The Importance of Domain Experience

A few years ago, I had a brilliant Data Scientist, backed up by certifications and knowledge of the latest trends, approach me after I completed a seminar and asked how she should analyze some Service Desk Data that was provided to her. She was just provided with the data and told, do some analysis. She talked about STA, Sentiment Analysis, NLP, Predictive, etc.

I began by asking some standard questions:

1 - Did you Identify the Client Pain Points & Business Impact
1.1 - Seek clarity on the specific pain points that the business is facing
1.2 - Understand the impact the pain points are having on the business
1.3 - Conduct an Assessment to further detail the pain points

2 - Did you Identify the Goals & Objectives & Define The Expected Outcomes
2.1 - Seek clarity on the Client’s goals and objectives
2.2 - Understand and define specific outcomes the Client is expecting
2.3 - Establish SMART measurable goals and business outcomes

The answer was no. It was no because she did not have a Service Desk background or delivery experience.

For me, I have been a service desk agent, knowledge coordinator, quality coordinator, skills/training coordinator, engagement lead, First Line Manager, Senior Manager, Delivery Executive, etc. I have worked on @100+ global accounts that had something to do with Service Desks. I have worked on dozens of critical situations where we were at the risk of losing the service desk business. Across all of those experiences, I was able to identify and capture lessons learned.

So when I get asked to assist with delivery issues, having worked in global Infra and App spaces, I can easily pinpoint the issue without even using advanced technology and tools.

My point here is, Data Science/Analytics is much more than technology and tools. It's not about plugging some numbers in an excel worksheet and performing calculations and building charts. There is much more to it.

To be successful in this space, you need to have domain experience and a strong business sense/acumen.

Here is a sample list of areas to probe:

1-800 # Availability
IVR Updates, IVR Options
Greeting / VnA
User Authentication
Usage of Templates
Triaging / Diagnosing
Documentation quality
Correlation of Emerging Issues
Prioritize/Classify
Routing / Misassigned
SME Availability / Coverage
Dispatch to L1.5/DSS/L2+
FCR/FCE
Premature Closure / Repeat Callers
SLA Hold Usage
Level setting of SLA/SLO timelines
Keeping Client Updated on Status
Escalations
Backlog Management
Skills, Capabilities, & Resourcing
Knowledgebase  usage
Repeat/Chronic Issues
Productivity / Utilization
Missed Service Levels
Staffing / Call Arrival Patterns
Time Spent in ACD Queue Issues
ABDN, AHT, Hold, Dead Air, Filler Words, ACW, AUX Usage, Inbound/Outbound Talk Times
Login/Logout/Schedule Adherence
Case to Call Ratio
Negative Surveys
Ghost Calls