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Engage in Meaningful Conversations with Your Data

By December 27, 2022June 1st, 2023Conversational Insights, Data Analytics5 mins read
Conversations with your data

Introduction

Business leaders of the 21st century are living in exciting times. Technology has advanced so much that it should come as no surprise that you can hold interesting conversations with your data. But, the most interesting point to note here is that the shelf life of technological advancements is lesser than before. All of them are becoming redundant in a short period. Everyone knows, and there is a disruption happening at each moment. But even amidst these exciting times, one question remains.

Would all of this have been possible without data?

Humans started innovating around their daily tasks when there was real actionable “intelligence” for them to ingest. And how did humans get this intelligence? By gathering data, talking to people, consulting with experts, etc. But at the turn of this century, an amazing advance in the data space happened. The amount of data getting collected skyrocketed.

IDC claims that the global datasphere will more than double its size by 2026.

In parallel, the technology to analyze the data and derive actionable information is also maturing, albeit slowly. There are umpteen issues associated with the modern tech stack engaging in the business of data analytics, the most common of them being technical complexity.

To battle these issues associated with data access, a simpler tool that allows you to engage in meaningful conversations with your data is required. Before we understand the concept of talking to your data, one has to learn about data storytelling and how it sits in the context of conversing with your data.

Understanding Data Storytelling and its Three Aspects

Data storytelling is a framework to communicate information in a way that is easy to understand.  It’s the process of using data and visually representing it to create stories. These narratives help readers understand how specific trends came about and how they’re evolving. Three aspects that every data story must possess to make it relevant, engaging, and interesting are:-

  • Data: When it comes to data-driven storytelling, it’s important to base your narrative on clean and accurate data. Effective data management solutions can help collect, clean, format, and store data from all sources.
  • Story: The chronological order with an introduction, the context, the middle, and the conclusion from the story where data points build credibility.
  • Visualization: A picture is worth a thousand words, and a forecasting chart is even more for a business. It might be easier to look at a visualization instead of reading through thousands of lines of data in a spreadsheet.

Socialize Data Storytelling

Data storytelling is a niche skill that a select few possess. It requires an in-depth understanding of the patterns hidden in data, building effective visualizations by navigating through different analytics tools and structuring the data points to provide a story.

But the world is moving at a pace where frontline employees are becoming decision-makers and their decisions are dependent on improved data access.

87% of leaders say their organization will be more successful when frontline workers are empowered to make important decisions at the moment – HBR

Enabling everyone to become data storytellers is possible when you build a data-driven culture and encourage everyone to depend on data by simplifying its access.

Why Should You be Talking to Your Data?

Take a step back, and travel back to the business world of 50 years ago when business leaders were expected to take tough decisions. Regular meetings would always have been a part of their daily life.

Imagine you’re a finance leader chairing a meeting and your team is presenting to you the order to cash figures of Canada for 1972.

  • What was the figure for Accounts Receivables for Q2 of 1972 in Manitoba?
  • Have we collected 100% of the pending payments?
  • Which customers are defaulting? And, why?
  • How is it looking in Ontario and Alberta?
  • Should we increase the credit of ABC Corp, because they’ve paid on time without even one instance of defaulting?
  • What is the overall DDO for all our Canadian customers?
  • What is the collection efficiency of our collectors working from Ontario province?

These are some of the questions, you will pose to your team members and they will be ready with their answers. At times, you will also be discussing with your Accounts Receivable director to rethink the strategy and improve cash flow.

Fast forward to today. The questions remain, but the way answers are consumed has changed. You’re sitting in front of an A/R dashboard and navigating through it to find the answers to the same questions.

Unfortunately, in the process of trying to innovate and close data gaps, we have also successfully complicated the process of deriving insights.

The current mode of researching, finding information, and then acting on it have its fair share of issues starting from information overload to delayed decisions

But the most basic ones are related to human behavior while asking data questions.

Infinite Questions

Questions for deriving data insights and information are neither finite nor fixed in nature. They change every year, every meeting, every moment.

Different Goals

The objective of the information seeker will influence the questions – A CFO may not necessarily be looking for the same information as a collection analyst.

Momentary Questions

The answers will prompt more questions from the user either because the original question was incomplete or the data answer has shown additional insights.

Future of Data Analytics – Came. Saw. Conversed.

A conversational approach to data analytics is the simplest solution as it is not different from the past. A past where humans helped each other to get actionable information, and make brilliant business decisions.

The only difference is that a technology like conversational insights is acting as your data assistant, but you won’t feel the difference. Conversational AI has ensured the humanization of machines so that actual humans can get more done in a shorter timeframe. The benefits are many, but two that will have a bigger impact on your data analytics will be:-

  • Removing the limitation on information availability, since it’s conversational and not peering into a static dashboard.
  • Presenting the insights sequentially based on the questions framed and the knowledge level of the information seeker.

Conversational insights is the one true solution that will ensure everyone becomes a master data storyteller.

Would you like to see conversational insights in action, where a business leader like you is asking data questions and getting insights, all in the language you speak?

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