Fortune 500: $480 billion in back office inefficiencies a year; how to drive it out
The past five years have taught us nothing if not that running a lean shop is crucial to survival. And yet, I recently came across a statistic that quoted the Fortune 500 as being responsible for $480 billion worth of inefficiencies a year, most of which is snarled up in the back office. Don't make the mistake of confusing this with bloated costs – most of that inefficiency has fallen by the wayside (or the company has). What we're talking about here is pure inefficiency of process outsource and resource utilization. And with so many shared services now focusing on managing data and driving business insights, there's no role more important than yours in fixing this.
The big trend today is to rationalize resources across disparate services delivery centers. Gartner's research is pointing to the fact that Business Process Outsource providers have recognized the writing on the wall, and are using technology to eliminate staff, increase the productivity of the workforce, and cut operational costs. And if BPOs are spotting a trend, you know it is coming to you!
It all points in the same direction: we can decrease the human element, we can work smarter, and we can simplify. But are we? And if not: What’s slowing us down?
The real challenges lie in the gaps in productivity and process inefficiencies. If you can capture actionable data you can implement changes for better business outcomes. But to do so, you need to take a view a holistic view of the customer experience, and monitor the end-to-end customer service value chain.
So what’s missing?
Firstly, we are lacking a standardized framework across functions and sites that captures key performance metrics and enables equitable measurement of productivity and effectiveness. And secondly, we need to build up the capability to view capacity across the enterprise and capitalize on cross-training and shared resources to improve service levels.
The ultimate challenge organizations face is to manage people, the amount of work, and the service goals/timings. ERP and workflow can do a lot of this; but on their own, and without a better appreciation of what "amount of work" represents, are limited. "Workforce optimization" strategies tackle that question head on, by focusing on the best utilization of staff while keeping an eye on customer service goals. The real opportunities for cutting inefficiencies reside mainly in tackling "idle time" and "managerial time".
More specifically, organizations should be rethinking these areas:
• Data driven staffing models: For most organizations, this is driven by finance. We need to promote the idea of filling short-term opportunities and requirements, however. Lowering the timeframe to 6 months, rather than longer term, also means you’ll be reacting to the right pressure points. Estimates are that this could give you a 10-15% impact on driving out inefficiencies.
• Idle time/non-productive time: Most work is today electronically delivered so it's easy to monitor. Desktop analytics solutions for the back office can now track how staff are using their time on their computers. Tracking idle time/time not spent in directly productive work is the winner, here. But it’s not about punishing staff – it’s about identifying where their work impacts productivity, and where it doesn’t, and then making appropriate changes to/reprioritizing their workload. There's an enormous opportunity here to drive more productive value – up to 25%, in fact.
• Managers’ time: There is a 25-35% opportunity for efficiency gain by automating many of the administrative tasks of managers, such as resource scheduling and report creation. Most managers, research has found, spend up to 45% of their day gathering data and doing analytics (is this you?), when really, they should be coaching employees on how to do their job better, in line with their skill sets. Managers should not be involved with administrative work.
What's really innovative here is that compared to traditional productivity measures, where productivity was measured across all activities, today you can zoom in on productivity by tracking it specifically against time spent in production. This statistic becomes far more relevant, and companies can subsequently make decisions as to how they wish to deploy their workforce. It's a new approach, and one that we are sure will gain traction. It's all part of becoming smarter, better, and faster. And if shared services isn't the engine to push this through, I don't know what is.
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