Personalizing Decision Intelligence with Augmented Analytics

Many executives, middle-managers, and frontline staff I speak with are caught in a decision-making conundrum. They want to make intelligent decisions based on data. But they are faced with a problem they can’t fix.

Analytics aren’t designed for them.

Executives are often presented with a report or a dashboard and need to decide on the next action. But they can’t do it themselves if they want to dig deeper to understand why one area of the business is performing differently than the others. They need to make a phone call to the BI expert who can help.  

Middle managers are highly motivated to dig into their data and make data-driven decisions. Still, they lack the technical knowledge to slice and dice the data in a way that enables them to better understand what’s happening in their business and why—and ultimately report up to their executive teams with confidence. They shouldn’t have to learn coding skills to do complex calculations to see the patterns in the data.  

And more than ever, frontline teams have access to vast amounts of data and have been entrusted with decision-making responsibilities. However, these individuals are business experts—not data experts—and it’s easy for them to be overwhelmed by the information at hand. They don’t need to see everything, nor should they spend inordinate time getting trained to be able to make sense of the data. What they really need are the golden nuggets to make timely, intelligent decisions independently in the areas of the business they manage.

Despite all the investments companies have made in data and analytics over the last decade, and despite all the “innovation” from well-known business intelligence vendors, decision-makers at all levels of an organization still struggle to identify and act on relevant insights from these BI tools.  

Let’s be honest, low adoption rates are one of the most painful and costly challenges for most BI and analytics leaders. It means their teams spend less time on morale-boosting and valuable revenue-generating work and more time on laborious, time-consuming, demoralizing one-off requests. What BI and analytics leaders want is to empower anyone in their organization to be self-sufficient.  

One significant barrier is keeping people from being data-driven: most BI tools don’t personalize the experience for those needing the data most. The context is often missing. It’s hidden behind overcomplicated UIs that don’t make sense for the 80 percent of users who need it most.  

A Tipping Point for Business Intelligence 

Augmented analytics has the potential to change the game. It is a transformative element of Pyramid’s Decision Intelligence Platform—a breakthrough innovation in analytics that combines all the power of data preparation, business analytics, and data science in a single platform with a point-and-click experience that makes all activities simpler for non-technical people.

While many vendors offer individual tools today, multiple tools can make personalization tricky. Pyramid offers a platform with a unified experience—driven by AI—that brings these capabilities together in one solution, streamlining the entire experience, simplifying personalization, and encouraging adoption. 

Augmented analytics encompasses artificial intelligence and machine learning functions that contribute to the adoption of data-driven decision-making. Analytics leaders can enable personalized, actionable data access for anyone in the organization, even those without a technical data background. 

When I say “personalizing” the experience in the context of augmented analytics, I’m talking about: 

1. tailoring the analytics experience by activating or deactivating business analytics capabilities based on role; 

2. tailoring access to governed data and activating data prep and data science capabilities; 

3. leveraging AI in a point-and-click UI that doesn’t require code; 

4. automating the delivery frequency and format of custom reports, interactive dashboards, visualizations, or alerts by role, or embedding them into the systems and applications people use to do their daily work so they can use data to make more intelligent decisions. 

The arrival of augmented analytics is as timely as it is critical. According to Forrester, only 1 in 5 organizations is using BI in any meaningful way today. A lack of personalization within BI platforms means business professionals simply aren’t using these tools in the ways they should or aren’t using them at all. 

BI and analytics leaders can use personalization to make decision intelligence something anyone can use, driving adoption beyond the people with technical skills. Personalizing the data-driven decision-making experience enables anyone to use data seamlessly within their existing processes and systems to aid their daily decisions. 

Why Personalized Decision Intelligence Is So Important 

First, we should highlight the core aspects of augmented analytics. Augmented analytics uses machine learning and artificial intelligence techniques to transform how analytics content is developed, consumed, and shared. With augmented capabilities, data and analytics leaders can truly personalize experiences for all types of people, many of whom will get value out of the organization’s data resources for the very first time. 

In this way, decision intelligence platforms can deliver the right kinds of insights to a spectrum of people within an organization. They use more consumer-friendly capabilities to make this possible, such as:  

• automated insights,  
• data storytelling, and  
• catalogs.  

AI and ML can also assist with data preparation, insight generation, model selection, and insight explanation. With these capabilities, people can acquire the information they need via governed self-service and can interact with the data in a way that seamlessly contributes to their daily decisions. 

