Developing analytic apps is a bold new direction for product teams. The Toolbox is where we talk development best practices, tips, tricks, and success stories to help you build the future of analytics and empower your users with the insights and actions they need.
What is the ultimate goal of using data internally at your organization? You probably answered something like “Make smarter, data-driven decisions.” That’s the goal for a lot of companies! But how will they accomplish this goal? Companies of all kinds are sitting on more data today than ever before, but business intelligence adoption remains low. To understand this problem, let’s take a quick look at the history of BI and then talk about the future: analytic apps.
Centralized reports were in-depth, but slow
Let’s go on a little journey through history that many of us have been on, starting with IT-focused “reports.” You or someone in your company needs some insights from your data stores, so you go to the IT team and ask for it. They put you on a backlog list, and at some point — maybe a few weeks or a few months later, you get a report. Now say you have another question, you go back again and wait some more. We all are familiar with this story and it’s not a good one!
Self-service BI began to empowering end-users
In order to solve this endless waiting game, the industry invented self-service BI which completely revolutionized how we interact with data. Self-service BI made it easier to combine multiple sources with a UI that included drag and drop, drill through, filter functions, and more. These tools are easy to use and users of all skill levels can find insights on their own and share them as well, without learning SQL or other languages. Self-service BI made huge inroads in making BI mainstream and more accessible. It continues to do so and is extremely relevant today.
But, even though for the last two decades — maybe even longer — “BI and Analytics” has been at the top of the technology agenda for most organizations with massive and increasing investments, pervasive BI adoption has continued to remain a challenge with organizations only seeing about 30% adoption (and in some studies up to 50% but still low).
Now, a hint at the underlying problem is that less than a third of organizations claim that they have fully connected this data effort to the actions that they take as a business. Just doubling down on traditional solutions that do not fix this gap between data and insights and actual actions is clearly not sustainable.
Combining actions and insights — the rise of analytic apps
This latest wave of actionable BI is the key to bridging the gap between insights and action by enabling users to act at the point of insight. This is one of the driving sentiments around our three new Sisense packages, for Product Teams, Cloud Data Teams, and Analytics and BI teams. All three groups have a mix of users with different needs, but all contribute to and/or profit from building analytic apps that connect insights and actions.
Organizations at the top of their industries are engaging in digital transformation strategies that go far beyond a drive toward efficiency and traditional BI practices. These organizations are completely changing the way they operate. They are focused on driving action within their organizations based on insights and on creating better partnerships with vendors and customers by delivering differentiated analytic apps, both inside and outside their organizations.
Actionable analytics, analytic apps, and embedded analytics will drive this third wave of BI. These are highly-interactive, action-oriented data experiences that co-exist seamlessly with existing applications and workflows.
Actionable analytics will lead to superior outcomes
What do we mean by analytic apps? Let’s take an example of an app we are all familiar with: Google Maps.
Google Maps is a quintessential example of a great app experience. Not only do we view data and metrics (directions, travel time, weather, etc.) but over the years, they have also added actions (making reservations, calling businesses, calling Ubers and so on) allowing for a seamless experience.
Do you remember how annoying it was to go OpenTable or Yelp or another website to take all those actions? Google Maps makes our workflow seamless from deciding where to go to making the reservations to finding directions and even hailing a cab — all without leaving the context of the application!
Why should analytics be any different? It is time to go beyond the dashboard and integrate analytics within workflows through actions to build a fully data-driven organization. Actionable BI is the key to increasing adoption and building a truly data-driven organization.
Analytic apps allow automation and the ability to act upon insights
Write-back for closed loops: Imagine that you are running an important space mission with critical metrics to track. It is a complex project and mission-critical project where you are tracking not just revenue and costs but also have to provide daily status updates and careful oversight.
An analytic app will enable you to provide these updates seamlessly within your workflow without requiring you to leave the context of your work. For example, you can edit data in a project management tool or you can or submit forms for the daily status update that goes to another application right within the analytic app. This removes friction and reduces the number of steps leading to better outcomes.
Integrate for seamless workflows: Analytic apps will allow you to integrate your analytics into third-party applications whether they are a communications app like Slack or Gmail or you’re sending data to an application like Salesforce or Gainsight, etc. to kick off a project or process. Or, in the case of Luzern, clients can track their market spend in a Sisense BloX actionable analytics widget, and dig into an individual ad’s performance. As they’re digging into performance metrics, they can mark it successful, put it on a watchlist, or pause it, all without leaving the analytics interface.
Feature-rich, interactive, and visually appealing: Analytic apps will allow you to purpose-build what your user needs or wants. It allows you bimodal integration — you’re not just embedding analytics into other applications or sending data there, but also bringing those applications into the analytics workflow. Last but not the least, analytic apps are customized to be aesthetically and visually pleasing, making your users more likely to actually enjoy using them (and thus, actually keep using them).
With analytic apps, users shouldn’t be able to tell where analytics end and operations start.
Former Sisenser Shruthi Panicker holds a BS in Computer Science as well as an MBA and has over a decade of experience in the technology world.