Thoughtspot of SeekWell and Qlik of Blendr.io. Both automate integration with dozens of operational applications. Unlike transaction services, automated writeback doesn’t require developers to write scripts to load data into one or more source systems, or work with APIs; automated writeback maintains connections to all source systems. So far, automated writeback is suited to adding data to source systems rather than updating existing fields. (See figure 6.)

Figure 6. Automated Writeback via SeekWell

Automated Actions. Business monitoring vendors with their AI-driven monitoring tools are well-positioned to support both augmented and autonomous intelligence. For instance, Anodot is instrumenting algorithms to support automated actions in the near future, such as the ability to automatically deactivate a cloud server to save costs. Customers will only apply automated actions to business processes that are well-understood, repeatable, and have straightforward remediation steps. Before deploying into production, humans will need to validate the machine’s recommendations (i.e., augmented intelligence) for a period of time to gain confidence that the machine will make the right decisions (i.e., autonomous intelligence).

AutoML APIs. Most AutoML products, including those embedded in BI tools, have APIs that enable customers to run the models programmatically to support a smart application, such as a recommendation engine or automated forecast. For example, rather than rebuild a forecast or plan each new period, they use AutoML APIs to automatically to re-score the metrics when new data arrives and retrain the models if data drift is detected. Programmatically activating analytical models is a prominent way that organizations implement actionable intelligence.

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APA. Analytics process automation (APA) is the newest term to describe technologies that design, build, monitor, and automate data pipelines. With the growth and variety of data sources and applications for data and analytics, data pipelines have become increasingly complex. Many now incorporate ML/AI models that automate actions and responses, closing the loop between data, insights, and action.

As such, they’ve become mission critical and BI vendors have taken note. Many have extended their analytics platforms to support data management functions so they can source, clean, transform, combine, and deliver data to a target destination and incorporate analytical models to support actionable intelligence. BI vendors, such as Alteryx, Qlik, Pyramid Analytics, Sisense, SAP, Incorta, Domo, and Zaloni, provide a unified data and analytics platform that makes it easy to create and manage data pipelines to support custom analytics applications. (See figure 7.)

Figure 7. APA Diagram from Alteryx

Recommendations: From BI to Actionable IntelligenceBusiness people have used BI tools to gather data, generate insights, and take action for decades. It’s just that once technology delivered data, humans took over. They connected the dots, generated insights, made decisions, and took action. Unfortunately, most business users don’t finish the cycle and BI tools are often left shouldering the blame. The handoff between technology and humans reminds me of that

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famous Sidney Harris cartoon of two scientists at a blackboard reviewing a step in a complex scientific formula that reads: “Then a miracle occurs.”

Today, BI vendors are working feverishly to help customers get more value from their BI tools by closing the distance between data, insights, and actions. Most BI tools accelerate data by supporting federated queries, embedding analytics inside operational applications, and creating applications that blend operational and analytical elements. Others close the gap by using AI to automatically generate insights from large volumes of business data and present them in user friendly analytic applications. Still others trigger actions through hard-wired or intelligently generated scripts, programmatic execution of ML/AI models, and automated pipelines that support custom applications.

RecommendationsAlthough it may take a decade or more for actionable intelligence to take root, it’s clear that BI vendors are intent on making good on the promise of helping their customers get more value from their tools and data. To help your company achieve the promise of actionable intelligence, follow these recommendations:

1. Federate. Give your business analysts and data scientists self-service analytics workbenches that incorporate a federated query engine that enables them to connect to any data anywhere so they can quickly generate insights the business needs.

2. Embed. Shorten the distance between insights and actions by embedding analytics into operational applications where business users spend most of their time and implement decisions.

3. Develop. Place a software developer on your BI or data team and give them free reign to use APIs, SDKs, and development platforms offered by BI vendors to build run-your-business applications that blend analytical and operational elements.

4. Generate. Encourage your business analysts to leverage assisted insights features and business monitoring systems to do the heavy lifting of sifting through millions of metrics to find relevant trends, correlations, and anomalies. This will make them infinitely more productive.

5. Automate. Leverage APA or DataOps tools to automate data pipelines that incorporate the output of AutoML or ML/AI tools. The result can be truly powerful augmented or autonomous intelligence applications.

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About Eckerson GroupWayne Eckerson, a globally-known author, speaker, and consultant, formed Eckerson Group to help organizations get more value from data and analytics. His goal is to provide organizations with expert guidance during every step of their data and analytics journey.

Eckerson Group helps organizations in three ways:

> Our thought leaders publish practical, compelling content that keeps data analytics leaders abreast of the latest trends, techniques, and tools in the field.

> Our consultants listen carefully, think deeply, and craft tailored solutions that translate business requirements into compelling strategies and solutions.

> Our advisors provide one-on-one coaching and mentoring to data leaders and help software vendors develop go-to-market strategies.

Eckerson Group is a global research and consulting firm that focuses solely on data and analytics. Our experts specialize in data governance, self-service analytics, data architecture, data science, data management, and business intelligence.

Our clients say we are hard-working, insightful, and humble. It all stems from our love of data and our desire to help organizations turn insights into action. We are a family of continuous learners, interpreting the world of data and analytics for you.

Get more value from your data. Put an expert on your side. Learn what Eckerson Group can do for you!

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About the SponsorDomo delivers a modern BI platform that helps organizations better integrate, interpret, and use data to drive informed decision-making and action across the entire business. With more than 1,000 pre-built connectors to simplify integration with existing technology, Domo takes BI-critical processes that previously took weeks, months, or more, and completes them on the fly, in minutes or seconds, and at an unbelievable scale. Domo works with many of the world’s leading and most progressive brands across multiple industries including retail, media and entertainment, manufacturing, finance, and more. For more information about Domo (Nasdaq: DOMO), visit www.domo.com. You can also follow Domo on Twitter, Facebook, and LinkedIn.