The Complexity Nobody Wanted to Touch

Every large customer service system accumulates complexity the way an old house accumulates wiring. A policy changes, someone adds a condition to the workflow. A new product launches, someone adds another. Years pass, and what started as a clean decision tree becomes a thicket nobody fully understands, kept alive because ripping it out feels riskier than living with it. Aeliya Rashid’s consulting work focused on exactly that kind of thicket, inside a Fortune 50 telecommunications company’s contact center systems, where she spent two years untangling logic that had been building up for far longer than that.

Rashid joined Kenway Consulting as a management consultant, working on legacy-system analysis before moving into a senior consultant role. Her work centered on a single client’s technology platform, one that supports more than a million customer interactions a day, a volume that makes even small inefficiencies expensive and small errors visible almost immediately. Redesigning core system logic on a platform running at that scale is not a project that tolerates much trial and error, since a broken workflow does not surface quietly in a test environment; it surfaces in a call center handling live customers.

The largest piece of that redesign work involved retiring a substantial volume of accumulated business logic from the platform’s underlying workflows, a process that required first mapping what each condition was actually doing, since documentation on decision logic built up over years rarely keeps pace with the logic itself. Some conditions turned out to be redundant, doing the same thing as newer ones layered on top of them. Others were dead weight, written for products or policies the company no longer offered. Sorting the two apart, then rebuilding the workflow without either category, cut process inefficiencies by 23 percent and left a system that could actually be maintained by the team responsible for it going forward, rather than one that only a handful of people who remembered its history could safely touch.

Getting to that result required more than an inventory. Rashid analyzed user behavior, system performance data, and operational metrics to find where the platform’s defect patterns and performance gaps actually lived, then led root cause analysis on the more stubborn issues, working directly with engineering teams to design solutions built to hold rather than patches meant to get through the next release cycle. That distinction matters in enterprise systems: a workaround can clear an immediate problem while leaving the underlying cause untouched, and it tends to resurface, usually at a worse time than the first occurrence.

Rashid’s involvement extended across the project lifecycle rather than stopping at the technical recommendation. She managed prioritization and stakeholder alignment, saw solution designs through testing, and stayed through deployment and the review afterward that determines whether a redesign actually delivered what it promised on paper. She also helped shape new engagements for the firm, which tended to follow the same pattern: a system too complicated to touch safely, and a client that needs someone willing to take it apart piece by piece.

Rashid’s academic path ran alongside this consulting work rather than separately from it. She holds a bachelor’s degree in economics, with a minor in mathematics, completed magna cum laude at the University at Buffalo, followed by a master’s in economics and a second master’s in engineering science with a focus on data science. She is currently pursuing a Ph.D. in information technology with a content specialty in data science at the University of the Cumberlands, where she also completed a master’s in project management. The economics training shows up in how she approaches a legacy system: not simply as a coding exercise, but as a question of which processes are actually producing value and which are just consuming maintenance time without anyone noticing.

What her work amounts to, in the end, is a fairly unglamorous kind of engineering: going through a system too large for any one person to hold in their head, deciding what still earns its place, and removing what doesn’t. It is slower than building something new, and it rarely gets noticed by the customers whose calls now route through fewer, simpler decision paths than they did two years earlier. That absence of friction, the thing nobody has to think about anymore, is the actual measure of whether the work succeeded. It is also the problem she has since set out to take on independently, through a consulting practice of her own aimed at organizations facing the same accumulated weight.