Merging Local Data Acquisition with SaaS

Jun 24, 2008 by

Generally speaking, I’m opposed to introducing different terms to describe the same thing. In the SaaS space, Microsoft has taken the position of using “Software + Services” rather than “software as a service.” To some degree, there is a level of correctness captured in “Software + Services” that you don’t find in SaaS, particularly when taken in the context of this post.

Traditional SaaS examples generally follow a theme where end users access their application online, produce data online, and then consume artifacts of that produced data online. Take using Salesforce.com, for example. Individuals save leads, contacts, etc. only to come back and use data they or others in their organization have added. What if a business domain relies heavily on or could experience huge value from exploiting geographically bound data? Software for the food industry could exploit this. Being able to near real time monitor things like refrigerator temperatures at a warehouse or refrigerated truck temperatures can reduce spoilage and lost revenue, reduce liability burdens, and even save energy. SaaS, at least in most people’s current conceptual model, doesn’t account for local data because of SaaS’ relatively centralized nature. Microsoft’s “Software + Services” approach is a touch closer to what I’d like to see. Local software agents essentially make up the on-premise software side of the equation, where the agents might be connected to things like temperature monitoring hardware. That data is coordinated and reported back to the food warehouse management SaaS offering, which can correlate the data to a tenant’s standard data model. This gives a tenant a local and deep view of their operations as related to the business function managed by the SaaS offering.

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This concept is not revolutionary and I’ve seen it done, but I think it should be part of standard SaaS conversation. I rarely hear discussions pop up regarding how to exploit customer premise data. It allows for situations like a food distributor recognizing drastic temperature changes in a refrigerated truck while enroute to a customer, or other situations like temperature fluctuations due to an overstocked freezer at a warehouse, and merge that with the inventory control functions of the SaaS offering. Decisions like “move the following stock from freezer A to B” are possible while maintaining most of the SaaS benefits. We live in a connected world, so what can SaaS do to exploit this connectivity? The creative boost that comes from local data acquisition is immense and shouldn’t be discounted.

What role do you think (if any) blurring the line between SaaS function and locally acquired data will play in the short term? The long term? Are security implications too grand to achieve success in this sort of play?

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Exploiting Data as a Value Add in Your SaaS Offering

Jun 10, 2008 by

I just read a great article by Joshua GreenbaumĀ that brushed on the topic of the next iteration of SaaS. Greenbaum identifies SaaS 2.0 asĀ being offerings that use aggregated data across the customer base to extract valuable information that can help any one of the customers individually. This is basically the concept of “benchmarking”. I’m completely in agreement with this concept, and I think it’s worth expanding on the topic. One very important discussion is how to deploy this and is there cross functional value in that data?

From a deployment standpoint, an offering that aggregates data and extracts value from that aggregation needs to offer each individual customer the ability to correlate that data to their own unique landscape and set of processes and metrics. Without taking this additional step, and making this correlation easy to associate and measure, the extracted data could prove to be just that – data.

Second, is the data valuable outside of the application’s customer domain? A SaaS 2.0 vendor should definitely look to other constituents. For example, if a help desk application can show help ticket close rates across the industry and offer to you, a customer, for benchmakring against your own performance metrics, it can use the same data and resell services and analysis to the hardware vendors for which the help tickets were generated against. Hardware vendors can use the SaaS vendors data and analysis to identify everything from manufacturing trouble spots to measuring the repair difficulty of a given product. In turn, this could lead to a community driven quality improvement without the community having to do anything beyond their normal use of their SaaS application.

My interest in this is seeing how a PaaS offering like SaaSGrid can help with this, making the abstraction of benchmarking even more interesting!

Do you see the next wave in SaaS as the exploitation of aggregated data or as something else?

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