Good-bye, Subjective Decision Making; Welcome, Predictive Analytics for Succession Planning
Workforce Analytics: Future proof your own personal business with Succession Planning implementing Analytics
Suppose you are part of a Gift Management team. A typical moment at your job starts with putting together and matching employee data through various systems and rummaging as a result of your mailbox for previous chats. Somehow, you compile relevant information and facts in the nick of time period, but you don’t have any time eventually left to think and plan ahead of your one-on-one meetings. You are aware of in addition to hope that you can control better in the next finding, but some things never shift.
The modern advice hunter-gatherer needs to stay forward of the game. Reactive in addition to predictive metrics are among the most vital tools to conquer the problems of talent management.
Allow me to share inquiries one needs to ask oneself while crafting out an analytics strategy.
A. Identifying Critical Talent: ‘ Critical roles’ do not automatically mean the ones from senior leadership and managers but could be roles related to sales, customer service, production and maintenance etc. To identify critical talent, you can use the following guideline questions.
- How important is the talent with respect to the success of your business strategy?
- What is the cost of replacement for a role?
- Are external candidates easily available?
- What is the ratio of your successors identified versus critical senior positions for the business?
- Are these skills niche skills and/or they replaceable?
- How urgent will be a potential replacement?
Measure the parameters for each of the guideline questions, for potential critical roles and positions. If any of the parameters is not measured, then, you must question if the position belongs in the list critical first. Maybe, it is time for you to reassess checklist!
B. Succession Decision: Once you have a superb understanding of the critical positions, it is time to prioritize them within your business before you build a pipeline. This helps to target correct talent investment, especially during turbulent and uncertain macroeconomic situations.
- Predict the most suitable candidate based on a talent index and diversity index for senior critical positions.
- Assess suitability of internal replacement versus external replacement of talent
- Flag off employees with good potential, high retention risk and stagnancy risk for critical positions
- Assess the replacement readiness of identified successors
- Integrate training programmes, 360-degree survey feedback, participation in external forums, publication published for senior critical roles.
- Calculate the revenue impact and the productivity impact as a result of engagement programmes deployed for critical talent.
Using a combination of self-service tools and algorithms, this information can be represented interactively, helping you gather intelligent insights. Often a talent manager spends a lot of time massaging data and trying to cultivate complex calculations around the data. At the end of the entire exercise, the goal of the analytics is lost somewhere in the multiple sheets.
- Analytics stories derived from this should over the time be able to tell you the changing landscape of critical positions over a period of time within your business and provide you the ability to keep a close track of the health of the talent to close these positions.
- Most importantly no matter what tool or algorithm you decide to deploy, this information needs to be easily accessible to relevant stakeholders on any device whenever needed.
Most brands apply analytics to understand customer buying patterns to improve revenue. However, it is still uncommon to find organisations applying these approaches internally to their processes and employees. Although we are yet to tap into the complete potential of analytics in the HR space, we willfind HR functions reinventing themselves from the days to come. A guess work and human biases approach is going to be replaced with a more information and data centric approach.
Sanjyot is the Director Data Analytics & Services ay Paratus Knowledge Ventures Pvt Ltd . She has over 14 years of experience in Data Analysis and Reporting and now runs a start-up specializing in Data Analytics and Gamified Learning. She has extensively worked inside of this domain in companies such as Cognizant and Tata Consultancy Services.
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Source: analyticsinsight. net
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