Managing data at speed requires flexibility and agility
This is part six in a series focused on findings and insights from the IBM Institute for Business Value’s latest study and paper: “Analytics: The speed advantage - Why data-driven organizations are winning the race in today’s marketplace,” byGlenn Finch, Steven Davidson, Christian Kirschniak, Marcio Weikersheimer, Cathy Reese and Rebecca Shockley.
In part five we explored Acquire, the first of three key stages within the analytics lifecycle, which provides the ability to acquire and integrate data quickly—foundational to creating an analytics speed advantage. In part six, we will look at the study’s recommendations and practical actions for the Acquire stage.
The importance of flexibility and agility
To acquire and manage data at the speed necessary to create value, organizations need to focus on flexibility and agility.
Develop solutions that support data diversity
- Support a wide variety of data, both in motion and at rest, by integrating newer technologies with the traditional data infrastructure currently in place. The first step for many organizations is to create an enterprise data warehouse, the foundation for strong management of structured data. Then, extend or augment traditional infrastructure with new capabilities, such as a big data platform for landing a variety data quickly. Creating two stand-alone systems decreases the value of both.
- Focus on agility rather than conformity by creating landing platforms and data lakes to quickly ingest data and stash it until it’s needed. Break the habit of immediately trying to force everything into the warehouse; instead use the structured, unstructured and unformatted data together to accelerate speed to action.
Let data fuel your organization
- Provide access to relevant information to empower customer-facing employees and inform back-office operations. Collecting and analyzing data are fruitless activities if data is not delivered in a timely manner to those who most benefit from it.
- Foster rapid data consumption by recognizing that some data comes with an extremely short shelf life and must be dealt with immediately. For example, a customer’s public complaint can quickly compound discontent, while a sensor’s alert of a malfunction could quickly turn into an equipment failure if not addressed quickly.
Contrary to popular belief, governance equals acceleration
- Instill governance to improve quality and minimize rework. Business-driven information governance often appears to make data efforts slower, but, without it, data integration becomes an even more arduous task. The upside of information governance—the ability to contribute reliable, consistent and quality data to the analysis process—is so powerful that organizations simply can’t ignore it if they want to stay competitive.
- Enable enterprise consistency through a common business language. The first step to effective information governance is standardizing common definitions, codes and identifiers across functions, geographies and systems. The ability to quickly integrate data is stalled if data means something different to each user group or common tasks use inconsistent codes to capture data.
In part seven, we will look at Analyze, the study’s second key stage within the analytics life cycle, which focuses on analyzing the data and identifying the insights most likely to create a positive business impact. We will also identify the three capabilities that differentiate Front Runners in their ability to accelerate data analysis