Upgrading Enterprises Analytics Capabilities: Why Analytics Learning Academies are the Solution
Enterprises across the world are engaged on a cost-cutting spree triggered by the pandemic. Hiring & promotion freezes, and nominal pay cuts are the norm to help tide over temporary business setbacks. However, Draup has learnt that the Learning & Development activities have so far turned out to be immune to this.
You can read an in-depth analysis on this phenomenon here.
A major contributing factor is that most companies have realized that internal reskilling and skill upgradations are the way forward. And this is true for the most in-demand skill in the current market scenario, Advanced Analytics, as well.
Jobs in the analytics domain are touted to grow between 16-21% by 2020 according to the World Economic Forum.
At the crossroads of business intelligence and AI, Advanced Analytics has emerged as a must-have skill for modern enterprises cutting across sectors. From banking to IT, healthcare and even public safety, tools powered by analytics engines have delivered outstanding results.
From the perspective of major workforce planning leaders, it makes sense to ensure that there is an organization-wide analytics capability to remain current and competitive. The establishment of an analytics learning academy also builds an inventory of future skills and a roadmap to attain them.
Analytics Learning Academy: In-House or Vendor-Supported?
Every time there is an accelerated shift in the tech paradigm, companies are eager to hire vendors to implement training modules. There is a prevalence of ad hoc solutions like online learning platforms, universities and executive-level programs. However, most often, these training modules are generic and might not be in-sync with the company skill goals. The result being that they manage to bridge the skills gap only partially.
Advanced Analytics is broad-spectrum skill base that is not going away anytime soon. Stop-gap measures will simply not do.
Fully capable, in-house Analytics Learning Academies are an alternative long-term solution that companies should explore seriously.
Bespoke Training, On Demand
A tailored training module helps bring a cohesive mindset around analytics for leaders, business staff, and analytics teams.
We have identified the following key benefits of Analytics Learning Academies:
Diverse training modules linked to company goals
With an in-house training strategy, the length and breadth of your curriculum is under your direct control. Depending on employee feedback and the changing industry context, you can tweak it without having to depend on external factors.
Training modules can be created keeping in mind the diverse learning needs of your talent pool. If a data scientist wants to engage in a project using Computer Vision, there should exist a training module specifically tailored to make this leap as easy as possible.
Similarly, for a talent pool that is well versed in data mining processes, a rigorous statistical analysis module will help them leap towards a predictive analysis project.
Evidently, academy training modules depend on your employee’s career path and enterprise learning objectives. The advantages of this strategy over a vendor pre-designed module are obvious.
Bridging the analytics skills gap
Despite the growing reliance on analytics tools and methods within organizations, you may find that not all employees are able to achieve optimal results. Within the same team, there could be individuals who are experts in using these tools and methods. A learning academy acts as a catalyst for knowledge transfer and helps raise standards to a more equitable level.
Having an SOP-oriented academy environment also significantly reduces the learning curve to learn new tools and frameworks.
The most business-critical benefit of an in-house learning academy is that it supports continuous learning initiatives. Acquiring new knowledge on an ongoing basis requires a lot of self-initiative. The learning-conducive atmosphere provided by an analytics academy motivates and drives employees to take on more challenges related to their job roles and aspirations.
With Continuous Learning at the crux of your learning academy, companies will be competitive enough for today’s evolving talent marketplace.
Training on the job
This is perhaps the biggest side benefit of having an internal learning & development strategy. You can train your employees with your actual data sets and problems that are unique to your industry/domain. No more learning generalized curriculum and figuring out how to apply it your problem.
Yes, building your own Analytics Learning Academy can get expensive. But this is a one-time major investment requiring only small periodic investments for maintenance. Compared with paying significant sums to external vendors who may or may not meet your learning goals, in-house centers are the way to go.
Analytics Learning Academy for a Future-Proof Workforce
Such an Analytics Learning Academy will also train senior VPs and leaders on digital age systems to take advantage of rapid innovations. They may also investigate the daily digital habits of the enterprise and see how that can be influenced. Doing this over a period of 18 months will dramatically impact the analytics capability across your organization.
Establishment of in-house learning centers has been accepted as a necessity by leading enterprises, especially considering the recent pandemic.
Assessing your talent pool on their potential for learning, training and reskilling them to facilitate internal transfer is the ideal way to stay ahead of the future talent shortage. This is exactly what Draup’s Talent Intelligence platform aims to solve. Talent management teams can identify skills, courses and certifications required to move to a new analytics job role and prepare a roadmap for employees to get there.
A major function of any learning academy is filling skills gap and enabling transition from one role to another. With the Reskill Navigator you can analyze the skill gaps between the start roles and the end roles for various analytics roles, along with efficiently predicting the job readiness and proficiency levels.