P&G: The Development of the Data Government and Management Strategies

Subject: Case Studies
Pages: 2
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Study level: Master

P&G Case

P&G continues to be the leader in sales of household chemicals and cosmetics for body and health care, including baby, home, and fabric care products. P&G relies heavily on large retailer stores, with Walmart responsible for 15% of the revenues (Datar et al., 2020).

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Smaller, local stores are also a critical part of the chain. Product differentiation allows P&G to be a leader because the company is heavily investing in developing different product lines, working on brand communication, packaging, household penetration, and value proposition. P&G operates in North America, Europe, Latin America, Greater China, and AMA (Asia Pacific, Middle East, and Africa). As a non-native in the digital world, P&G faced the need to create a customer data management system and optimize that system. This decision suggested the development of the data government and management strategies and the data ecosystem creation.

The company launched the Friends of Data Science program, appointed a direction manager, and hired analyst scientists who developed an effective digital structure that could be used by managers across departments. The scientists also conducted several local experiments to determine the most effective way to invest in product innovation and product presence on store shelves. Today, P&G faces new challenges related to the analytical education of its employees and data capability. The need for more comprehensive integration stems from increasing digitalization, and the responsibility for implementation lies with the Friends of Data Science team.

Impact of Technology

In the presented case, technologies play a central role since it directly examines the impact of data management on the development of a company’s business. Interestingly, P&G continues to develop innovative smart solutions for their products that lie at the intersection of health care and electronics. For example, innovative solutions for Oral-B Genius electric toothbrushes and Airia aroma oil diffusers have combined the shopper experience with related applications to take the consumer to the next level. Through Airia and Oral-B Genius apps, the P&G technology team has provided deeper engagement and stronger customer relationships.

Other Issues

Separate consideration deserves a structured and thoughtful approach to managing and organizing data and how data is used to make informed decisions about merchandising and investment in innovation. For example, decisions on the distribution of supply and sales of shampoos for multicultural hair types were made based on consumer preference data, which could be unexpected. This type of data manipulation can be promising since preferences are often linked, and the consumption of some goods can warrant the consumption of others. Another exciting area is an investment in innovation based on consumer habits, especially considering the possibilities offered by smart products. The advice offered by technology can help build stronger relationships with tech-savvy consumers and increase brand loyalty.

Recommendations and Ideas

Given the information above and the case analysis, several recommendations can be offered. First, P&G should continue to develop its data ecosystem by providing training for managers and other employees. Ideally, retailers can train employees to use apps that offer specific, local data on shopper habits and preferences. The application may contain optimized tips on discounts, promotions, and similar or related products that store employees will voice when purchasing or send in the form of chat or SMS messages through the application. The study of the market demand is also promising and can be optimized by working with customers through social networks. For example, a company can purchase data provided by social media to produce targeted ads.

Reference

Datar, M.S, Mehta, S., & Hamilton, P.J. (2020). “Applying data science and analytics at P&G.” Harvard Business School, 7(1) pp. 1-20.

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