Competition is everywhere, from our workplace to the reality television we watch. Concurrent with competition is escalating complexity: Industry analyst firm IDC predicts enterprises may have 10 times today's data by 2013, 100 times by 2018. (John F. Gantz et al., "The Diverse and Exploding Digital Universe: An Updated Forecast of Worldwide Information Growth Through 2011," March 2008.)
Enterprise applications like SAP have improved business efficiency. However, if your competitors have the same applications, where is the substantial advantage? Business intelligence (BI) and analytics help you make better decisions. But again, your advantage narrows because these are increasingly commonplace.
Today, the difference making the difference is agility. Moving faster and changing course when appropriate-based on accurate and timely information-keeps you ahead of the competition.
Unfortunately, moving fast is difficult for most enterprises today because they have large operations to run, huge security challenges to master, and massively complex data systems to harness. Fortunately, emerging technology, known as data discovery, is changing the game. Data discovery lets business analysts, managers, and analytic professionals answer new questions, resolve problems, and make decisions faster.
What data discovery is and who uses it
How many times have you thought or said, "I know the information is somewhere, I just don't know how to get to it"? If you're lucky, existing BI reports deliver what you need. Or, you're technically savvy and can use SQL or a report writer to build a report. With sufficient time and funding, you can ask for IT help. What about the rest of the time? Data discovery combines BI's powerful information support with search's reach, ease, and speed, meeting ad hoc information needs with minimal to no IT support. As a result, sales managers can understand their customers' buying patterns to gauge their appetite for a new product. Marketing managers can accurately judge the initial impact of a new promotion and fine tune accordingly. Customer service managers (CSMs) can respond intelligently to customer issues before they escalate beyond repair.
How data discovery works-an end-to-end example
Consider a CSM who wishes to determine why her customer is missing deliveries, to quickly return this customer to "green status."
Without data discovery, she scans order, shipment, inventory, and invoice reports hoping the problem becomes apparent. If it doesn't, she contacts IT to produce a custom query. This may not return immediate results, however, because IT typically has a project backlog, and the CSM may not know what to ask for initially, requiring several iterations of queries before the problem is solved. With data discovery, the CSM has a more direct path from question to answer.
Step 1: Search Enterprise Data
The CSM searches across the enterprise systems for data about the customer, and his/her purchases, shipments, and deliveries by entering the customer's name in the data discovery's search box.
Step 2: Understand the Complete Picture
Selecting from the relevant data returned, the CSM pulls together a complete, 360-degree view of the purchases, shipments and deliveries using data discovery's capabilities for combining row and column data in a spreadsheet-style workspace.
Step 3: Drive to the Answer
Drilling into the specific shipments where there are no corresponding deliveries, the CSM determines actual cause using data discovery to find and access data relationships. In this scenario, the common thread turns out to be shipments from the Long Beach warehouse with an improper "ship to" address.
Step 4: Communicate the Results
The CSM can now export the analysis into Microsoft Excel for a nicely formatted snapshot with summary statistics on correct shipments (to reinforce the positive), also demonstrating that the delivery problem was a minor correctable data entry error.
Step 5: Use the Insights to Improve Future Performance
Leveraging community features, the CSM packages the Excel report and its supporting data queries and user notes, saving it in the best-practices repository. If warranted, the CSM sends the report to IT to show requirements for a new "undelivered shipments" report alert to avoid this problem in the future.
Getting started with data discovery
Data discovery is useful for a range of analysts, managers, and analytical professionals because it supports the data in your existing backbone transaction systems and data warehouses. So, while you can start almost anywhere, a win-win scenario is to "follow the money" and choose a revenue-oriented project first for immediate delivery of ROI.
Data discovery tools delivered as an appliance or via a software-as-a-service (SaaS) model can be quickly installed. Look for data discovery tools that leverage automated relationship discovery rather than those that require large, up-front investments in data modeling, natural language mapping, and other manual activities.
In today's complex and competitive world, savvy analytical professionals can use nascent data discovery technology to find the information they need to keep their competitive edge.
About the Author
Robert "Bob" Eve is currently the vice president of marketing for Composite Software, Eve has held executive positions at Oracle, PeopleSoft, Mercury Interactive, and Informatica.
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