Six Remedies For a Dire Forecast

Part III

Your plan to avoid forecast calamity in the back office is well underway. In the first two parts of this series we addressed bulking up your people and focusing on the right priorities to drive productivity and smother bottlenecks.

The focus of this final installment will be on how to properly motivate you team with financial benefits and reduce waste caused by overcapacity.

Pay Only For the Best

When there is simply no way around spending on overtime, comp time, bonuses or other concessions in order to manage a challenging work queue, use the data in your forecast and analyze the capabilities of your workforce to secure the best help available. Employees may clamor for the opportunity to earn more money, so get bang for your buck—tap your most competent performers to earn the extra pay and help you battle the bottleneck most efficiently.

Reduce Wasteful Overcapacity

Not all bad news comes with the looming shadow of insufficient staff levels, aggrieved customers, or penalty-happy regulators. Be sure that you scan every forecast for significant overcapacity as well. Having more employees on hand than are needed to meet projected demands costs your organization money. Back office environments have historically struggled to develop reliable procedures for seasonal, part-time, or otherwise demand-driven scheduling because forecasting has been so limited. Modern, sophisticated forecasting will map out the low seasons for back office demand and play a key role in long-term efforts to shift to seasonal hiring, shared or blended associates, and flexible work schedules that break the 40-hour-week mold.

Consistent forecast issues could be a sign of deeper problems. Productivity may be systemically low or slipping downward due to a lack of management information and tools. By analyzing your resources against your forecast, you can uncover these trends and identify opportunities for coaching, training, and other staff action plans. On the other hand, routine forecast misses could demonstrate that the underlying assumptions and projections about the time to complete key work types are flawed and need to be re-evaluated. If even the best performers consistently need 50 percent longer than projected to complete new member applications, it is the model and not the manpower that needs adjusting.

Once the dire warning signals have stopped flashing and order is restored in the world, remember that the key to effective forecasting is having transparent data. Should you run into another issue, you will be ready to draw on the right people, focus on top priorities, and drive performance.

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