Data Strategy – Nailing It & Why It Really Matters

By Dr. Somdutta Singh

With rapid advances in AI and data science, data has become an essential asset to every enterprise. Setting up a data strategy, therefore, has become every enterprise’s mission, particularly in the C Suite and at Executive levels.

What is a data strategy and how do we create the right data strategy?

Data strategy defined

A data strategy is a common reference of methods, services, architectures, usage patterns and procedures for acquiring, integrating, storing, securing, managing, monitoring, analyzing, consuming and operationalizing data. It is, in effect, a checklist for developing a roadmap toward the digital transformation journey that companies are actively pursuing as part of their modernization efforts. This includes clarifying the target vision and practical guidance for achieving that vision, with clearly articulated success criteria and key performance indicators that can be used to evaluate and rationalize all subsequent data initiatives.

Key takeaway: All aspects of a data strategy should be agile and deliver frequent, iterative value to the business. Such agility enables the strategy to evolve over time, changing as the organization changes and allowing for input and recommendations from all levels of the organization.

 

The data strategy vision

All organizations make decisions about how they engage with, operate on and leverage their data — whether at an enterprise or project level. Companies that form a holistic point of view in adopting an enterprise-grade data strategy are well positioned to optimize their technology investments and lower their costs. Such a strategy treats data as an asset from which valuable insights can be derived. These insights can be used to gain a competitive advantage by being integrated into business operations.

Organizations that want a smooth transition to becoming data driven — aligning operational decisions to the systematic interpretation of data — need a plan for advancing their digital transformation journey and treating data as a corporate asset. Creating a data strategy is the first step toward enabling such a plan and increasing the organization’s Analytics IQ. This term refers to an organization’s ability to deploy advanced analytics at every point of interaction — human as well as machine — to continuously improve decision-making quality and accuracy.

The key elements of a good data strategy

To create a robust data strategy, business leaders need to consider many factors. Here are the critical points I would expect to see in a strong data strategy:

• How are you meeting your data needs? In order to find the right data for you, you must first define how you want to use data. You may need certain types of data for some goals and different types of data for others.
• How you will source and gather the data? Having identified what you are looking to achieve with data, you can now start to think about sourcing and collecting the best data to meet those needs. There are many ways to source and collect data, including accessing or purchasing external data, using internal data and putting in place new collection methods.
• How that data will be turned into insights? As part of any solid data strategy, you need to plan how you will apply analytics to your data to extract business-critical insights that can inform decision making, improve operations and generate value.
• What are the technology infrastructure requirements? Having decided how you want to use data, what kind of data is best for you, and how you might want to analyse that data, the next step in creating a robust data strategy is considering the technology and infrastructure implications of those decisions. Specifically, this means deciding on the software or hardware that will take your data and turn it into insights.
• What are your data competencies within your organisation? In order to get the most out of data it is essential to cultivate certain skills. There are two main routes to developing data-related competencies in your organisation: boosting your in-house talent and outsourcing the data analysis.
• What about data governance? Collecting and storing data, especially personal data, brings serious legal and regulatory obligations. Therefore, it is vital any organisation factor data ownership, privacy and security issues into their data strategy. Ignoring these issues, or failing to properly address them, could see data go from a huge asset to a huge liability.

Here are my final thoughts. In business, information is power, and Big Data is providing information we couldn’t have dreamed of collecting or analysing just a few short years ago. With the massive growth in Big Data, plus the rapidly evolving methods for analysing data, the importance of data across every aspect of business will only increase. Those companies that view data as a strategic asset and develop robust data and analytics strategies are the ones that will succeed in this new data-driven world.