How can Enterprises Succeed with Self-Service Analytics?
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How can Enterprises Succeed with Self-Service Analytics?

By Sushant Ajmani and Yash Bhattacharya

With technology evolving at a rapid pace the sheer influx of data from business operations is ever-growing. Managing and analyzing these vast reservoirs of data are proving to be a challenge for analytics teams. They just don’t have enough manpower to analyze all the data being ingested, to be able to offer high-quality insights that can influence business decisions in real-time. 

The introduction of self-service analytics is a turning point in data analytics – advocating a democratization of data where end-users without technical qualifications can access and analyze data. A system where general employees can be engaged in leveraging self-service analytics tools to gather actionable business intelligence.

Self-service analytics promotes business growth from the ground up. Business decisions are being made at every level of an organization, but seldom are they well-informed decisions. If employees have access to data that is relevant to them and are given the tools to analyze the data sets, they can gather actionable insights and make better-informed business decisions. Improved decision making in turn enhances operations and the return on investment (ROI) for every team. And if every team generates a greater ROI, the business as a whole becomes more profitable.

The self-service analytics industry has been witnessing a transformation, with more and more companies entering the digital space. The demand for self-service analytics tools has skyrocketed, as organizations have started to realize the advantages of self-service BI. But this beneficial system can pose unique problems without effective governance. 

Once all the data is being handled by generalized personnel, there are always risks of not just data leakage and misinterpretation of data, but conflicting reports being created from the same data set. This results in misunderstanding of data, insights becoming undependable and officials not knowing which data to rely on. Data and business alignment have to be ensured by those responsible for data governance because without it employees would be empowered but no real value will be gleaned from the initiative.  

Augmented Analytics and Self-Service BI

It is not just a rise in the amount of data being ingested, but the growing data complexity that is creating new problems for those trying to analyze the data and obtain actionable insights. Even though major advances have been made when it concerns analytics tools and their capabilities, certain tasks such as building business models or interpreting analysis results, demand human intervention. This is where Augmented Analytics is revolutionizing the self-service industry, gaining momentum in recent years.

The serious dearth of expert Data Scientists has left a void in an ecosystem desperate for help with analytics. Augmented Analytics addresses this challenge by automating tasks that are usually time-consuming and biased. The technology is a simple augmentation of human intelligence and contextual awareness, based on Natural Language Processing, Machine Learning, and Automated Insights. This enables employees to generate actionable insights through automation and make better-informed business decisions. 

Automation eliminates human error, saves time, and can even filter out insights that are irrelevant, optimizing the information being leveraged. With relevant and actionable data, generalized employees can now make well-informed business decisions that minimize risks and maximize the potential return from a venture.

Course5 Discovery is an AI-powered Augmented Analytics solution, geared towards promoting an insights-first culture that values data-driven decision making. Discovery enables automated data extraction and management of meta-data using a network of inbound data connectors. The Machine Learning knowledge base keeps improvising insight generations, recommendations, and publishing, with a centralized Search Index that keeps refreshing for faster querying. The solution is rounded off with an automated narrative generation service publishing precise and contextual insights, which is the order of the day.

The Importance of Actionable Insights

The data being ingested at every level of an organization is only as good as the people and the technology analyzing it. The right tools can transform an ordinary data set into a treasure trove of contextual and actionable insights, enabling an organization to use the data to its advantage and make well-informed business decisions. 

A Forrester report states that even though 74% of organizations wish to be data-driven in their operations, only 29% succeed at leveraging analytics for business decisions and the actual execution of operations.

Actionable insights are the missing link that organizations need to bridge the gap between data and business value, and organizations understand the importance of data-driven success. 

For insights to be truly actionable, they need to be aligned with the organization’s business goals and strategies. A benchmark or point of comparison is also needed for proper contextual understanding, without which it’s just stand-alone data. The insights have to also reach the right personnel at the right time, to be relevant enough to deliver business value. And the more clarity and specificity employees have on insight, the more likely it will be acted on. And it is ideal if the action can be taken in real-time so that well-informed decisions can optimize operations to maximize business value and ROI.

