We live in a world where data is a business asset. It is revolutionising the way companies operate across almost every sector and industry. With the ever-growing smart world, data becomes the key to gain a competitive advantage. In the coming time, an organisation’s ability to compete will be directly proportional to its ability to analyse data and take leverage of it.
According to the International Institute of Analytics, in 2020 companies with analytics saw $450 billion as productivity benefit over the companies who are not using the data.
A few years back picture
A few years back when data analytics was the new term on every mind. Companies were focusing more on the implementation of data analytics in their organization. Following were the key points on which companies focused back then.
- A smart strategy was as necessary as the volume of data. It did not matter what data was available, what data you are collecting, and what your competitors were storing. It did not matter whether your organization had data ready to be analyzed at your disposal or next to zero. A good strategy was more about what your business wants to achieve, how data could help you get you there than what data is available or potential ready.
- Finding out the right data: It required the definition of how you wanted to use the data. After deciding what you wanted to gain from data, the primary objective was to source and collect the best data.
- Data to insights generation: A plan was laid out about the application of data analytics to your data to extract business-critical insights. It would result in better decision making, improved operations, and more value generation.
- Meeting infrastructure requirements: The next step was to decide upon the software and hardware that would help you in the generation of insights from the raw data.
- Boosting data competencies: It was essential to cultivate data-crunching skills. The main two options were to educate your in-house talent and outsource the data analysis.
- Data governance: Since data was and is a part of critical and personal information. Collecting and storing it brought legal and regulatory obligations. Hence, companies needed to incorporate data ownership, privacy, and data security into their data strategy.
FACT TO KNOW: 55% of North American businesses have adopted big data analytics.
Current and Upcoming Scenario
Accessible tools have brought tech and business into a tightly coupled relationship. Amid rabid competition, data drives the most efficient decisions in the supply chain, marketing, and IT industries.
To expedite the advantages of data analytics, one of the major proposed changes is the removal of a standalone data analyst role. Companies are expanding the job requirement for their corporate employees to inculcate data analytics skills. The same applies to the hiring of new employees. They must have skills or a fair sense of tools for data analytics.
Today, data analytics is seen as part of every role in the organizations. It has fuelled data literacy throughout the company. Partnering with a subject matter expert with tech-savvy employees will yield the most. Imagine the benefit when these two skill sets are available with one employee. It will not only speed-up the data analytics process but will also lead to the most effective leveraging of the data.
If you are not coping-up with these changes, if you are unable to analyze the dataset, draw conclusions and make decisions based on them, you are not fit for survival in the jungle of corporate.
Another subset of the futuristic approach to data analytics is modeling data skills. Businesses know the importance of data analytics strategy. Organizations must invest in building reusable platforms if they want to say bye to traditional roles of data analyst or data scientist. With data analytics skilled business users, they will focus on extracting insights from raw data. The IT team can specialize in building data platforms.
Problems with this change will be a probable rise in data quality issues as business users will extract the data. Secondly, these business users must mind the data silos.
On the other side, organizations that wish to implement data analytics but face analytics scarcity will welcome this change whole-heartedly. The organizations combating analytics scarcity has two options. Either teach technical experts the business contexts or train subject matter experts in technology platforms. The fastest way out is to pair both the departments to meet the company’s needs.
Along with, an expanded skill set of everyone; we should expect technology to be more business user friendly. Even with ease in access to data tools, demand for roles related to data science has grown by 46% since 2019, according to LinkedIn’s report.
The need of the hour is to reinvent old traditional data science roles by asking, what are the new ways of delivering the platform and services. To make the most out of the data, companies should rely on advanced technology and forge their business and technology decisions as one. This agility will new your organisation’s new strength.