Decision Management and the Cloud

Last week Predictive Analytics World brought together a fantastic collection of minds to share case studies and expertise. A theme echoed in multiple sessions and conversations was that analytics are a necessary but not sufficient ingredient for success. To succeed it is critical to have a strong alignment and integration of technology, processes and corporate strategy. Not an easy task but the ROI tends to be irresistible and mastering this act is at the core of Decision Management.

What does Cloud Computing have to do with effective Decision Management? Well, one of the most obvious aspects is better analytics. Cloud computing offers more storage and more processing power at lower costs. More computing power and more data for less money seems quite attractive. Furthermore, these characteristics make predictive analytics accessible to many more organizations and applications. I like to think about it as the democratization of predictive analytics made possible by Cloud computing.

But that is just one part of the story. Predictive Analytics on the cloud will succeed because of the Cloud's standards and open platforms. Operationalizing analytics behind the firewall of a large corporation can require the custom integration several layers of expensive software and in-house applications, e.g.: point of sales systems, call centers, databases, rule/workflow engines, analytic engines/models, etc. The cost and complexity of these projects can easily challenge the most optimistic ROI models.

Fortunately the Cloud is being designed precisely to simplify these scenarios. For example, let's consider Salesforce.com, one of the leading Cloud platforms available today (along with Netsuite and Intuit among others). Salesforce simplifies integration because it has a rich API based on open standards. Salesforce has a powerful workflow engine to automate business processes a flexible data repository and native support of email, social and mobile channels. All of this functionality is available on demand on a pay as you go basis. Similar functionality is becoming more and more popular among cloud platforms but getting it on-premises is far more complicated.

The Cloud can deliver more powerful analytics and also help make them actionable. Now we just need alignment with the Corporate Strategy but we'll leave that for a future post.

Doing more with less

Christopher Musico wrote a well timed piece for DestinationCRM describing how some companies are leveraging predictive analytics to become more competitive. It comes as no surprise that during challenging economic times companies try to be more efficient by making better use of their assets. And what better asset than their internal databases?

I think it is safe to say that by now most companies (large and small) have deployed relational databases and reporting software of varying sophistication. This reporting tools have been asked to answer questions about historical events. Questions about 'what happened', about 'the impact (how much, how many, how often)' and even more specific questions that require drilling down to granular levels of information to understand where exactly the event took place (place, product, point in time). Some more advanced companies have even deployed alerting systems to be notified as soon as certain conditions occur. The natural next step to develop competitive advantages is to deploy analytic solutions that can predict and optimize future events.

This conclusion might seem obvious to many. Christopher's article includes the results of a survey where more than 50% of the respondents intend to deploy predictive analytics in the next 6 months. Predictive Analytics can bring many benefits but effective deployment is no easy task. The software cost, skills shortage and infrastructure complexity can be significant barriers to entry. Not to mention the necessary changes in culture and business processes.

Traditionally, the successful deployment of predictive analytical solutions has been reserved to a handful of large companies with vast resources. It is nice to see organizations like USTA succeeding with these projects. I believe this is a sign of things to come. I think the intersection of Cloud Computing and predictive analytics will create new possibilities for powerful and accessible insight.

What if the Cloud never makes it to the enterprise?

David Linthicum wrote an interesting piece about the cloud reality setting in. The enterprise is cautious and a bit skeptical about the Cloud; as it should. Frederic Paul at bmighty.com writes about the Forrester report that asks "Why not run with the Cloud". There seems to be a general agreement that when it comes to the Cloud the question is not IF but rather WHEN and HOW.

But what if the answer for the enterprise is never. What would happen if the enterprise never adopts the Cloud (at least the cloud as I like to think about it). What are the risks of inaction? How competitive would those enterprises be?

I believe history would repeat itself. No matter how large or mighty, those corporations would collapse unable to compete against more efficient and more innovative competitors. Just like Chrysler, GM or the print media industry. I echo David's opinion: 'there are pros and cons, let's understand both' (paraphrasing) and I would like to add that companies need to go one step farther and start focusing on the HOW. The ones that do will deliver more value to customers and shareholders for a longer period of time.

Gartner and the Cloud

Back in may there was some controversy with the estimates by Gartner of the Cloud Computing market size. Earlier this month Gartner announced the results of a survey of SaaS users where findings did not exactly provide a ringing endorsement of SaaS. Needless to say these results also caused controversy and a very articulate response from Jeff Kaplan from THINKstrategies.

Gartner's press release of the SaaS survey mentions that TCO, ease of integration and technical requirements are challenges faced by SaaS solutions. No surprise. And that is why when I look at the most successful SaaS company in the planet I can understand that success is never a coincidence. Salesforce.com's is a true role model for Cloud Computing and SaaS startups. Ten years ago they understood the importance of technology integrity, innovation and excellent customer service.

When it comes to the future, I prefer to focus on the ones that are shaping it and not just talking about it.

More Blue Analytics

IBM continues to position itself as the absolute leader in Business Analytics and Optimization. With the acquisition of SPSS IBM has the deepest portfolio of products and services available under one roof. Oracle also has quality products but it lacks IBM's depth in Business Consulting. On the other hand SAS software and consulting is top notch but IBM's offering is superior because it can enhance its analytics platform with database, hardware and decision management software. It is almost too much for a single company to handle effectively. For sure some new buyers will be concerned with vendor lock-in but I believe most IBM customers will be glad to have access to all of these capabilities from a trusted advisor.

While Cloud Computing has grabbed most of the headlines this year, the developments in Predictive Analytics should not be ignored. I am convinced that the intersection of Cloud Computing and Predictive Analytics will provide the perfect stage for the future of business innovations.