twitter facebook linkedin instagram vimeo arrow-down
Jeff Marinstein


Recent Posts



Data-Driven Business Strategy

Big data and analytics have the ability to transform company operations and influence client interactions. As a result, both are at the top of the corporate agenda. In the search for value, companies have relied on adding new capabilities and assets, studying historical customer behavior patterns, and following major business trends. Traditional business strategy and planning were once static processes performed annually, if at all.  Leaders in today’s customer-centric ecosystem create value by mining data and conducting analysis in real time. Business strategy is dynamic, ever evolving and driven by insights from data.

The emergence of data-driven business models is helping companies deliver performance gains not seen since the 1990s when core processes were reengineered. A study by the University of Cambridge showed that data-driven businesses have output and productivity gains that are 5-6% higher than companies whose processes are not data driven. The use of analytics to extract insight and embed it back into organizational processes is a key enabler of business transformation.

The development and execution of a data-driven business model requires several key elements. These include:

  • Strong technology leadership. The CIO and/or CTO must work closely with business leaders to ensure there is a focus on business value creation. C-suite executives must embrace a corporate culture that enables the use of data-driven decision-making.
  • A willingness to consider outside perspectives. These can come from customers, suppliers, partners or people in other industries. When studying customer behaviors these outside parties may provide data, insight and help speed offerings to market.
  • Strong executive sponsorship and leadership. Some analytic programs simply enhance existing business. Others are highly disruptive and require a new business model or a separate business unit to support them.
  • The skills to carry out strategy, statistical evaluation, and modeling of complex data sets. These skills need to be placed within marketing, sales, finance and other functional areas and complement existing teams.

The lack of strong data management skills may limit the ability to curate, merge and maintain multiple sources of data. Technology must be in place to handle processing, storage, and analysis of large volumes of data. In many cases these investments can be costly and require IT processes and systems to be redesigned.  

Best practices in data-driven business strategy can often be found in technology-driven companies. Indeed is an example of a company with a data-driven business model. As the world’s #1 job site, Indeed’s mission is help people get jobs.’s websites attract over 200 million unique visitors every month from over 60 countries.

Many external factors impact Indeed. For example, changes in the labor market and the complexion of the workforce based on the outcome of elections are reflected in the underlying data from job seekers and job listings. To get the most from this large amount of information Indeed has embraced a culture that trusts the data. This is key to their success. Business leaders have been trained to use data to make key decisions. Business strategies are supported by data.

Key principles allow them to use data and analytics effectively. They continually expose metrics to improve team performance, and they use data (internal and external) to understand the behaviors that matter most to each segment of their client base. Business strategists, analysts, and managers are trained in all aspects of data analysis and know the KPIs that drive their business.

IT and the lines of business each play a unique role. IT is responsible for providing the infrastructure, tooling, and data model. Each line of business has dedicated strategists and analysts to drive business decisions and improve the customer experience.

As they continue to grow, the volume and velocity of data create unique technical challenges. Indeed found limitations in traditional data query and analytic products. In response they developed Imhotep, a system for large-scale analytics and machine learning which allows them to execute complex queries on large data sets in near-real time. Indeed is a great example of a company pushing the boundaries of big data and analytics and succeeding with a data-driven business strategy.

This blog was co-authored by Jeff Marinstein and Brian Gavin, Customer Experience and Strategy consultant.

Leave a Reply
Your email address will not be published. Required fields are marked *