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Self-Service Workforce Analytics Needs Self-Service Data Management

SwoopTalent
August 5, 2018

A software system without useful data is, well, not very useful - and that's doubly true if it's an analytics system! There is now an explosion of data in the world to keep up with, data that must be kept up to date for real-time prediction, modelling and analysis tools to work.  That is why self-service workforce analytics requires a separate, self-service data management system.

Unfortunately, while many companies invest in workforce and people analytics systems, they do not have adequate resources (whether they are people or tools) to deal with the flood of data required to make them effective. In fact, when managers make the decision to purchase these systems, it is sometimes done to avoid hiring several workers to generate the results themselves. The idea is to produce a clean, accurate workforce analytics tool with existing data.

To get the optimal result, the closest to the truth, companies simply need more data and don't have enough time or resources to produce it.  That is why self-service is so crucial.

Useful workforce analytics systems call for an on-going stream of real-time data to achieve optimal results. There are several steps in this process that must be automated. These include:

  • data collection
  • data modeling
  • data preparation
  • data warehouse
  • semantic layer
  • data integration
  • data governance
  • data security

Each of these steps requires coding or a script in order for automation to work. They consolidate large amounts of information, remove extraneous data and protect the information from theft. Most importantly, they are prepared so that the team can make them as useful as possible for decision making. 

Again, all of this automation requires a heavy investment in engineers, outsourced services or a strong IT department. Once more, managers are purchasing the workforce analytics tool to avoid this investment so it defeats the purpose.

That is why the emerging field of self-service BI and workforce analytics has developed important philosophies about ease-of-use and access-to-all.  That means there are no longer conflicting users with different models, inputs and access.

Instead the users have a clear understanding of the source of the data and the accuracy of the information. The data automatically updates and any new customization or queries are completely self-service. Employees are empowered to learn to use the system for themselves. However, they are not burdened with the upkeep and maintenance of the data inputs.

Instead, the data inputs are all set-up on implementation. At that point, the software is integrated into the other overarching tools being used in the business. Whether that is Microsoft Dynamics, an HR tool, ERP, CRM or financial programs, it all flows through a self-service model. 

Implementation

The key to a self-service analytics tool is the initial implementation. Top tools make it easy to point the software to the correct sources of information. Whether that is online data, an SQL database, emails, Google trends, financial information or anything else. 

Top implementation teams can quickly and efficiently set the self-service analytics tool in motion. Once completed, the overwhelming flood of data in the world becomes a manageable stream that virtually anyone can work with. 

SwoopTalent

Despite the daunting nature of these tasks, programs like SwoopTalent can automate much of the process for talent data. The system efficiently segregates and compiles the information while connecting, managing and canonicalizing data from all the various sources automatically.

SwoopTalent aggregates internal and external data to create a holistic picture automatically. This can be used by senior management to make key talent management decisions. That produces a better organization with far higher levels of talent.  At the end of the day, this makes the difference between success and failure.

The firm helps many small and medium clients gain the most out of  workforce analytics. For more information, please contact us.

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