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For a global apparel manufacturer, developing advanced analytics capabilities is essential to achieving its growth strategy.
It called upon Accenture again to help define the appropriate operating model and talent required. Accenture collaborated with the company to design a new “hub and spoke” organizational structure and governance model, deliver a forward-looking talent strategy to help scale its analytics capabilities, and develop a three-year implementation roadmap for North America as well as a framework to scale globally.
The company had worked with Accenture to develop an enterprise analytics roadmap for North America, but found that its existing organization lacked a clear structure, alignment and accountability to put the roadmap in motion at the pace required.
Although Accenture had already helped develop an enterprise analytics roadmap for North America, the company’s existing analytics organizational model lacked a clear structure, alignment and accountability to put the roadmap into action.
Analytics knowledge was scattered throughout the company’s business units, providing few synergies in terms of data, tools and talent, but especially insights.
With analytics talent at a premium (demand surpasses supply), the company needed a plan to hire and develop the appropriate talent in key areas. It engaged Accenture to help create an integrated analytics operating model and talent strategy that could scale advanced analytics effectively and efficiently across the company.
In a fast-paced yet thorough way, Accenture collaborated with the company to define the operating model and talent needed to execute its enterprise analytics roadmap. Together, they:
Assessed the existing analytics organization, capabilities and talent management. This information, gathered via stakeholder interviews, surveys and workshops, offered insights into how the analytics organization could be structured for maximum impact. It also identified potential opportunities to source, maintain and grow analytics talent.
Developed a “Fit for Purpose” organizational structure, including detailed roles and responsibilities. The new structure allows for some centralized control and oversight of analytics operations while giving business units and brands the flexibility to innovate and collaborate on strategic insights.
Defined talent strategy for how the company could scale its analytics capabilities, including analytics talent sourcing options and potential career paths for analytics experts.
Created a three-year roadmap for implementing the new operating model and talent strategy for North America and a framework to scale it globally.
The team quickly established the new analytics operating model that the company has now put in place. As a result of the work, the company now has:
A roadmap to scale analytics: Business units across the company now have a clear structure—outlining roles, responsibilities, governance for the Analytics Center of Excellence, business functions, and IT organization—to scale analytics efficiently and effectively.
Ability to improve cross-functional synergies: With the new operating model, analytics professionals can build connections across teams to coordinate analytics priorities and standardize tools and processes. For instance, within the new model, analytics professionals within the company’s R&D organization work more effectively with those in marketing on new product launches or with supply chain management on improving product delivery.
A pathway to value: The company is now able to invest confidently and more aggressively, supported by a clearly defined path to build analytic capabilities. Highest value capabilities have been prioritized which reduces the likelihood that other parts of the organization are making overlapping investments.
“Quick wins” to self-fund the journey: Eliminating inefficiencies like redundant reports and tasks across the analyst base provide seed funding for the company’s analytic journey.
The new model and talent strategy can help the global apparel manufacturer mature and expand analytics adoption to improve innovation, market expansion, sales and analytics return on investment.
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