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COVID-19: Dynamically assign and manage resources

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DMS Covid

We blogged previously about the need to react quickly and accurately to change and the importance of building and sustaining customer relationships remotely. One final area of focus is the need to be more flexible and dynamic in how resources are assigned and managed.

Companies are going to have more staff working remotely. Remote workers can’t share work as readily with their co-workers, or bounce assignments to others by simply standing up and waving across the room. A group of collocated workers could be assigned work pretty mindlessly and left to sort it out for themselves – simply queuing up the work for the group worked OK. This approach had problems before but now these problems become too serious to ignore. Organizations need to rethink how work is assigned and move away from first-in, first-out queues to more sophisticated allocation and assignment.

For instance, one call center we know supports remote workers and multiple locations by investing in its call routing approach. Instead of just dumping calls into a queue, the stated or predicted topic of the call as well as customer details and value are used to route it appropriately. To maximize the engagement and value of these calls, the organization also determines the best possible upsell or cross-sell to be made at the end of the call (including the possibility than not making one was the best option). Where possible, calls are routed not just to someone who can solve the problem the customer has but also to someone who’s good at selling the identified upsell. This focused assignment is highly dynamic and can be changed whenever new products or campaigns are launched or when the kinds of calls being received is impacted by outside events. Staff are given work they are good at, customers get agents who can help and who are enthusiastic about the products being up-sold, and results improve.

Even when organizations have built dynamic allocation and assignment approaches, there are often overrides. When call volumes get high, when the quarter-end is looming or when marketing campaigns are in flight, all the sophistication is thrown away as the override kicks in. This is never great – overriding things like this inflicts long term damage on data-driven improvement for instance – but it becomes very high risk when circumstances may often result in new overrides. Like now, when the constant changes to COVID-19 rules and regulations are causing companies to keep overriding their systems and process to cope.

The new environment is going to require much more managed overrides and more rapid change. One of our clients, for instance, has a routing algorithm that considers a wide range of factors before deciding how to handle a particular product return. Various situations exist that “override” the default algorithm but these are built into it. Business users can simply identify that a particular circumstance has occurred and the built-in changes to the algorithm are triggered. The business gets the appropriate response, users still rely on the system in exactly the same way and all the usual data gets collected. The “override” gets 100% compliance from users because its built in and the cost and impacts of the override are transparent because the system still runs and still creates the data needed for analysis.

All of this brings up one last point. Precise resource assignment increasingly involves algorithms – machine learning and predictive analytics. Which customers are churn risks, which products will be appealing, who’s likely to be able to handle this problem – all of these are candidates for advanced analytic models and machine learning algorithms. Focusing on the business problem – how to do the assignment or allocation – frames your need for these analytics so you can not just build the algorithm, you can also get it across the “last mile” and into production.

These systems are going to require new decisions to be made – dynamic, managed, automated assignments and allocations will replace first in, first out queues and simple distribution. Processes will change to add these decisions. Analytic insight will matter in these decisions, as will expertise and experience. Batch analysis will be replaced with real-time scoring and simple logic with managed business rules. Decision models will help you integrate these elements to deliver the real-time decisions you need.

Dynamic, managed assignment is something you can build into your systems now. We’ll be posting regularly on ideas and approaches and producing some great content. To stay up on it, why not sign up for our newsletter.

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