4 steps towards achieving your analytics "yield of dreams"
Turning analytics into captured value (return on investment, or yield) is no easy task. Through years of trial and error, our internal consulting team has worked with a diverse set of cross-functional IBM client teams to explore how analytics can most effectively drive business outcomes. From sales to marketing to operations and beyond, we have learned much about what works and what doesn’t in harnessing analytics in pursuit of deeper business insights. This process has led us to identify key success factors for the deployment and integration of analytics.
We have found that when it comes to successful data analytics implementation and adoption, cultural and human factors (buy-in, accountability and trust) weigh just as heavily, if not more, as structural and functional factors, such as funding, process and tools.
Often when a project is complete, our instinct is to move on to the next priority without pausing to reflect on what we learned and how we can improve. However, this hindsight is critical to analyze which plans were implemented, which worked well and which ones failed after launch or, worse yet, failed to launch entirely.
In the recently published IBM Institute for Business Value white paper, Analytics "yield of dreams," we do just that: take a critical glance back at past internal analytics projects to evaluate successes and missteps. After reviewing dozens of project experiences, we identified eight examples that teach us how analytics can most effectively drive business value. Each of these examples is explained in detail throughout the study, as well as the lessons learned.
The study has culminated in a proposed iterative system, which incorporates four critical elements:
- Prime the field: Select data sources based on the potential for acceptance, rather than initial perceived perfection.
- Ease their pain: Provide relevant insights that are easy for users to quickly understand and act upon.
- Go the distance: Mandate the integration of analytics into the business-as-usual workflow.
- Expect improvements: Incorporate feedback mechanisms to cleanse data and foster new stages of future analytics.
Download Analytics "yield of dreams" and explore the framework developed to help maximize the value of data analytics for your team and clients. The paper offers a thorough discussion of the four critical elements as well as the underlying project examples, both of which can lend new insights into how you establish and leverage analytics to make business decisions.
The opportunity to gain competitive advantage from data-driven insights has never been more compelling, and it’s important that teams build systems and processes to support the use of analytics for the future. By employing this framework within projects at IBM, we have achieved better data quality, produced more effective analytics and realized exponential value. We welcome your feedback and comments for the continual improvement of this and other research.