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You understand the value of having integrated data to enable data-driven decisions, but you are running into several roadblocks that continue to hinder progress. Compartmentalization of data, lack of internal analytical skills, and general skepticism in the minds of key stakeholders are some of the common barriers that keep your analytics initiative in the “not now” category.

 

You see the value of bringing data together, but often find data that is cordoned off or difficult to access, let alone analyze. Within many organizations, there is a growing intolerance and drive to change the “silo” data culture and a shift to make data not only readily accessible, but also integrated for anytime analysis. You have rich data and it is just begging to reveal deep insight that can support and enhance the overall business objectives and initiatives of the organization. Unfortunately, you find data that is all parceled off into different departments, business units, and fiefdoms. The data resides in different legacy systems and databases that do not speak to one another. There could be several reasons why this is so. You may find there is a general lack of skills internally to bring this data together or you may run into permission issues when you try to access. Although you can envision something that could be truly transformational, the process to get there often appears insurmountable.

 

Here is something that several of our customers have used to lay the groundwork for building an analytics strategy that is truly sustainable. Many companies embark on their workforce planning and analytics journey by focusing on analyzing and solving one or two key business objectives. This can be a great way to promote and drive a universal interest in analytics and build a powerful business case for a more sustainable long-term strategy. If you are like most organizations, the key issues will not be difficult to identify. Whether you are looking at a looming retirement issue, a build vs. buy dilemma, or a high performer retention crisis, a comprehensive predictive study can be a fantastic way to facilitate meaningful collaboration. When you focus on solving one or two critical business issues, it is often easier to get buy-in from key stakeholders who have the drive and authority to break through common roadblocks. More importantly, if you can get high-level support and buy-in, the hindrances you have been keenly aware of will now be illuminated to everyone and solutions will often come about more rapidly.

 

A comprehensive predictive study can offer high-value insight quickly and it is easier for everyone to see what a broader analytics implementation could offer. Here is one case example to give you an idea of what a predictive study could provide to your organization.

 

Case Example – Modeling Turnover

 

For turnover and retirement, Vemo enables the following objectives:

 

Key Drivers Analysis: Our model organizes and analyzes a large array of data – employee attributes, employer actions, workplace conditions and external conditions – to identify key drivers of turnover.

 

Forecasting: Our machine learning approach to statistics creates an estimated flight risk for each employee, divides employees into high-risk and low-risk baskets, generates an overall forecast for the company and identifies high-risk work units for interventions.

 

Data-Driven Scenario Building: Our workforce analytics and data science expertise allows you to model the likely impact of hypothetical internal and external events and interventions on turnover outcome.

 

Example Questions We Help You Answer

 

You have questions. We provide the answers that allow you to control flight risk.

  • Which workplace conditions drive turnover?

  • Based on current state, when will retirement eligible employees actually retire?

  • How will changes in the economy and unemployment rates impact when our employees will retire?

  • How might we change our workforce environment to foster higher retention?

  • What is the optimum annual raise to boost retention while also controlling wage expense?

  • How can we design HR policies that are responsive to changing economic conditions?

Sample Outcome:

 

You determine the ideal increase in employee compensation to improve retention vs. diminishing return for a critical employee segment.

 

Vemo is a leader in workforce planning and analytics subscription software and predictive analytics consulting services. Vemo differentiates itself in the market by its expertise, innovation and customer-oriented approach.

 

For more information: info@vemoworkforce.com

 

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