Five Steps to Transform Data into Actionable Intelligence
One complaint we hear often in the age of Big Data is that we now have too much data. You may ask: How do I dig through all the noise and find the data that truly helps me measure and manage my operations?
Here are five steps to break through the noise and transform data into actionable intelligence.
Start with the end in mind. Ask the question, “What business outcomes are we trying to achieve?” Use a clean slate but keep your ultimate goals in mind. Share these to gain consensus on the top priorities. Don’t try to boil the ocean—start by focusing on a few goals to work out the process for your organization before you tackle additional objectives.
Identify the behaviors that drive business outcomes. You’ve determined the top business outcomes you want to achieve—now comes the hard part: identifying the behaviors that drive those outcomes.
If your goal is to improve the time to delivery by 20 percent in the next 6 months, what activities impact the execution of orders or services in your organization? Can you map these activities into a single process and timeline? Once you have done that, you can tie activities to specific behaviors and roles that execute those activities.
Set goals for the behaviors. After you’ve aligned the activities with who performs them, you need to set goals for each of the behaviors. For a five-step order process: Order Receipt, Order Entry, Fulfillment, Shipment and Billing, assign a target for how long it should take, including setting an SLA for hand-off to the next step.
Looking at the overall process, set target time standards for each step that cumulatively will help you achieve your end goal of a 20 percent reduction in processing time.
Identify the data sources that measure the desired behaviors. Once you have the activities mapped and have set timing targets, identify the data sources to measure the behavior that is driving the outcome. If an order comes into the contact center by phone, the ACD can report on how long that step took.
Even in the age of Big Data, there are still areas where information is not readily available. In the back office, so many different legacy systems may be used to process work that extracting direct data feeds to measure the activities may not be possible. Non-system-related activities such as opening mail or scanning documents may need to be estimated and incorporated by doing periodic time studies because they are not automatically measured.
Convert the data into strategic metrics in performance scorecards. Present the data in a standardized framework that enables employees and managers to clearly see the composite metrics used to assess their performance, the targets for these metrics, and their current status against goal.
The scorecard should roll up into an operational dashboard that captures all of the enterprise or cross-functional activities and aggregates them into an overall performance score. This view enables the organization to see how they are progressing against their goals on a continuous basis. Executive management needs to be able to drill down from the dashboard into the functional, team and individual scorecards to identify any shortfalls, so that they can take corrective action.
Verint Operations Visualizer can help organizations overcome some of the challenges of creating an enterprise operational dashboard. The solution includes Application Analysis, which can capture employee system data directly from the desktop, even to the level of start and stop times of activities on a legacy processing system.
For manual or non-system-related activities, employees can log their time into Operations Visualizer to capture those activities. Data from these solutions and your other systems can be imported into Verint Performance Management Scorecards to create the standardized framework needed to evaluate behaviors and drive desired outcomes.
Read how a healthcare insurer was able to improve employee productivity by 16 percent with Operations Visualizer.
The post Five Steps to Transform Data into Actionable Intelligence appeared first on Customer Experience Management Blog.