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.

BI and the Cloud

Wayne Eckerson from The Data Warehouse Institute has an interesting post about Implementing BI in the Cloud. He mentions that BI in the Cloud faces four constraints:

1) Customization or application fit

2) Ongoing cost of transferring data to the Cloud

3) Data Security

4) Vendor viability

Wayne wraps up his post with the following conclusion:

BI for SaaS offers a lot of promise to reduce costs and speed deployment but only for companies whose requirements are suitable to cloud-based computing. Today, these are companies that have limited or no available IT resources, little capital to spend on building compute-based or software capabilities inhouse, and whose BI applications don’t require significant, continuous transfers of data from source systems to the cloud.

I tend to agree with the following high level thoughts:

1) BI on the Cloud is not for everybody (yet)

2) Due diligence is necessary to reduce risks on data security and vendor viability

But Wayne's post raised several questions in my mind:

Integration. There are several ways to customize an application. For example, a multi-tenant architecture like Salesforce.com offers endless possibilities to customize and extend every single instance. Are these customizations unprofitable? No they are not, they are part of the application and they do not require changes to the underlying code. Can the same level of customization apply to BI? Absolutely. Wayne mentions briefly Platform as a Service but his focus is towards custom application development (although his chart shows "DW as a Service"). An intriguing approach to offer a BI platform as a service would be to setup something like MicroStrategy and configure it in a multi-tenant fashion. The underlying layer of IaaS would support the data repository while the top layer of SaaS could support ad-hoc reporting, vertical applications or full customizations on top of their API. Would this be unprofitable? Not at all. Wayne makes another good point regarding integration:

So, unless the SaaS vendor supports a broad range of integrated functional applications, it’s hard to justify purchasing any SaaS application.

But from my experience, successful enterprise wide deployments need to focus on integrating subject areas at the data level. This is an architecture and design challenge. A well integrated data repository will support integrated functional applications seamlessly. It is about the underlying data not only the application.

Ongoing Data Transfers Costs. Is this really a significant constraint? How much data does the typical Data Warehouse has to incorporate on a daily basis? The cost to transfer data to Google's App Engine is $0.10 per GB. Moving a TB a day would cost around $3,000 per month (I'm not suggesting using BigTable as a DWH repository yet). As Data Warehouse costs go, this does not seem unreasonable. Amazon is running a promotion right now that would bring that cost down to $1,000; hardly a deal braker. Latency and complexity can complicate this data transfer. This is to be expected because 99% of them were not designed with the Cloud in mind. Which brings me to my final point.

I mentioned using MicroStrategy as a BI platform on the cloud as an example to make a point. I believe that successful Cloud applications need to do more than just cloning their on-premise counterparts. They need to leverage the Cloud inherent qualities, for example elastic computing power. The nature of the Cloud can enable ongoing ETL: receive a copy of the transaction on the fly via a web hook, cleanse, transform and aggregate in real time or a few times a day at least. How about Map Reduce? I think this technique will allow to create more powerful analysis over more data, faster and easier.

Rigid applications built with yesterday's patterns will struggle to survive, in the Cloud or elsewhere. The Cloud is an open environment by definition, its openness will facilitate the integration of multiple data sources from inside and outside the corporate firewall. This integration will support a next generation of cross-functional applications. Bandwidth and storage costs continue to drop very rapidly and will cease to be a major consideration in the near future. New design principles (e.g. scale out vs. scale up) will enable more sophisticated analysis over ever larger datasets (Google analyzes over a PetaByte of data every day). With over $1B in sales Salesforce.com is the most successful SaaS provider. They host more than 55k customers, well over 1M users and every day execute more than 30M lines of customer code. If they can do it, I'm convinced the next BI leader in the Cloud will do it as well. That is how I see it.