Do you agree that information is power? With this premise in mind, let’s discover how businesses should implement a data-driven system to achieve success. People are used, because it’s natural, to make decisions based on gut feeling and experience, and they generally rather privilege qualitative data, not quantitative. Despite this human tendency, those companies who care about sustaining their decisions based on data are a few steps ahead – improving their edge over the competition.

 

Data-Driven Decision Making

Making strategic and operational decisions based on data analysis and interpretation leads to more accurate outcomes compared with intuition alone.  Businesses with this methodology use information derived from data to guide their choices. It involves collecting, analysing, and interpreting relevant data to gain insights that inform decision-making.

By analysing data, companies can identify inefficiencies and optimise processes, which causes, organically, overall efficiency and productivity improvements.

 

Understanding Better Client’s Needs

Data-driven insights allow businesses to identify trends, predict future outcomes, and make more informed strategic decisions. To understand better their customers, businesses must comprehend their preferences, behaviours, and needs – leading to more targeted marketing strategies and improved customer satisfaction. Organisations that leverage data effectively gain a competitive edge by making smarter decisions, and faster than their competitors.

Fully understanding the desires and concerns of their clients, enables businesses to forecast results. They can utilise statistical models and machine learning algorithms to predict future trends and outcomes based on historical data.

 

“The Heart of All Decision-Making”

Most businesses believe data is the core of the criteria needed to take action in different fields of business. A study conducted by EY (Ernst & Young Global Limited), found that 81% of businesses agree that data should be at the “heart of all decision-making”.  Data-driven businesses are also 23x more likely to acquire customers, 6x more likely to retain those customers, and 19x more likely to be profitable.

A total of 270 senior executives responded to 27 questions on all aspects of their data strategy. Around 68% of respondents are active stakeholders in big data projects, and all departmental functions and industry sectors are represented, with most respondents working in finance, marketing, and IT, as well as in cross-departmental management roles.

73% guaranteed to understand customers better, 72% to improve products and services, 47% to improve the management of existing data, and 41% to create new revenue streams. 40% said data is a necessity for their business model, and 20% emphasised the detection and prevention of fraud as an improvement.

 

Project Management Methodologies: Business Intelligence

Traditionally, Business Intelligence (BI) focuses on gathering, storing, analysing, and presenting historical data to support decision-making. This method is slightly different from the data-driven approach, which has a broader scope. This second concept encompasses not only historical data analysis but also the proactive use of data to guide strategic planning, operational processes, and innovation.

While BI and data-driven businesses share similar objectives in leveraging data for decision-making, data-driven businesses go beyond traditional BI. They embrace a more proactive and holistic approach to data utilization.

Data-driven businesses prioritise real-time data analysis, predictive modelling, and a culture of data-driven decision-making across the entire organization to drive innovation and achieve competitive advantage.

 

 

Agile methodology

The name is self-explanatory, agile methodology focuses on iterative development and continuous improvement. By leveraging data analytics, teams can analyse metrics such as user feedback, performance indicators, and market trends to adapt project requirements and priorities dynamically.

Agile methodology promotes transparency, accountability, and informed decision-making. By emphasising estimation, traceability, and velocity tracking, teams can drive continuous improvement, adapt to change, and ultimately achieve greater success in their agile projects.

 

How Major Brands Are Using Data

Google with its popular search engine has developed several open-source techniques and tools to explore their target. The company uses big data analytics to understand better the customers based on parameters, such as search history, trends, locations, and more. The search engine ultimately shows the ranked or sorted search regarding authority and relevancy designed to match the user’s requirements.

Spotify never underestimates the importance of big data analytics. The streaming platform hosts more than 200 million users and has a lot of information to explore. Spotify launched “Spotify for Artists”, an app that uses data analytics to provide valuable information about their listeners: behaviours and preferences, including, for instance, the cities where their music is saved and streamed.

 

Netflix is one of the biggest online platforms for streaming by using data analytics. The company collects customer interactions and behaviours while watching the shows. For example, Netflix can find the date a specific episode of a series was watched, if customers saw the full episode, or just a segment, etc.

They make every possible decision with this information, including predicting what users want to see next or creating new original content.

 

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