Company

Unveiling Sisu’s vision for Decision Intelligence

By Berit Hoffmann - September 28, 2021

When I joined Sisu over a year and half ago, I thought I was joining a data analytics company. And in some ways, I was. Our founder and CEO, Peter Bailis, started Sisu based on the insight that with the emergence of cloud data infrastructure – and the resulting exponential growth in the complexity of cloud data – the analytics layer needed a fundamental rewrite.

Peter’s insight about the need for a foundational shift in conventional analytics is arguably even more relevant now than it was when he started Sisu in 2018. But after spending the last few years immersed in how businesses leverage their data today and the biggest challenges they face, we’ve reached an even sharper realization about what’s missing in the current data ecosystem.

This realization is simple but striking: the world doesn’t need yet another analytics tool. It needs a platform to facilitate decision-making.

The actual problem to solve: Better decisions

In Sisu’s early days, we heard customers talk about problems like “we’re not fully leveraging all the data we have,” or “analyses take too long and too much manual work.” But in reality, those were pain points obscuring a more critical underlying need. When we dug deeper, the actual problem people wanted to solve was using their data to make better, higher confidence decisions.

Specifically, we realized that better analysis capabilities are necessary but not sufficient in solving the problem of making better decisions with data. So we began researching not just the steps of data analysis but instead the entire decision-making process. And we quickly realized what we needed to solve for was a multi-step, multi-user workflow.

As an example, we met with an analyst at a company already using Sisu to diagnose why their key metrics were changing. As the user walked us through their workflow, we observed they were creating manual pivots and basic visualizations in their traditional BI tool to decide where to dig in, moving to Sisu for the deeper, comprehensive diagnosis they couldn’t get from their existing BI product, then going back to the BI tool to create charts summarizing their findings for other stakeholders. Needless to say, this struck us as painful and inefficient, and we knew there was a bigger opportunity to streamline the workflow.

The solution vision: Decision Intelligence

Building on our thesis that the real problem to solve is facilitating a multi-step, multi-user decision-making workflow, we developed a vision for a product experience that brings together multiple users in collaboration around multiple types of cloud-scale analysis capabilities so they can make the best possible decision. We call this a Decision Intelligence Engine.

To be successful in executing this vision, we believe a Decision Intelligence Engine must solve three key challenges:

    1. Address all types of questions
      Establishing confidence in decisions requires asking many types of questions, so a Decision Intelligence Engine must enable users to answer all of them.
      This includes understanding “what” happened to their metrics, diagnosing “why” it happened, and deciding “now what” to do in response. Legacy BI products focus primarily on “what,” yet in data-forward organizations, much more time goes into answering the more difficult “why” and “now what” questions.
      We found traction with Sisu by addressing the market gap around answering “why.” We’re now feeling the pull from our customers to address “what” and “now what” all within Sisu as well.
      Today, we took a big step in this direction by launching Explorations and Dashboards, which bring the “what” and “why” together in Sisu with seamless handoffs between them.
    2. Facilitate fast iteration
      Decision-making is not a linear path, so a Decision Intelligence Engine must empower users to iterate efficiently and in real time.
      “What” questions raise “why” questions, which in turn raise more “what” questions, and so on. This iteration is not only inevitable; it is critical to developing strong conviction for a given decision. Yet traditional dashboards make drilldowns and iterative exploration slow and painful.
      Going forward, Decision Intelligence must elevate fast iteration as a first-class citizen in the product experience. At Sisu, we’ve invested heavily in both a user experience and analytics engine that enable users to initiate and run follow-on analyses or drilldowns in seconds.
    3. Enable everyone to collaborate
      Making and executing the best decisions requires participation and alignment across teams of people, so a Decision Intelligence Engine must uphold multi-user collaboration as a core part of the product experience.
      This means meeting both decision enablers and decision makers where and how they already work so they can easily review and discuss data insights together. Products like Figma, G Suite, and Slack have shown us that the right product experiences can actually drive culture changes in how teams work with each other.
      We won’t deliver on the full potential of Decision Intelligence until we realize a similar level of seamless collaboration around data-driven decision-making.

We know there’s still work to be done to bring our vision to fruition. But today’s launch is a major milestone along the path. And backed by the resources and investor support from our Series C, as well as strong momentum from our growing customer base, we’re excited and committed to delivering the future of Decision Intelligence.

To learn more about how data-forward organizations can use Sisu, please join us for our webinar “Exploring, analyzing, and sharing data at cloud scale.


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