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Strategic Workforce Planning For Data-Driven Organizations

May 10, 2022

Help organizations find the right talent by identifying skills gaps and the right talents is our core competency.

A skilled workforce is the lifeblood of an organization. Therefore, finding the right employees at the right time is essential for organizations. Strategic workforce planning helps an organization achieve this goal by anticipating its skills gaps and recruiting suitable candidates to fill those gaps.

The four main challenges faced by organizations for effective planning and management of the workforce are:

1. Skills Gaps

Skills gaps are defined as the differences between an organization’s needs and employee skills. It can be applied to both hard skills like technical skills and soft skills like interpersonal skills. In data-driven organizations, technical abilities include understanding the data and the different technologies used to handle data efficiently.

2. Diverse Workforces

Workforce diversity refers to an organization’s employees’ heterogeneous composition regarding age, gender, language, education, ethnic origin, etc. Managing such diversity is a real challenge for HR professionals because to deal with different people, they are required to use different approaches.

3. Talent Retention

Talent retention is one of the major problems faced by organizations today due to frequent job-hopping. In a survey by BambooHR of over 1,000 workers, 31% had quit their job in the first six months. Therefore, retaining talented employees and reducing employee turnover are areas of concern.

4. Quality and Quantity of Workforce

Finding the right quantity and quality of employees is another challenge that can be addressed with workforce planning, where the three primary questions of how many, who, and when should be answered accurately.

We can see that the discussed challenges are not traditional; thus, modern and flexible solutions are required rather than ad-hoc approaches. These challenges become even more intense when hiring potential employees in data science because this field is new and still evolving.

Apply an analytics mindset to power your strategy

CADS AI platform emerged as a practical solution, particularly to help data-driven organizations fill their pipeline with data science and analytical talents. The solutions given and adopted are discussed below:

1. CADS AI platform helps CHROs build effective talent roadmaps and training programs for employees to bridge the gap between technology and skills using a modern method of learning called triple loop learning.

2. Recruiting candidates will be conducted based on thorough assessments, the results of which are tabulated and stored for analysis rather than relying on their CVs.

3.  CADS AI platform allows organizations to conduct internal recruitment by matching employees’ skills to the job requirement, which would help reduce the costs incurred in hiring a new candidate.

Ultimately, CADS AI platform aims to help reduce the risk of hiring the wrong candidate and avoiding employee churn by making use of smart analytical tools for making hiring decisions.

CADS AI platform is part of the offering within our Data-Driven Organization roadmap. We’ve identified six pillars of a mature data-driven organization that enable others to synchronize big data at all stages of their business.

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It will help connect the dots between the different departments within the organization, and eventually, help bridge the talent gaps to ensure sustainable business outcomes.

Check out how you can optimize your business strategy with data — and improve your results.

Book a demo to get started.


Source: The 5 Steps of Analytics-Driven Workforce Planning

Source: Why HR Needs Data-Driven Workforce Planning to Avoid Talent Shortfalls

Source: A Guide to Strategic Workforce Planning

Source: Use Strategic Planning Techniques to Build Your Workforce Plan

Source: Future-proof your organization through data-driven workforce planning

Source: Triple Loop Learning


Max is the official mascot for CADS or the Center of Applied Data Science.