Enterprise software developers are just as talented as their free-wheeling consumer-facing peers, but are shackled by the need to prioritise enterprise security over personal utility, and by the fact that IT buyers differ significantly from IT users, as 37 Signals' Jason Fried has pointed out. But a new breed of enterprise software seeks to overlay and augment crufty old systems with dynamic, user-friendly social software, and may well become a $4bn market within the next five years, according to Wells Fargo analyst Jason Maynard.
Data, not surprisingly, is both the engine behind this shift and the glue sticking it all together.
Enterprise software systems, new or old, throw off immense amounts of data, or "digital exhaust". With the rise of programmable interfaces, or APIs, getting access to that exhaust is easier than ever, but data is only useful if harnessed, made comprehensible, and turned to business value.
Unfortunately, most data is "exhaust" in the traditional sense of the word: waste. If enterprises collect data they do so in data warehouses that sit largely untapped. This is a shame given the potential of data to transform the way we work.
Enter the data stream.
In a new report from Accenture, the consulting firm underlines the importance of finding ways to "develop new data architectures for effectively handling both structured and unstructured information," given the overwhelming volume of data. Otherwise data is mired in complexity that an elite cadre of expensive programmers and analysts can interpret, but no one else.
But if the voluminous updates from colleagues, business partners, enterprise systems and more can be streamed to users Facebook or Twitter-style, then - as I said on the Nodeable blog here - data becomes manageable and those expensive enterprise systems suddenly become worth their price tags.
This is what IBM is discovering. The company that imposed Lotus Notes on the world is finally getting around to making its crotchety interfaces more manageable by overlaying it with an activity, or data, stream. Suddenly, as Alex Williams writes, the activity stream "changes the whole nature of the offering. Lotus now suddenly has a way to be relevant in a post-PC society".
IBM might actually discover users that now want to use its software, rather than being forced to by their Big-Blue-loving CIOs. Imagine that.
The first step in this trend toward data streams is to get systems into the cloud, something stressed in a recent Wells Fargo Research note, Fostering the People: The Shift to Engagement Apps. As analyst Jason Maynard writes:
Business applications are moving beyond merely transactional and analytical functions and are becoming critical tools to engage with customers, to improve productivity, and to facilitate collaboration within the enterprise and throughout the entire value chain... These ["Engagement Apps"] should be native cloud, socially aware, mobile ready, and embedded with intelligence.
That "embedded intelligence" is a product of big data, or can be, and the engagement itself is a rich treasure trove of data. But again, it starts with making data intelligible and actionable by someone that doesn't have the word "scientist" in her title.
Someone, in other words, who can interpret a data stream, or activity stream, or engagement app, or whatever you want to call it.
Enterprise software has always been powerful. In fact, it has often been powerful beyond the means of average users to productively use it. Putting a consumer-friendly data stream on the front end of these complex back-end systems has the chance to resurrect their value and make them much more approachable to the mainstream.
Dan Woods call this out in a recent Forbes article, and calls it "operational big data." It's the process of crunching big numbers in the background to spit out easy-to-understand "little numbers" in a format that average workers can appreciate. And it's set to make enterprise software relevant again, by making it feel much more like the consumer software we prefer to use. It's about time.
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