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Strategic Service Optimization

This afternoon we were chatting with a very smart analyst, when he coined the term Strategic Service Optimization for what our company does and what a lot of capacity planning teams do. For the sake of my personal ego, we are going to pretend that I coined the term. Yes, let’s go with that*.

Coining a “better” phrase for capacity planning recognizes that the task of putting together week over week staff plans has morphed into something bigger and more important than budgeting (although budget planning is still critically important). What used to be a linear, mechanical process has evolved into the single best decision-making device for contact center executives.

The concept, Strategic Service Optimization, encompasses a fair amount in those three little words. First, longer term contact center planning is by its nature strategic. Planning is not usually about the right here and right now, but instead is about the near to farther term. For contact center operations, this implies managing seasonal peaks and valleys of the contact center operation, as well as helping with decisions that are longer term, have longer and significant repercussions, and, hence, are much more important. It involves understanding the variable demand for our services, as well as managing the variable supply of our workforces. Contact center strategic planning decisions affect the overall corporate strategy (and vice versa).

Strategic questions that are analyzed throughout the planning process (or assumed by the planning process) include:

  • What channels should service which contact types (and which customer segments)?
  • What levels of service, and concurrently, what customer experience do we wish to design?
  • What agent experience (the best hiring versus overtime policy, what occupancy is best, what level of training will we maintain) will support the customer experience?
  • What sales opportunities do we wish to move to our contact centers?
  • What are the budget priorities for the contact center operation?

Clearly, all of these questions are both critically important as well as strategic in nature.
Among the most important contact center strategic decisions centers around service. Every budget and capacity plan has an implied service investment, an explicit service delivery strategy, and an implied customer experience.

More and more organizations are designing their customer experience – and this requires strategic analyses. Gone are the days when a company executive simply decides service levels based upon gut feel. Determining the customer experience and deciding levels of service for the various contact types is now understood to be strategic questions, and executives are, more and more, seeing that the analyses around these important questions receive the appropriate rigor.

Which brings us to the final word in our new term, optimization. Optimization is a term that is thrown around by many consultants, and usually means something like “improve,” but this term also has a mathematical definition that means much more. True mathematical optimization means not just to improve a bit, but to achieve the absolute, mathematically provable best. This is obviously not an easy thing to achieve for complex operations.

The single complicating factor that makes achieving true mathematical optimization difficult is that each business usually has several competing goals. For example, for contact center operations, our objectives would be a laundry list, possibly including:

  • Answer the contact as soon as possible
  • Provide the most highly skilled agent
  • Provide the appropriate customer experience for each customer segment
  • Run a lean, efficient, low cost operation
  • Keep agent attrition low, and do not “burn out” agents
  • Maximize sales

Clearly, these are competing objectives – one cannot simultaneously answer contacts super fast while running a low cost operation.

But there are ways to draw out the most efficient set of plans even when there are competing objectives (answer fast, least cost). A plan, or a solution, can be proved to be “non-dominated,” meaning a goal (answer fast) is as optimal as possible, given the state of another competing objective (low cost). It is a tad confusing, but in our example, it would mean developing a plan that answers calls as fast as possible, given that our maximum budget is, say, $20MM for the year. In this case, we are doing as well with service as we can, given our budget constraint.

If you’d like to impress your friends, look up the term Pareto frontier. The concept of optimizing competing objectives involves finding plans that satisfy the trade-offs of the different goals in ways that are as good as mathematically possible, the Pareto frontier.

Contact center Strategic Service Optimization draws out all of these business trade-offs; it maximizes as well as possible all of the competing objectives. Given a budget, you can find the plan that provides the best service that does not overspend. It draws out the relationships between service, customer experience, costs, and revenues. And it does so accurately and optimally.

In order to truly optimize planning, your analysts must have a model of the operation that provides solutions at the appropriate (for your business) nexus between planning, customer experience, finance, revenues, and agent experience. Strategic Service Optimization can help.

* Thanks Jim Davies of Gartner for coining the term Strategic Service Optimization!

Ric Kosiba, PhD is a charter member of SWPP and co-founder and president of Bay Bridge Decision Technologies. He can be reached at Ric@BayBridgeTech.com or (410) 224-9883.