Earlier this spring I attended my first IBM Vision Conference. This is, ostensibly, focused on finance, risk management and sales compensation. But I found a strong thread of predictive analytics throughout almost all of the presentations and discussions. In fact, every conversation I had with a Revelwood customer or an IBMer included talking about predictive and where and how it is being integrated into existing analytics applications, or where it’s being deployed for new applications.

One of the biggest challenges faced by organizations adopting any type of analytics is where to start, and how to quickly reach a success point, rather than designing, building and deploying an analytics project that takes years to produce results. IBM and a handful of partners decided to tackle this issue and have created several Storybooks for IBM Watson Analytics. These are easy-to-use tools for Watson Analytics that are individually packaged assets with data models, analysis, visualizations, and insights focused on solving a specific business problem. IBM announced eight expert Storybooks, which are in open beta, at Vision.

These eight Storybooks were developed by a number of different organizations. They include:

• Customer Profitability, in which the American Marketing Association (AMA) offers a best practices way of looking at customer profitability. By starting at cost allocations at the customer and product level, you can understand the interplay of profitability with your marketing investments.
• Sales Win/Loss Analysis, which helps analyze sales pipeline to anticipate performance gaps, track current conditions and alternatives.
• Sales Insights offers sales leadership, sales compensation practitioners, and financial analysts insights into where and how you are booking business, sales performance trends, and assessing Compensation Cost of Sales (CCOS).
• Retail Coupon Performance gives the marketing leader an effective way to assess performance of coupon programs by evaluating performance across a variety of key drivers.
• CMO Executive Summary, by IBM Analytics for Telecommunications, is an essential executive summary for the CMO of any Communications Service Provider (CSP). It highlights key insights relating to Over-The-Top Applications and the impact they are having on you as a CSP.
• Hiring a Top Salesforce, by IBM Talent Engagement Solutions, provides HR and business leaders with insights to optimize talent acquisition programs and investments to drive the highest quality of hire.
• Resiliency Peer Comparison, by IBM Resiliency Services, helps answer your question on “How does my resiliency program compare to my peers and others?” by industry, geographic location and organizational size.

Revelwood’s contribution was an Accounts Receivable (A/R) storybook. It helps organizations to easily analyze accounts receivable and predict which receivables are at risk. It provides a guide to help organizations understand trends in their A/R, see which customers are likely to go into write-off, and to see your predicted exposure.

When you use the A/R Storybook, you can ask Watson Analytics any number of natural language questions, and get visualized answers to those questions. For example, you can ask “What is the total outstanding amount for each customer?” Through the Storybook, Watson Analytics will provide you an answer that looks like this:

Or, you can ask Watson Analytics questions about customer behavior over time. You can ask “How does the number of customers likely to write-off change across time? Are more or fewer customers likely to move to write-off this month?” Watson Analytics and the A/R Storybook would deliver an answer like this:

For a while we’ve known predictive analytics will be growing in usage, and seeping into all aspects of analytics. The conversations I—and my colleagues at Revelwood—had at Vision confirm this belief. Many organizations are jumping right into SPSS. But for those who are not yet ready for full-blown predictive analytics, Watson Analytics and the numerous Storybooks are a great way to experience the power and promise of predictive analytics.