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Benefits, barriers and recommendations to achieve workforce optimization through analytics

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Nov 16 2016

Every retailers dreams with a efficient and optimized workforce at store floor providing the highest customer services with the lowest labor cost. Nowadays this is possible and is accessible to all retailers through advanced analytics.  But there are some barriers that may rule out  the possibility to achieving the benefits that workforce optimization can provide to business, here you will find some recommendations to overcome them.

The current era makes for a challenging environment for retailers. In addition to the macro pressures that drive organizations to focus on efficiency, retailers must become more agile and proficient in analyzing trends to balance the competing forces of customer needs — which are ever more demanding, and the competitive pressure to do more with less.

Retailers who have deployed automated workforce management solutions, such as budgeting, forecasting, scheduling, timekeeping and task management, have access to volumes of valuable data, which can yield a wealth of analytical information to improve workforce optimization and labor allocation.

By deploying a workforce management solution with analytical capabilities,  retailers gain the ability to make better workforce management decisions, and track the effects of whatever adjustments they make. Analytics give to retailers the possibility to make continuous improvements, helping them to do more with less while delivering an optimal customer experience.

Labor is often the largest controllable operating expense for most retailers — frequently in the range of 12 to 15 percent of sales – so there are huge benefits to be gained through scheduling the right people at the right time at the right location to optimize the customer experience and maximize conversion of store traffic to sales.  Retailers know they need to optimize de in-store workforce in order to improve margins, and  store productivity.

While retail organizations have long used BI and analytics to optimize inventory, pricing, and other variables on a store by-store level, some organizations have been slow to extend efficient analytics into the richly promising area of workforce management.  Recent retail surveys inform that only 1/3 of retailers have purchase a workforce management solution with analytical capabilities or have prioritized it for the near future.

A recent Workforce Insight Retail Analytics Adoption Survey identified the top 5 benefits that workforce analytics provide to organizations.

  • 48 % accept that the WFM solution provide a productivity improvement, at the employee and store level.
  • 48% accept that they improve gross margin thanks to the WFM solution
  • 46% accept that they improve revenue notably since the WFM solution deployment
  • 40% accept a cost reduction thank to the WFM solution
  • 31% accept a risk mitigation with the WFM deployment

Analyzing that result, seems obvious that a WFM solution could provide a enough worthwhile benefits , but now the question is: What about the others retailers surveyed? What are stopping them to achieve this benefits?  The mentioned survey also identify the top 5 barriers that organizations are finding to achieve workforce optimization through analytics

  • 60% accept a lack of analytical bandwidth
  • 38% accept a substantial lack of data accuracy
  • 37% accept insufficient business cases
  • 35% accept a lack of executive sponsorship
  • 33% accept serious difficulties to obtain the data required.

In order to overcome those barriers and avoid their consequences is key to implement a WFM solution with analytical capabilities with the right third-party partner, only in this way retailers will achieve the identified benefits with guarantees, and improve their  decision-making capabilities around the workforce planning and scheduling.

All this data clarify that deploy a WFM solution is not enough by itself to reach the potential benefit that can provide to the organization. The deployment of this solution must be accompanied with a retail analytics strategy to accomplish all the solution value.  In this sense we identify some building blocks to reach a successful workforce optimization strategy.

  1. Leverage tools to collect data from multiple data points and create a data lake that could deliver actionable insight using advanced analytics models.
  2. Data is the base to achieve actionable insight, without quality data it is not possible to get any real value of any analytical tools. In order to guarantee results, define a data governance strategy, and implement it around all the organization
  3. Identify the direct impact of decisions in margins using  labor management KPIs during all the scheduling process.
  4. Join the predictive analytics capabilities to the prescriptive analytics in order to identify from  “what will happen” to “what should happen”.
  5. Select the right  third-party partner expert on this matter.
  6. Involved executives and managers play an essential role for success, it is important align their goals,  interest and expectations.

There is tremendous opportunity and value that is still untapped by many retail organizations to better leverage the increasing volume of workforce data to optimize workforce utilization. By identifying the most valuable KPIs related to workforce management and arming store operations with actionable insight, retailers have the opportunity to substantially improve performance — from customer satisfaction to profitability.

While labor represents the highest controllable operating expense, it’s also the retailer’s’ most valuable asset. With labor representing 10 to 15 percent of sales, retail organizations can enhance overall profitability by taking advantage of the workforce insights made possible through workforce management solution based in advanced analytics.

If you desire to read more articles about staff scheduling issues and how advanced analytics can help, you should register to our LinkedIn group “Performance Based Approach” or visit the blog section in our website.

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