Finding the balance between "offense" and "defense" is critical in any situation. Knowing when to be proactive (and when to take a step back) can be the difference between success and failure; closing a deal or not.
For marketers, however, it's critical to start thinking offensively. With all the transformations happening in today's world (digital, social, technological etc.), it's imperative that companies are continually innovating in order they want to stay relevant to their customers, and keep them from taking their business elsewhere.
In general, marketing organizations are relying on a “defensive data approach.” While suitable for many other parts of an organization, it doesn’t provide marketers with the tools necessary for success. The time has come for a strategic shift to offensive data analytics.
A recent HBR article, “What’s Your Data Strategy,” does a wonderful job of outlining the concept of “offensive” data—and don’t worry, it doesn’t take a data scientist to understand the key points.
From a CMO perspective here are some of those key points:
The “plumbing” aspect of data management is the responsibility of all C-suite executives.
- More than ever, the ability to manage torrents of data is critical to a company’s success
- Most companies remain badly behind the curve
- Cross-industry studies show that, on average, less than half of an organization’s structured data is actively used in decision making—and less than 1% of its unstructured data is analyzed or used at all
- The “plumbing” aspects of data management may not be sexy, but they’re vital to high performance. As such, they’re not just the concern of the CIO and the CDO; ensuring smart data management is the responsibility of all C-suite executives
Defense Versus Offense
- Data defense is differentiated from offense by the distinct business objectives it supports, as well as the actions required to achieve these goals
- Data defense is about minimizing downside risk. Activities include ensuring compliance with regulations, using analytics to detect and limit fraud, and building systems to prevent theft
- Defensive efforts also ensure the integrity of data flowing through a company’s internal systems, and is used by legal, financial, compliance, and IT departments
- Data offense focuses on supporting business objectives such as increasing revenue, profitability, and customer satisfaction
- Offensive data typically includes activities that generate customer insights—for example, data analysis and modeling—or integrate disparate customer/ market data to support managerial decisions
- Offensive activities tend to be most relevant for customer-focused business functions, such as sales and marketing, and are often more real-time than defensive work
- Every company needs strong offense and defense to succeed
The Elements of Data Strategy
|Key Objectives||Ensure data security, privacy, integrity, quality, regulatory compliance, and governance||Improve competitive position and profitability|
|Core Activities||Optimize data extraction, standardization, storage, and access||Optimize data analytics, modeling, visualization, transformation, and enrichment|
“From “What’s Your Data Strategy?” By Leandro Dallemule and Thomas H. Davenport, May–June 2017 © HBR.ORG
From my perspective, traditional, manual Big Data efforts—driven by data scientists and engineers—are best suited for defense data initiatives. To get offensive, marketers must adopt new techniques, including AI and machine learning, to automate the curation and analysis of customer data. It is in this way, that companies will be able to know and interact with their customers in an effective and mutually beneficial manner.