How Augmented analytics can give better root cause insights over traditional dashboards?

Legacy data analytics products offer reports and dashboards that simply report past data. For everyday business users, understanding “what” is happening in the business is important but not enough. Time and again, we hear from business users that they have too many reports and dashboards but no actionable insights. It is very challenging to understand root cause or “why” analysis using the legacy data analytics products.

Users are tired of limited reports. They want to understand “why” their metrics changed. In other words, they’re looking for the “root causes” of changes in important business metrics.

Understanding “why” is the holy grail of finding actionable insights from data in real-time. No user can make tactical or strategic decisions without knowing which factors affected business changes. Legacy data analytics products do not offer these capabilities and offline manual analysis requires too much time and resources. Oftentimes, business situations change by the time users are able to find critical answers.

Recently, some software products have attempted to solve this “why” problem. However, they all require deep technical training and only solve only one use case as a point solution. As a result, these solutions fail to get traction at the business user level, where actual business impact decisions are made. This causes a lot of frustration for business users as they must use multiple platforms for various analytical needs.

This is where there’s a great paradigm shift happening from using conventional dashboards & reports to advanced insights offered by augmented analytics data platforms.

How does a modern Root cause analysis dashboard look like? Is that the same?

Modern augmented analytics platforms with intelligent search capabilities offer an easy and user-friendly way of understanding root causes on “why” key business metrics are changing. Users can find root causes with a simple search query in natural English. Platforms like MachEye return complete insight in the form of a chart or an audio-visual story - sounds quite mind-blowing right?

With MachEye, getting answers to “Why” questions is as simple as asking a question in the search box. Let’s understand this with an example of real, publicly available data of total lending in the state of New Hampshire across different financial services companies.

You can simply ask MachEye: “Show me loans by lenders” and MachEye will answer this question instantaneously.

MachEye not only answers this question but also finds and presents other important insights. You don’t have to ask any additional questions or worry about AI models or data engineering tasks. Root cause analysis on critical business metrics will be presented to you automatically.

The above analysis highlights that RMS Mortgage is a leading lender compared to the rest of the players – on average, all other players have achieved $38 MM in lending whereas RMS Mortgage has booked $410 MM). More importantly, Why Analysis clearly presents root causes by highlighting the combination of drivers that have influenced stellar growth at RMS Mortgage. In this example, RMS Mortgage has done $96 MM in additional lending compared to the average for this combination of factors: Applicant ethnicity non-Hispanic and applicant gender is male.

For you as a business user and decision maker, this is a valuable nugget of information. This insight goes beyond “What” is happening in the data and also highlights the root causes for “Why” certain things are changing in the data. Additionally, if you work at a competing bank, these insights also become actionable as you can aggressively focus on the segments where RMS Mortgage has done well.

If you want to ask ad hoc “why” questions, you can easily drill down and compare via an intuitive interface. MachEye opens up rich possibilities for more advanced analysis to understand causes of business behavior across products, competitors, customer segments, time periods, or any such dimensions available in data.

An important point to note here is that none of these insights are coming from a “black box” approach. MachEye offers relevant AI models that will be trained automatically on your data to give you insights on day 1. You can also configure these models from a simple user interface as needed.

How We Do Things Differently at MachEye? Why us for root cause analysis?

At MachEye, we start with some important strategic objectives:

• Transforming the paradigm of analytics by offering actionable insights to every business user.
• Making data consumable and making conversing with data easy for business users.
• Integrating consumable and actionable insights in one simple end-to-end workflow.

MachEye strives to usher data analytics users from the antiquated world of stale, static, time-irrelevant, and expensive reports into the new world of root cause analysis and resulting actionable insights. The following differentiators answer why MachEye can become your best-augmented analytics partner.

• MachEye transforms the data analytics paradigm by helping users understand root causes behind business metrics changes and answering all-important “Why” questions.
• MachEye offers actionable insights and not just reporting of past data. Understanding of root causes immediately makes these insights actionable.
• Root cause analysis is essential for all business users and hence, MachEye offers this functionality to all users without needing any technical skills.
• With MachEye, understanding root causes with “Why” analysis is as simple as asking a question in a search box.
• MachEye presents all types of advanced insights as part of a single and simple, end-to-end workflow for all business users. With MachEye, natural search, AI-powered insights, root cause analysis, and interactive audio-visual stories come together in a single seamless workflow.