Data Services Verticalization in 2013
I am seeing more evidence day to day that enterprise software and services, both the platform and best of breed varieties, are increasingly maturing toward industry or vertical-centric solutions. Some of this could put a kink in traditional software/service delivery and it wouldn’t surprise me to see it blossom in the next 12-24 months.
Big vendors like SAP or Oracle have traditionally depended on customers to configure their broad platforms for processes and documentation specific to manufacturing or retail or claims management and then re-offer that customization in industry templates to similar clients. Now, some of the smaller horizontal plays that started out working on ubiquitous processes -- sales automation, marketing automation, HR and finance for example -- are retreating toward specific verticals in order to better distinguish themselves in the marketplace. Moreover, they are doing it more with data services than platform bells and whistles.
If you believe (as I do) in the relentless creep, creep, creep of SaaS-based handovers to more and more departments and functions like SFA or HR, you’ll agree that these are destined to become commodity services with low barriers of entry for the competition. Vertical expertise on the other hand is distinguished by a narrower orientation and subject-matter expertise that is likely to be revenue focused.
Gordon Ritter, a founder and general partner at the VC firm Emergence Capital Partners, thinks of this kind of strategy as “shared wallet” domain traction because it quickly delivers more value up front than the horizontal players can offer without a lot of consulting and configuration support. When I spoke to him a couple of weeks ago, one company he referenced was PivotLink (disclosure: his firm has been an investor) that took a broad BI approach and refocused it on retail. He calls it a winnowing process to see what the vendor does especially well and then focus on the niche and its constituents.
More profoundly, Ritter says the big SaaS vendors like salesforce.com or SuccessFactors are very well placed to study and turn multiple tenant behaviors and outcomes into metadata, guided services and vertical process optimization -- things the old enterprise vendors never focused on. On legacy platforms, these complications were necessarily offloaded to the likes of an Accenture or McKinsey for custom ($$$$) efficiency work. Ritter figures a good job of data analysis by the SaaS leaders could mark the demise of "borrow your data" consultants like the aforementioned. In either case, I'd agree it's apparent that vendors can and should be at the center of the data and pay less attention to the custom fields and features they used to differentiate by.
Vertical optimization still requires organizational oversight and controls for the data behind the process and outcome optimization. Coincidentally, I interviewed Sunil Soares not long ago for an upcoming interview on his new book on big data governance, but he’s also just released a new industry vertical oriented governance resource and service through his Information Asset LLC startup.
“Why start from scratch when you have a prebuilt data governance charter for banking or health care, where you struggle with sharing claims information with third parties?” Soares told me. “What about sampled organizations with roles, responsibilities for each member and maybe some reference data sets?” Instead of generic governance training, he’s thinking of particular industries where he can already deliver artifacts and process-centric collateral.
To me, there is just as much green field opportunity for network value-add data service vendors like those found surrounding the platforms of salesforce.com or Netsuite, though Ritter thinks the bigger platforms are better suited to aggregate and understand vertical behavior across many constituents.
“If you are Experian and have unique data that no one else has, maybe mashed up with a bunch of other more public data, and some good algorithms, you’ve really got something,” Ritter says. “If you just have good algorithms, I think that becomes a commodity over time.”
That’s an area where private companies alone or in partnerships can also get into the data value add game (as many have been trying or will do so in coming years). While an Experian or ADP might have obvious departmental uses right now, there’s no doubt a distributor or process manufacturer will likely have their own unique ticket to market in the not-distant future.
I can see it happening sooner rather than later. What about you?