Back-fitting on-premise for ‘web 2.0’ growth
Kewill plc succumbed to a buy out by Francisco Partners PE. Without disrupting complex code bases, how could Kewill have avoided this fate?
‘Web 2.0’ business architecture apps are not so different than the previous era ‘client-server’ business architecture. Forester calls the new era App/Internet. Fueling growth requires more, back fitting traditional on-premise applications with the ‘web 2.0’ business architecture. Generally this is additive additive, not code base disruptive.
Illustrative is Sage Group plc, last year we arranged for Google Seattle to host a tech talk by Sage Chief Software Architect, Stephen Smith. The installed base of conservative accountants is not yet ready for SaaS and certainly not big data, yet Sage wants to share the benefits with customers. All applications, 6.2 million customers, are being reachitected using Google’s GWT not .NET or Java, ahead of this huge effort the Sage application installers are being back-fitted for big data user experience analytics.
On an opt in basis, usage is promulgated to Sage.com giving specific usage analytics allowing for learning from users the same as Google does with its search engine. This allows Sage product designers to attend to real optimization (not hearsay) http://smist08.wordpress.com/2012/03/25/sage-advisor-pep/
AfterShip.com a startup entrant based in Hong Kong is more directly going to big data via by texting customer service shipment notifications directly, and collecting ratings back from customers. Providing a seamless delivery experience, reducing missed parcel shipments, at the same time learning from customer feedback about carrier, city, neighbor hood, delivery satisfaction. The resultant feedback is anatomized for privacy, and circulated back into the Aftership SaaS providing more satisfaction and value. http://blog.aftership.com/zappos-to-text-customers-before-package-is-delivered/
How might Kewill, have blended Sage and Aftership approaches, to back-fit tier-1 / tier-2 / tier-3 applications without a huge or disruptive code base investment? Likely each of Kewill’s customers is under pressure to deliver higher levels of customer service, Kewill touches on-premise and in hosted applications shipment data, yet former era application architectures do not have a way to close the web 2.0 big data loop.
The Web 2.0 Big Data flow illustrates how products can be back-fitted to capture opt in data, providing a service that improves shipment recommendations, by annomizing and aggregating data, then passing back star ranked recommendations.
An excellent source for getting a grip on designing for trust and privacy in Web 2.0 business architectures is #pii2012 http://www.privacyidentityinnovation.com/
In turn these recommendations automate customer service, and collect star ratings on deliveries. Web 2.0 and big data technologies to architect a solution are often open source and used by many of the new startup entrants such as Aftership and increasingly by established company’s like Sage Group.
Previous era client-server companies who want to avoid falling prey to PE buy outs should consider back-fitting for growth using the same Web 2.0 business architecture as the new high growth entrants.
