To get the full business value from big data, companies are focusing less on the three Vs of big data (volume, velocity, variety) and more on the four Ms of big data: Make me more money! New sources of data, coupled with advanced analytics, can improve customer engagement, optimize business processes and point to new monetization opportunities.
A recent Forrester study by Brian Hopkins and Fatemeh Khatibloo highlights the critical role of a business-centric focus in the big data discussion. Hopkins and Khatibloo argue that technology-focused executives within a business will think of big data as a technology and fail to convey its importance to the boardroom.
Businesses of all sizes must reframe the big data conversation with stakeholders in the boardroom. The questions are, where exactly should businesses focus their big data capabilities and how do we define the realm of what is possible?
Before you begin these discussions, you must assess your level of big data maturity. Companies tend to be at one of four phases:
- Business monitoring. Leveraging basic analytics to assess company performance and alerting relevant members of your organization.
- Business insights. The evolution of monitoring, business insights are gleaned when stats, predictive analytics and data mining are used to inform business processes and improve performance.
- Business optimization. As a business begins to glean insights, they can begin to use analytics to automatically optimize certain aspects of business operators. An example of optimization is a retailer that could automate product pricing based on purchase patterns, inventory and social media insights.
- Data monetization. The level of business maturity where organizations are trying to sell data to other organizations, integrate analytics into products to create new levels of intelligence or leverage insights to improve the customer experience.
Organizations of all sizes, across all industries, are at varying points on the maturity curve. That’s not stopping them from pushing forward on their big data journeys. Think of a credit card company creating location-based offers, a high-tech manufacturer improving supplier quality and reliability, an energy producer reducing costs through preventive maintenance or even a public school improving student performance while increasing teacher retention. All these organizations are leveraging new sources of data, coupled with advanced analytics, to uncover new insights about their customers, products, campaigns and students to optimize key business processes and uncover new monetization opportunities.
Companies like John Deere are also on a big data journey. According to Forrester, the company is planning to arm farmers with data-driven insight using weather, geography, soil composition and seed genetic data. With that type of information, farmers will be able to better understand what, where and how to plant crops to yield more bushels per acre.
Whether you’re a small/mid-sized business or one of the world’s largest legacy manufacturers, there are four lessons that can be learned when approaching big data.
1. Develop and feed an insatiable appetite for data. Whether through sensor or purchased, data is good. More data is better. You need to identify the relative value of the data with respect to the targeted business initiative.
2. Intimately understand your targeted users. Invest time to capture your target’s key business processes, and then decompose each process into its supporting decisions, questions, and data sources.
3. Visualize the user experience. Be bold and audacious. Create a compelling vision for the targeted users and set a high bar for the organization. Start with a simple dashboard, make it more actionable, ensure that actionable insight is readily apparent, and make it “iPod simple” (one button to execute) to take action.
4. Focus on the business. Take time to identify where and how new sources of customer, product and operational data can be coupled with advanced analytics to optimize key business processes, improve customer engagement and uncover new monetization opportunities. Leverage envisioning techniques and collaboration between business stakeholders and key IT personnel to identify use cases that can deliver meaningful and actionable business insight in six to nine months.
Ultimately, big data only matters if it can help organizations improve the business and make more money by increasing customer acquisition, reducing customer churn, reducing operational and maintenance costs, optimizing prices and yield, reducing risks and errors, improving compliance and more.
Remember that no matter the size of your business, you don’t need a big data strategy. You need a business strategy that incorporates big data.
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