Data-Driven Staffing to Turbocharge Growth and Transformation

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Staffing and recruitment, by its sheer nature, is a business built on data. On the demand side, clients analyze their business requirements overtime to determine their people needs. This takes the form of job descriptions and skills requirements spread across the dimensions of time and location. On the supply side, candidates with requisite skills, experience and expertise require to be assessed for fitment to existing and upcoming positions. The volume and variety of opportunities involved coupled with the necessity of velocity in hiring makes it a business apt for disruption from data driven approaches.

Business Drivers for Staffing Industry

An enterprise-level data and analytics platform can enable a number of use cases for business. It can help meet the urgent need of cost optimization/efficiency on the one hand and growth and transformation on the other.

First and foremost, staffing companies can leverage data to enhance growth by turbocharging the sales process and fulfillment engine, thereby, increasing the number of open orders and positively impacting the fill rate. Across front-office functions, data platforms can help track the lifecycle of a lead and provide insights into correlation between leads generated and revenues realized. It can also enable data driven demand fulfillment — from proactive prediction of demand, to prioritization of job orders to submittals and placements.

Across middle and back-office operations, order to cash analytics can provide better means to track Days Sales Outstanding or DSO and enable proactive follow-ups for faster cash collection. Spend analytics can provide opportunities for Selling, General and Administrative (SG&A) Expense optimization.

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Further, data platforms can help improve existing offerings by providing value added services which can be a source of competitive advantage. It can also pave way for innovation by helping build new products and services and expand to new market segments.

Overall, in a data-driven staffing company, the most important metrics affecting the top and bottom line, including revenue, can be predicted with high accuracy with a possibility of timely interventions for driving positive business results.

So, what is the most effective path to become a data driven staffing company? Here are some thoughts.

Succeeding with Data-Driven Staffing

In an industry that’s built on the foundation of personal relationships, data driven staffing presents a paradigm shift. Success in any such endeavor will depend upon top leadership support, organization wide adoption and lean execution across segments. Following are the key tenets in order to succeed with data:

  • Enterprise wide use cases. Instead of working on siloed business cases, focus on cross-functional, enterprise wide use cases like lead-to-revenue lifecycle, order-to-cash analytics, talent redeployment quotient etc. This will provide a long term program vision with an emphasis on measurement and control.
  • Value realization based governance. Organization structure and workflows need to be remodeled toward the realization of business value. Governance should amplify data based approach.
  • Business and IT Amalgamation. For success of data driven staffing, business and IT teams need to work together, not only to formulate solutions but also to learn and adapt.
  • Agile technology development. Following an agile, minimum viable product (MVP) based approach aligned to data technology vision and overall enterprise architecture is critical.
  • Continuous data transformation. Becoming a data driven organization is not a one-time activity but a continuous journey. What works today may not work tomorrow. Hence, an unquenchable thirst for transformation is desired to remain successful.

As the staffing industry tackles the obstacles imposed by pandemic, data-driven staffing offers a faster avenue to growth and transformation. However, technology alone is not sufficient for such a transformation. A holistic approach and effective execution is required to succeed in the data-driven world of work.