Inside the Analytic Mindset: Creating the Data You Need By John O’Brien | Principal and CEO, Radiant Advisors May 8, 2013 Reprinted with permission of 1105 Media, Inc. There are many differences between a business intelligence (BI) mindset and a business analytics (BA) mindset. Business analytics focuses on designing an algorithm that achieves a specific business objective by leveraging data as variables. Analytics developers typically work separately from BI and data warehousing teams and seek out data that builds an analytic model to achieve business objectives. Although a business intelligence mindset is frequently concerned about where the data comes from, a BA professional analyzes and leverages data from the data warehouse, operational systems, external data, and user-generated data, and in some cases considers how to create the data needed. A new role should be created in BI/BA teams for creating applications that generate the required data. For example, many years ago while performing operational analysis for a major bank, we needed to capture deposit and check volumes arriving at our centralized facility so our 100-plus staff could micro-encode, balance, and batch them for the clearinghouses. Each staff member had different throughput rates and quality levels. In order to capture the data needed, a very simple—albeit crude—method was used: a yardstick taped to a countertop. We measured the stack of checks in inches, translated one-inch thickness as 100 items, and recorded the arrival time stamp and branch number. With that daily data (and years of history), we accurately forecasted workloads and optimized staff levels, rewrote courier pickup routes to save 40 percent in expenses, and analyzed business changes such as new banking hours. The BA mindset here: sometimes having data is more important than its accuracy. Think outside the box and own the responsibility for creating the data you need. Throughout the years, this BA mindset has served well to solve the lack of sales channel data at major wireless carriers for telecom metrics, and, more recently, at one of the largest Internet carriers for monitoring its network. There, our BI team wrote our own applications to be installed on thousands of servers and network switches. The applications monitored network traffic every second, captured those metrics, and then aggregated them into five data packages to be shipped to a central collection manager program. Now we could monitor the massive network in real time. In this case, the BA mindset was to write a small agent program to distribute across the infrastructure and machine-generate the data we needed to solve the business challenge of operating a network. If you look around carefully, you’ll discover how major technology companies are creatively building new ways to capture the data they need for business analytics as well as to become a business that runs on information. Google has long been recognized for analyzing the Web and constantly improving with user behavior data. I recently noticed the Google Chrome browser now leaves a blue strip on the website I’m reading as I scroll—Google is at it again, capturing how I read websites. Recently, it was reported that Amazon captures all the data from its Kindle e-readers and downloaded books, such as book titles, reading speed and frequency, highlights, book abandonments rates, and more—all great data for e-book analytics and the publishing industry. In recent discussions with BI vendors, I asked why they don’t offer the data that captures how reports and BI applications are being consumed. With this information, BI teams could optimize their programs by analyzing which BI apps are used most often, which screens and widgets are most popular, which metrics are drilled through most often and through which path, and so on. Leveraging database tools to capture SQL queries is not enough; asking users to add comments (or ratings) is asking too much. The BA mindset is to take the initiative to instrument and capture BI user behavior without imposing on users.
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The next time you’re faced with a BI or BA project, don’t limit yourself to the “what data do we have in the operational systems” mentality. Think about your business objective and what data you need in order to deliver analytics and useful information to business users. Then think about how you can creatively generate that data yourself, rather than relying on other applications or development teams. --John O’Brien, CBIP is principal and CEO of Radiant Advisors, a strategic advisory and research firm that delivers innovative educational materials, publications, and industry news. You can contact the author at john.obrien@radiantadvisors.com.
www.RadiantAdvisors.com
© 2013 Radiant Advisors, All Rights Reserved