There’s a dirty four-letter word at the heart of many BPO and ITO engagements. It can drive costs through the roof, undermine customer trust and de-rail the best SLA-governed plans. The word in question: “D-A-T-A.”
If you’re on the business side of outsourcing, maybe you don’t think too much about the nuts and bolts of client data. It’s easy to take data for granted, much as one takes for granted water from a faucet and electricity from a switch. It’s equally easy to assure a customer that his data is in capable hands. But is it?
If you’re on the IT side, however, you probably know a regrettable truth. The one-off, custom-built data-integration processes behind many outsourcing engagements can be inordinately expensive, inefficient and brittle, and provide only limited visibility into how customer data is processed and manipulated.
As the outsourcing industry grows, so grows the magnitude of data challenges that confront service providers. It’s no longer HR and payroll — customers want outsourced services for finance, supply chain, CRM and other functions. It’s raising the stakes for how outsourcers handle client data. Like it or not, outsourcing growth means: More applications and data types, higher data volumes, increased data complexity, and greater data exchange frequency.
Managing Data
Outsourcers have traditionally relied on ad-hoc tools, tactics and technologies to get customer data to the outsourced data center. In some cases, providers may leverage the client’s data-integration system to access, transform and move information across firewalls. In other cases, a small army of specialized programmers is dispatched to customcode mechanisms to access client data in archaic homegrown systems, legacy mainframe databases or packaged software from providers like Oracle and SAP.
The custom-coding tactic may have been serviceable enough eight years ago, when the only systems in play were HR and payroll. But with more and more clients, applications, data and complexity, its shortcomings are obvious.
High costs and lengthy cycle time:
Because the scope and complexity of data integration is frequently underestimated, labor costs for developers skilled in programming languages can bust the budget. Unforeseen data complications can delay the go-live date by months. Simply finding specialized programmers can be an ordeal … never mind the megabuck wages they command.
High maintenance and lack of reuse:
Client-specific data-integration systems can’t be repurposed for other engagements, perpetuating a vicious one-off cycle of high costs and hit-or-miss deadlines. Troubleshooting and maintenance can be an ongoing nightmare that corrodes the entire relationship, often exacerbated by time-zone differences.
