Data-driven decision making: how to make it?

Data-driven decision making: a practical guide

Data-driven decision making applied in the business context

In the business context, every decision counts. In fact, the fate of a company may depend on the right choice. Data-driven decision making has become a priority to drive bold and visionary strategies.
But what is this process, is it really that important for your organization, and how can it be applied in a BPO and Contact Center company? Here are the answers to all these questions.

 

Data-driven decision making

Data-driven decision making consists of using quantitative and qualitative information to make informed decisions. Unlike decisions based on intuition or hunches, this practice is supported by business analytics. In this way, organizations manage to discover patterns, trends and hidden opportunities (UC Innovation Center, 2021).
The importance of this approach lies in the fact that it allows BPO and Contact Center companies to operate with a clear vision. That is, to align actions with market needs and customer expectations. It also provides a solid foundation for optimizing operational efficiency and improving the quality of services (Conexión Esan, 2021).
 

Practical guide for data-driven decision making

This involves a methodical and strategic approach, as detailed below.

  • Collect and clean relevant data. Identify what information is needed for the analysis. The collection should be from reliable sources. Subsequently, perform data cleaning to remove outliers, errors, and duplicates.
  • Apply statistical analysis techniques. Apply appropriate statistical techniques to obtain meaningful insights. This may include descriptive, inferential or correlation analysis, depending on the objective (ESIC, 2022).
  • Interpretation of results. Data often provide valuable information, but without proper understanding, they could be misinterpreted. That is, rely on qualified professionals who know what insights are and how to make an accurate interpretation.
  • Data visualization. Display results using graphs, charts or other visuals. Also, make sure that complex data is presented in a simple way. The idea is to be understandable, regardless of the type of audience (UNIR, 2021).
     

Application at all levels of the organization

Integrating a culture of data-driven decision making at all levels of the organization translates into success and efficiency. Follow these practical tips to achieve it.

  • Promote education and training for all employees in related programs, regardless of their role in the company. Keep up to date with the latest trends and analytical tools (GOV.CO, 2021).
  • Encourage the use of data in decision making. Establish clear metrics and KPIs to measure performance. Guide decisions at every level of the organization.
  • Implement appropriate tools and systems. Adopt customized technology strategies and platforms that facilitate data collection, analysis and visualization.
  • Appoint leaders with data analytics skills who can guide and support teams through the process.
  • Conduct periodic reviews and adjustments to evaluate the effectiveness of the implementation of such culture (CETYS University, 2020).
     

Transforming the user experience

Data-driven decision making for social listening in networks achieves the transformation of experiences for all end users in the chain. In this sense, it is necessary to analyze interactions and comments on social networks.
 

Thanks to this process, a deep understanding of the needs and preferences of the public is obtained. Adopting new strategies, improving products or services, and offering personalized responses are also possible. It is important to generate a meaningful and enriching connection. It is about satisfying users' expectations and strengthening brand loyalty (Narvaez, s.f.).
 

In conclusion, this is the foundation that drives BPO and Contact Center companies toward a promising future. As a result, achieving operational excellence and customer satisfaction is now entirely possible.