BPM Analytics
How automated data analytics can improve team productivity?
Today, data is the most powerful asset that can fuel the growth of an organisation. According to a whitepaper published by International Data Corporation (IDC), the Global Datasphere will have 175 Zettabytes by 2025. Every business has data about its products and services, customers, operations, processes, finances, employees, and various performance parameters.
However, mere accumulation of data does not equal knowledge. It needs to be processed to turn into information that can be used for decision making. And that is where data analytics comes in. Data analytics provides powerful insights that can transform crucial organisational functions such as sales and marketing, human resources, product development, finance, purchase, and customer care services. These insights help make better decisions than those aided by conventional wisdom, as the inputs are more accurate and unbiased. Results of data analytics tools bring out patterns, facts, and figures backed by data-driven inputs through business process automation solutions.
As data continued to grow exponentially, automated data analytics which is powered by AI, came to be used extensively.
What is automated data analytics?
Automation generally results in processes that need little or no human intervention, and it is so in automated analytics too. The use of automation almost completely automates data analytics processes through AI techniques to simplify and streamline data discovery, preparation, and insight generation. Automated data analytics processes vary in their complexity. They could involve creating a simple script or generating predetermined data models that can perform complex statistical analyses. These processes help identify significant data patterns to initiate meaningful action. For example, automated spend analysis can help arrive at appropriate sourcing decisions through accelerated analysis of complete purchase data.
Why should we automate data analytics?
Speed is one of the foremost benefits of using automated data analytics. With automation, data analytics can happen in near real-time with little or no human involvement. Also, as machines are better at performing tedious and complex tasks more efficiently the quantity of data processed can also increase multi-fold. The speed and efficiency thus gained, help optimise processes and aid profitable decisions vital for survival in a highly competitive market.
Time is money, and automated data analytics helps enterprises save precious employee time which is very valuable. With the time that is saved employees can focus on tasks such as core business areas that need human ingenuity while automation manages mundane and tedious tasks. Employees bored of rote tasks can be better deployed for tasks that can deliver high-quality, innovative output. Thus, improved employee productivity is one of the prime factors driving enterprises to adopt automated data analytics today. We will explore the productivity aspect a bit more as it is significant.
The impact on productivity
Automated data analytics can remove routine tasks such as reporting and business intelligence dashboards out of the scope of data analysts. They can now concentrate more on expanding their data sources and furthering the scope of their analyses. They have more time to explore different and innovative perspectives from the vast data sources that can help improve many functions. Complex statistical models that would otherwise have been time-consuming due to the need for multiple iterations can be accelerated using automated data analytics. Data analysts, given the nature of their work, are happier working on more challenging and complex assignments than mundane tasks. Their satisfaction levels go up, and so does the data analysis team’s productivity.
Also, exploring data analytics through multiple aspects can help bring out hyper-productivity* in individuals and teams. Organisations can highlight, celebrate, or incentivise such instances to boost employee morale. In turn this can set off a domino effect and can inspire other employees to achieve more and strive for recognition. Another important aspect of automated data analytics is that since these are automated data-driven outputs, there are no chances of any biases.
Additionally, automated data analytics can help identify process bottlenecks and automatically improve them without human intervention. People tend to lose interest when their efforts don’t seem to produce desired results, and delayed decision-making by stakeholders can add to the woes. Automatically optimised processes can thus help achieve higher productivity and employee satisfaction.
Automated data analytics leads to better products and services that can help organisations gain a competitive edge. When products and services perform better, revenues and profits too will improve. Organisations can invest more in core areas and employee engagement resulting in happier employees and enhanced productivity. Thus, automated data analytics has a multi-pronged positive impact on team productivity.
*For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.
