Why read this: To understand the quality of your data and drive better decision making using the Analytics Cycle.
The payoff: Two new expert resources from IBM Business Analytics that frame the problems and solutions for your organization.
In today’s frenetic business environment, we all need to make smarter, faster, data-driven decisions to serve customers better, outpace the competition, and drive growth in revenue and operational performance.
But there’s a big handicap: far too many businesses are stuck working with poor data, and then interpreting it badly because of the limitations of traditional business intelligence (BI) tools. They may be captivated by pretty charts and dashboards, yet they are also chained to weak analysis — and therefore bound to make bad decisions.
The answer? Adopting a comprehensive approach to analytics, or what we at IBM refer to as the Analytics Cycle.
You’ll hear us talk about the Analytics Cycle a lot — and rightly so. Maximizing the potential of the Analytics Cycle is the key to amplifying the impact of your data, harnessing the best technologies to support your analysis, and making the best decisions, faster than ever, to support your business objectives.
Using the Analytics Cycle to Drive Better Business Decisions
The Analytics Cycle has five parts, each one naturally leading to the next. Here’s a simple overview, including the parts of the IBM Analytics portfolio that apply to each:
1. Planning analytics — What is our plan?
This stage is forward-looking, and often focuses on budgeting and related milestones. The technology you use here — such as IBM Planning Analytics — empowers you to create more accurate plans, budgets, and forecasts.
2. Descriptive analytics — What happened?
Desktop tools made self-service BI possible. These tools give executives and managers a single snapshot of how their business is performing. However, in order to avoid getting blindsided by that “pretty picture,” it’s critical to know that you can trust your data visualization tools and move beyond acting on quick (and potentially misleading) insights.
3. Diagnostic analytics — Why did it happen?
Watson Analytics uses data discovery and exploration techniques to drill down to the true business drivers and find unlikely relationships hiding in your structured and unstructured data. Smart data discovery allows you to uncover what happened, so you can then determine exactly why it happened.
4. Predictive analytics — What will happen next?
Our SPSS technology has long been a gold standard for data scientists wanting to predict what will happen based on the deep patterns in data that can only be uncovered by machine learning. Now those insights are being put into the hands of everyone, not just the specialists.
5. Prescriptive analytics — What should we do?
When you’re ready to take the insights of predictive analytics and direct them toward the outcomes your organization wants, look to IBM Decision Optimization and the ILOG CPLEX Optimization Studio. These powerful solutions help you nail down your decision making like never before.
The new knowledge generated from step #5 then feeds back into your next phase of planning, so that the entire cycle starts again — getting smarter with every iteration. You can immediately use the insights gleaned to make better decisions and implement operational improvements; as you complete the cycle multiple times, you’ll also begin to achieve new levels of innovation driven by analytics.
Two Business Analytics Resources for Better Data-Driven Decision Making
We have recently debuted two publications to help you understand exactly how this lifecycle works, starting with how to make sure you’re using data you can trust in ways that make sense, and then walking you through each part of the cycle in detail.
Our new smartpaper — “How Can You Trust Your Data Without the Big Picture?” — provides an entertaining overview of how your business can avoid the pitfalls of bad data and bad analysis to make better decisions in each part of the Analytics Cycle. It features an embedded video so you can hear directly from the experts, along with links to key resources and real-world examples drawn from business environments including software, telecom, broadcast television, and even the 2012 London Olympics.
Our new whitepaper — “Trust Your Data with IBM Business Analytics . . . or Face Disruption” —builds on the insights of the smartpaper to highlight the importance of having and using data you can trust, paying special attention to the Planning, Descriptive, and Diagnostic steps of the Analytics Cycle. The paper provides a closer look at how IBM Business Analytics offerings work at each step of the cycle. It also delves into vital related topics such as financial audit trails and the special requirements for performing analysis on social media data.
More data is bombarding us every minute, which means that the need to make better decisions will only grow over time. Make the right data-driven decisions, drive revenue, and maximize operational improvements using the Analytics Cycle today so you can keep your organization ahead of the game.