CDOs Need an Offense-Defence Data Strategy

There’s truth in the old saying, “Offence sells tickets; defense wins championships.” Part of building a sound data strategy and a strong data-management function is the notion that organizations are going to rely on strategies that can be viewed as either growth-driven (the “offensive” approach) or risk-mitigating (“defensive”).

Chief data officers need to maintain security and compliance via sound data strategy and execution, touching all areas of the organization. According to IDC, 40% of businesses on A2000 (Asia-based 2000 businesses) will begin adopting multi-cloud data logistic platforms that enable enterprises to actively migrate data between hyper-scalers to optimize costs, reduce vendor dependence and improve governance. An effective multi-cloud data strategy will therefore require both offensive and defensive stances.

Reasons to adopt an offensive and defensive mindset

An effective CDO must focus on building a data-driven culture to propel the digital transformation and innovation processes that drive growth. At the same time, they must also apply prudent data management strategies to reduce costs, increase reliability and ensure compliance with privacy and security standards.

In evaluating the strategy, businesses in highly regulated industries with a dominant focus on IT security will focus more on the defensive side, emphasizing compliance and risk mitigation. This is common in the financial, insurance and healthcare spaces.

An offense-driven strategy will emphasize data management, optimizing analytics and data-driven insights for market competition. Retail, travel and entertainment businesses will look to data for its analytics capabilities and the ability to drive innovation and change. 

Businesses usually deploy a combined offensive and defensive strategy for their data platform, driven by their business focus. Both strategies are equally important, and companies need to find the balance between these two methods so that the enterprise can reap the best of both worlds.

DEFENSIVE: Secure, quality data at a reasonable cost
A defensive strategy is more than just security. It also focuses on cost efficiency. While all businesses are interested in securing their data at a pragmatic cost, a defensive strategy empowers them to maintain high data quality for their operations. Some defensive measures include:

• Address compliance and regulatory requirements
• Prevent cyberattacks/data breaches
• Ensure data quality through data governance
• Employ analytics to detect and limit fraud

OFFENSIVE: Use analytics to generate revenue opportunities
An offensive strategy focuses on innovation and marginal gains in data democracy, which can sometimes come at the expense of data quality. Speed is the name of the game, and the ability to utilize data to improve customer experiences and operational efficiencies and make better choices is what an offensive strategy is all about. Managing this flood of data generated can be taxing on human resources, and a better solution is to leverage software that enables the business to:

• Increase the value of company data
• Apply sophisticated, real-time analytics
• Respond quickly to markets and competitive activity
• Generate a return on investment in big data and analytics infrastructure

Fundamentals come first

Just as in a sports team’s playbook, a successful offensive play is made possible only with a strong defense. Discipline comes first.

The business can employ leading-edge technologies like AI and machine learning in creating data pipelines. Companies that cannot manage their data quality, governance and cost cannot rely on the results of their analysis. 

Which risk mitigation mechanisms are part of your organization?

• Access controls (zero trust)
• Data security (encryption, confidentiality, reporting)
• Data governance (catalog, lineage, stewardship, data quality, master data management)
• Access controls (zero trust)
• Compliance (GDPR, CCPA, HIPAA, SOX, SOC2 and others)
• Cost Management
• Ethics and data bias in AI

Businesses without the fundamentals and the building blocks in place will struggle to drive the adoption of analytics at scale in their organizations. Therefore, an effective playbook will help the business balance innovation and adoption (offense) with control (defense). This is important since businesses may need to pivot between these roles frequently.

For example, such capabilities enable the business to shift periods of rapid experimentation and innovation, using data to stabilize and build resiliency once the AI models are field tested and ready to use at scale. Focus and investments will shift according to business needs, priorities, situations, timing, and immediate strategy. No matter which industry a company operates in, it will constantly shift across the offensive/defensive spectrum.

Having true self-service analytics capabilities in the business

For internal stakeholders to harness self-service analytics in the business, it is imperative to ensure that the data supply is reliable, secure and compliant. This is achieved when everyone knows the meaning and context of the data assets (catalog). These assets can then be used seamlessly, extracting information from them becomes reliable, repeatable and consistent globally every time.

That’s when leaders gain confidence and can encourage a data-driven culture, ultimately leading to winning teams.

The ultimate business goal: A balanced strategy

For businesses to be truly effective, they must find an equilibrium between creating a single source of truth that enables them to be agile and innovative. Consolidating data in disparate systems and making it accessible and functional for customer-focused functions like sales and marketing in real time must be the priority of CDOs.

With both offensive and defensive moves being intertwined and inseparable in the business, the transformation process must arrive at a middle ground that enables the company to win with internal and external stakeholders. This requires a commitment to build a stronger data strategy and data management capabilities that align with the business objectives to realize growth, control and flexibility.

Hemanta Banerjee, the vice president of public cloud data services at Rackspace Technology, wrote this article.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/gorodenkoff