The companies need to begin with understanding the needs of their business before adopting analytics – address questions like what is the goal and how analytics support that goal.
For a long time, businesses have not been able to adopt analytics across all users. The question is why? It is likely due to existing analytics and data platforms. However, with modern Cloud-based Analytics and Business Intelligence (BI) tools that can embed ad-hoc data analysis and dashboards into applications, things are changing. But what can be done to scale analytics adoption? According to a recent report by Citrix, 38 to 50% of today’s workforce is said to be digital natives, meaning the ones who grew up with technology and the internet. And, by 2025, this number is likely to stand at 75%.
At the same time, when we talk about accepting data analytics, it becomes important to take into account the remaining 50% of the workforce which doesn’t come under the category of digital natives.
Against such a backdrop, it becomes vital to come up with a plan that focuses further enhancing scalability and usability of integrating analytics tools into the daily workflow.
How to Increase Scalability and Usability of Analytics Tools?
It should be a long-range, purposeful plan which can accelerate the acceptance of analytics tools into the daily workflow. So, what are the key requirements in order to scale analytics adoption? Scalability, in simple terms, means the ability of a computing process to be used or produced in a range of capabilities. There are two steps that need to be followed here:
Firstly, providing the users with a tool that can be used easily, covering essential points of availability and usability. Secondly, it needs to deliver information that is relevant to their needs, implying adaptability. You can only scale analytics adoption when it is easier for non-technical people to use.
Now, another important factor to take into consideration is how it performs? To achieve long-term success with analytics it should be able to adapt to the needs of its users. Furthermore, it should have a robust backend that is capable of accommodating increased workload. At the front end, it should be easy enough for widespread acceptance of analytics.
Other aspects which need to be undertaken while fostering analytics adoption are planning, technical frameworks, and testing. The companies need to begin with understanding the needs of their business before adopting analytics – address questions like what is the goal and how analytics support that goal.
Once you are done with your research, identifying goals, looking for the technologies that will work for you and building the technical framework are to be done subsequently. It is also important to choose the right technologies, tools, and systems which support current and future workloads along with providing a good experience to end-users.
How to make it Flexible?
Along with working towards scalability, flexibility is another aspect that needs to be considered. The foremost factor which ensures flexibility in scaling analytics adoption is deploying the flexible infrastructure.
How will you do that? Cloud-based infrastructure is one way to go about it. With cloud-based infrastructure, you can get analytics pipelines up and running fast. But even when companies are investing in cloud technology, why only 24% of organizations have succeeded in becoming data-driven? Unlocking its value still remains elusive for many organizations, that is why we raise the following questions.
Why Cloud-based infrastructure?
It is a cost and labour-effective way to cope with heavy computing tasks. It’s more flexible and scalable when compared to other technologies. An additional inducement is a cloud-based infrastructure that will speed up implementation and make analytics’ value more quickly apparent.
Another way to make it flexible is by making it accessible from anywhere. If the business is relying heavily on data for all its decision-making processes, adopting analytics can be most flexible when available even on mobile. Secure mobile access to analytics will make it easier for users to adopt.
In a nutshell, it is important to remember that this is just the first step towards scaling analytics adoption and it largely remains a process that can’t be achieved in one go. Thus, organizations will have to navigate their way into incorporating analytics into the system to achieve the best results. The key is to keep evaluating, deploying, and scaling.
Source: Business World