Adapting Tech to Humans, Not the Other Way Around

In terms of strategic value, the Decision Intelligence Platform employs augmented analytics in a way that tailors the analytics environment to the individual—not the other way around. This represents a stark contrast to traditional BI, where countless hours and dollars have been spent forcing personnel to adapt to BI software.

The use of AI in augmented analytics means personalization itself is growing more sophisticated. Augmented analytics enables data leaders to “personalize BI beyond just ‘producer’ and ‘consumer’ personas,” as Forrester describes. In fact, Forrester identifies 12 different core activities and seven user personas that decision intelligence can support through augmented analytics. But use cases aren’t limited to those activities and personas alone, especially as augmented analytics evolves.

For example, imagine if your business leaders could get a one-click explanation of the drivers of last quarter’s performance in a particular region? Or if they could pull up a chatbot and type in basic conversational queries (ex., “Show this table as a bar chart.”) that change how the data is displayed. This “augmented” assistance lets them ask the right questions without having to know the underlying technical details—delivering an interactive experience that’s comfortable and familiar to them. 

The benefits of augmented analytics personalization are tantalizing for those running the whole BI infrastructure too. They can save vast amounts of time and reduce the backlog of one-off requests that technical BI and analytics teams struggle to get through. After all, spending much of their day responding to one-off requests from businesspeople isn’t the best use of their time. Imagine all the revenue-generating work they could be focused on if they got that time back!

The Business Benefits of Personalized Decision Intelligence 

In the best analytics environments, AI-driven guidance is everywhere—from modeling to discovery, visualization, and storytelling. In fact, there is a logical flow of consumer-friendly augmented analytics from the data source to the people consuming it.

In Gartner’s 2022 Critical Capabilities report, Pyramid Analytics’ Decision Intelligence Platform emerged as the category leader in augmented analytics. Here is a closer look at the AI-driven processes from the report that characterize augmented analytics and make this flow possible:

1. Natural language query: Businesspeople ask questions of their analytics tools using everyday language via typing or voice command. For example, an executive can use an NLQ Chat Bot to interact and investigate data directly from a dashboard without explicit knowledge of the underlying data structures, hierarchies, and measures. 

2. Automated insights: The platform identifies the most critical attributes within a dataset based on the query and then generates actionable insights for people who can leverage or repurpose it as they choose. For example, with a click of a button on a dashboard, a business manager can generate Smart Insights that contains a narrative analysis of their data that can be easily shared in a board report or a presentation. 

3. Natural language generation: The platform automatically creates “linguistically rich descriptions of insights found in data,” as Gartner describes. “Within the analytics context, as the user interacts with data, the narrative changes dynamically to explain key findings” or the meaning behind data visualizations. Imagine, with a point-and-click action, a frontline worker can Explain a complex data set with automatically generated textual commentary and visualizations.  

4. Data storytelling: The platform enables users to combine interactive data visualization with narrative techniques so that they can be packaged, repurposed, and shared with other decision-makers. For example, rather than picking through a massive table of contact and opportunity records, a marketing analyst can interact with a dashboard and generate narrative insights about the accounts most likely to convert. 

No matter the use case, augmented analytics can assist people with decision intelligence and even support the decisions of their colleagues with whom they share their findings. This puts into perspective the most exciting benefits of decision intelligence with augmented analytics— to drive personalization and therefore adoption of data-driven decision-making across the entire organization. 

Leading Our Decision Intelligence Future 

We are entering a world where analytics can serve the needs of anyone through their own personal discovery within a governed self-service environment tailored to their role. The current economic environment requires people in all parts of the organization to decide faster, respond faster, capitalize on opportunities faster and take corrective action faster. I believe in the next decade we’ll see a massive transformation in how companies scale to meet the analytic needs of their non-technical people. The organizations that will survive and thrive will have much higher adoption of data-driven decisions because they use decision intelligence with augmented analytics capabilities to enable personalized, interactive experiences. 

Pyramid Analytics, the Category Leader in Augmented Analytics 

In 2022, Pyramid Analytics became the category leader for augmented analytics in Gartner’s annual Critical Capabilities report. Contact one of our augmented analytics experts today to discover why global data and analytics leaders rely on Pyramid Analytics for their most comprehensive analytics initiatives.