Improving ROI with Self-Service BI

As talked about before, self-service business intelligence solutions enhance the capabilities of even the generalized employees to not just access but analyze business data and gather actionable insights. They can leverage these insights to influence business decisions in real-time and enhance the profitability of their department, in turn increasing the overall ROI of the organization. 

Expenditure on self-service BI solution licenses and related hardware is easily quantifiable, and these remain the primary focus of organizations when the total cost of analytics solutions is considered. But what is not taken into account, is the cost of employing IT personnel to execute and manage business intelligence solutions. Self-service models afford organizations the luxury of saving up to 60% on their investment per user, requiring organizations to invest lesser for a higher ROI. 

Analytics for Success

Data and analytics are quintessential to an organization’s efforts towards digital transformation. Organizations yet to adopt augmented analytics or self-service BI tools are not too sure about the advantages that come with being a data-driven operation. The adoption of analytics into business operations is proving to be a metric for success, and here are some benefits that such organizations are enjoying. 

  • Being data-driven and leveraging analytics ensures a company is 23 times and 6 times more likely to attract and retain new customers respectively.
  • They are 19 times as likely to be profitable.
  •  Companies using big data and analytics are experiencing an 8% increase in profits and a 10% reduction in costs, says a BARC survey.
  • More than 50% of retailers have also reported experiencing a competitive advantage over their competitors after implementing self-service analytics tools.
  • Data-driven businesses are witnessing a steady growth in their business operations, capabilities, and clientele, all thanks to analytics and informed decision-making.

Insights at Scale

Analytics capabilities are expanding exponentially, coupled with an increasing demand for empowering generalized employees with self-service BI and analytics solutions. The following are some areas where we are witnessing a propensity for scaling analytics and delivering insights accordingly.

  • Effective business strategy design depends on data and analytics not just of the current scenario but of projected ones, to best curate operations based on insights.
  • State-of-the-art analytics models are being employed to influence business decisions, but even though they are difficult to maintain and keep upgrading to meet requirements, they seem to be highly effective in delivering precise and relevant insights.
  • Cloud-based infrastructure offers the best option for flexible and scalable resources while implementing analytics and gathering insights.
  • Mobile access to analytics tools in a self-service model allows employees access to relevant insights that they can act on and be familiar with business operations as a whole.
  • Data security and data governance become very important in a self-service model, and user permissions can now be automatically configured and managed, scaling the amount of data an employee can access and the insights they can generate. 

Integration of Augmented and Self-Service Analytics

With analytics capabilities evolving continually, there will be the eventual integration of Augmented Analytics and Self-Service Analytics tools. Automation and human intervention will work in tandem to operate a seamless data collection and analysis process, which will yield actionable data relevant to the employee. To function smoothly, there needs to be a collaborative work environment and the right people need to have the right tools at their disposal.

Organizations need to have a two-part approach if they want to succeed at this integration and have a streamlined self-service BI experience. Organizations need to acquire robust BI tools that will deliver results in both the short and the long term. They also need to inculcate an agile analytics culture, where employees have access to data relevant to their operations and not just generalized data for all. 

To get started on this journey towards a seamless self-service BI platform, companies need to sponsor projects and get employees enthusiastic and motivated to take up challenges and deliver high-quality insights. Simply deploying the BI platform is no good, if the employees aren’t trained to operate on the platform and manage vast data banks. Onboarding and training processes have to be in place to ensure employees can do their bit when operating the high-end BI solutions. 

All that is then left, is embracing a data-driven culture, where employees can delve into analytics and BI tools to deliver truly actionable insights. And if the operation is agile enough, the organization will be successful in leveraging the insights to enhance business value in real-time. 

Course5 Discovery offers you access to AI-powered augmented analytics tools to help your organization become data-driven and create a work culture that values high-quality insights. Request for a demo today and digitally transform your business through automated analytics and insights that can be easily consumed in narrative form.

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Sushant Ajmani
Sushant Ajmani
Sushant has over 20 years of experience in the digital analytics industry with a strong background in Customer Analytics, Marketing Analytics, and Logistics Analytics functions....
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