Need BI on the Fly? Self-Serve Analytics is the Next Frontier in Ad Hoc Reporting
Ushering in the New World of Self-Serve Analytics
For the past 20 years, every generation of Business Intelligence software has held the promise of self-serve analytics. When ad hoc reporting was launched several years ago, BI solution providers claimed this promise was finally fulfilled. However, the enterprise soon learned that ad hoc reports didn’t live up to the hype. Why? Because ad hoc reporting is too intimidating for the average business user. And that’s a problem. If your key stakeholders can’t access data in real-time to make critical business decisions, then you can’t run a data-driven organization. Today, thanks to advancements in artificial intelligence (AI), the challenge of self-serve BI has been solved. AI-powered self-serve analytics now puts deep business insights at users’ fingertips, regardless of their training or skill level. Let’s take a closer look at why ad hoc reporting is dead and explore the future of self-serve business intelligence.
Ad Hoc Reporting Has a Big Learning Curve
Theoretically, ad hoc reporting empowers users to generate their reports without burdening the IT department. It’s supposed to liberate users from the canned dashboards provided by IT, which constrain their ability to view a larger set of analytics or different datasets. However, in most companies, that’s not how it works. When users try to create a new ad hoc report, they’re confronted with too many choices. Here’s how a typical report is created after a user opens up the BI software dashboard:
- Usually, BI software presents the user with a blank screen, which is intimidating. To create a report, there’s a list of database column names that users need to drag and drop. Most business users have no clue about these names or how to use them.
- When it comes to reporting formats, users are also left in the lurch because they must choose whether to build a chart or other visual.
- Users have no idea about how to add calculations to this data—and these calculations are often the most important metrics within reports.
Ask most business users how this works for them, and they’ll often respond: “I find the white screen too intimidating.” In other words, most users don’t get very far before abandoning the ad hoc reporting process altogether.
Changing the Paradigm: Self-Serve Analytics
Advancements in AI have revolutionized the business reporting paradigm. All users need to do is ask their questions—without any manual effort or user training. This is what the future of self-serve analytics looks like: Analytics can be accessed from anywhere. When users want business insights, they’re no longer tethered to BI software. Thanks to embedded analytics, they can do it from anywhere—from within collaboration apps (e.g., Slack, Skype, Microsoft Teams), workflow apps (Salesforce, Veeva), and more.
- Users ask their ad hoc questions by simply clicking a button embedded in whichever app they’re currently using. Then, they can type their question—using natural language—in a search box. Or they can send their question via text message from their smartphone.
Analytics are scalable across every silo. While traditional ad hoc reporting solutions require days to analyze billions of records, AI-powered self-serve analytics can answer questions instantly. It’s intelligent enough to train itself on a company’s products, geographies, competitors, and more, which gives it unlimited scalability.
- Business intelligence is no longer trapped in silos, like sales, marketing, R&D, supply chain, and manufacturing. There’s a true single source of truth.
Analytics reports are automatically formatted using AI. AI-powered analytics delivers answers that are formatted in a way that makes the most sense for users. Whether it’s a bar chart, a line graph, or some other visual, the system is intelligent enough to generate the right visualizations on demand.
- Users simply pin each chart or visual onto a board to generate a self-serve ad hoc report.
With self-serve analytics, there is no blank screen in front of you. You are just asking questions and pinning visual answers, like line charts, to a pinboard. When you’re done, you can organize these visuals into a report and share it with others with just a few clicks. It's all accomplished in a matter of minutes.
Ad Hoc Analytics are Contextual
One of the biggest reasons that AI-powered self-serve analytics is a game-changer is that answers to ad hoc questions are contextual. Here’s an example from one of WhizAI’s pharmaceutical clients, which demonstrates how contextual answers speed up analytics for life sciences.
Instant access to pharmaceutical sales data
A sales manager is preparing for a meeting. He pulls up WhizAI on his browser and types a question in his dashboard: “Show me the sales trend for Lyprexl last year?” The answer instantly appears: The company sold five million units in 2020. Additionally, WhizAI automatically creates a line chart that displays sales trends by month. For additional details, he types: “Year over year change?” WhizAI contextually understands that he’s asking about 2019 compared to 2020, and it provides an answer comparing the two years. Now, he types “MOM” for month-over-month. Because 2020 is still in the context of his questions, WhizAI displays this data in a line chart, so he can understand it at a glance. Or, let’s say he wants to see sales trends for a particular territory. All he needs to do is type “Boston, MA” and the AI will understand he’s asking for all these analytics for this territory. When he’s finished, he can create a report by simply pinning each result to his dashboard’s sidebar. Then, he simply selects the pinned charts and hits “share.”
Get Answers to Important Business Questions in Real-Time
WhizAI’s AI-powered self-serve analytics is a game-changer for the life sciences sector. Our analytics solution is trained to intelligently understand your pharmaceutical business faster and better than other solutions. Because AI-powered analytics can understand complex business questions and deliver contextual responses instantly, ad hoc reporting is a thing of the past. Book a demo today.
Subscribe to our blog
People also viewed
Customer Centricity and Digital Experiences which are Redefining Pharma
It is no secret that the pharmaceutical industry has historically flourished from blockbuster products with substantial brand equity, favorable pricing
Awash in Data, Yet Starving for Insights? Transform Life Sciences Commercial Teams with Augmented Analytics
Personalized communication is something the HCPs have come to expect. To do that, pharma sales reps need to know their customers well. In order to know the customer well, they need data. Enterprise pharma companies, however, have many data resources and lots of data at their disposal. In fact, there is a data explosion. So what do you do?
Readiness of Augmented Analytics for Life Sciences Commercial Teams
Demand for smart, agile, and near-instant commercial analytics in Pharma is rising. More contextual, continuous, and connected data and analytics are required to respond to more complex and uncertain business decisions.
Adding Up Data Analytics Total Cost of Ownership (TCO) and How to Lower It
High data analytics expenditures don’t have to be a cost of doing business for life sciences companies. WhizAI lowers total cost of ownership (TCO) while making data insights more accessible to business users. Traditionally, data analytics TCO has been a significant expense for life sciences organizations.
Transforming Life Sciences Commercial Function with AI and Augmented Analytics
In this whitepaper, sponsored by WhizAl, Everest Group explores the business case and profound impact Al and Augmented Analytics can have on the life sciences commercial function across various use cases in Sales, Marketing, and Market Access. They examine what top pharma enterprises are looking for in an augmented analytics tool, a roadmap for how to get started, and a blueprint for adoption.
Augmented Analytics is “On the Rise” on Gartner’s 2022 Hype Cycle for Life Science Commercial Operations
The Gartner® 2022 Hype Cycle™ for Life Science Commercial Operations introduces a new category, Augmented Analytics, this year. WhizAI is listed as a sample vendor in the Augmented Analytics category in this Hype Cycle. This summary report covers the following highlights.
Why Domain Expertise Is Essential for Life Science Analytics
Domain expertise matters. Consider this: Enterprises choose transportation and logistics companies that have created the specific types of services they need. Businesses seek professional services with experience in their industries and look for consultants with good track records in their markets. However, remember that domain expertise benefits extend to analytics platforms, particularly those deployed for life sciences.