“Whatever made you successful in the past won’t in the future.” – Lewis E. Platt, the ex-chairman and ex-CEO of Hewlett-Packard Co.
Are you into archery? If the answer is yes, then you already understand how much effort goes into hitting the bull’s eye. It’s the same with an organization’s performance. Let me explain.
Just as in archery, there are two critical aspects that players keep replaying in their heads. One is to assess every shot, i.e., whether it is too high or low, too far left or right from the center. Second, performing well and achieving (or even surpassing) their earlier best. The same goes for the leaders in the service industry!
The landscape of customer support and service is changing rapidly. Organizations are making strides to create and adopt unique, compelling strategies to stand out in a volatile global market. The questions arise: Are organizations using the best practices across the industry? Are they getting successful results as compared to the industry benchmark and their competitors? Here’s one way to find out – The Support Services Maturity Model.
Built by TSIA, this model has been designed to combat the challenges faced by support & services leaders while enhancing organizational performances. But before we dig deeper, let’s understand the fundamentals of the Support Services benchmark by TSIA.
TSIA’s Support & Services Benchmarking
TSIA gathers benchmarking data with over 150 questions covering all the major practices that involve people, processes, technologies, and organizational models. Any organization can compare itself against the defined standards and develop a consistent way of measuring performance. TSIA has a large segment of benchmark data based on the following areas:
- Support Fundamentals
- Service Financials
- Talent Management
- Customer Satisfaction
- Sales and Marketing
- Assisted Support
- Self Service
- Outsourced Service Management
Thanks to a cornucopia of quality benchmark data, TSIA’s members “benefit from industry and peer data that reflects best practices and pacesetter-level performance reflecting the top 15% of responses across the results and metrics performance measurements.”
Understanding the Framework Behind the Support & Services Maturity Model
The Support Services maturity model is heavily reliant on results and metrics. However, the two are inextricably intertwined. Let’s shine a light to see what distinguishes them from each other.
- Results: Analytical measurements that are quantified as a consequence, effect, or conclusion of implementing a key support practice/s but are dependent variables like resolution time.
- Metrics: Analytical measurements that are quantified as a consequence, effect, or conclusion of implementing a key support practice/s but are independent variables like response time.
For example: Once a ticket is raised, the clock starts ticking. To brief, a ‘response’ means that an agent has read the ticket, and responded to the problem stated. Now, the ticket resolution process has started. A ‘resolution’ means that the agent has resolved the problem and closed the ticket. In a nutshell, if the initial response time is lower, it will affect the overall resolution time. This correlates to lower assisted support CSAT ratings. Hence, results are dependent on the metrics.
How Different Organizations Stack Up Against the Support & Services Model
After analyzing all the firm’s data, a comparison is drawn with the aggregated member benchmark results across two practices and metrics/results axes. The resulting plot is then further divided into four categories of Support and Service (SS) organizations, as described below:
- Overheated SS: Refers to the organizations with low adoptions of core practices and good results/metrics (false positives or unscalable), resulting in flawed conclusions.
- Start-up SS: Refers to the organizations with low adoptions of core practices and bad performance or that are unable to track the results/metrics.
- Maturing SS: Refers to the organizations with high adoptions of core practices but poor execution, leading to bad results.
- Optimized SS: Refers to the organizations with high adoptions of core practices and good results/metrics with the proper execution, resulting in good results/metrics.
Shifting Gears from Overheated SS to Optimized SS with Cognitive Technology
Being in the ‘Overheated SS’ quadrant is the harbinger of bad news as it indicates numerous challenges like poor content findability, lower support efficiency, increased churn rate, etc. Organizations that fall under this quadrant must take measures to switch to ‘Optimized SS.’ By embedding cognitive tech, organizations can take a giant step in that direction. Let’s find out how.
- Improve Information Discovery: Fueled by AI technologies, cognitive search eliminates silos and helps your support mavens find the information they need quickly and easily, leading to faster case resolution. This polishes up the support metrics and transforms your firm into Optimized SS.
- Empower Agents With A Cognitive Assistant: Modern customers expect responses from brands in the blink of an eye. With next-gen apps like Agent Helper, you can provide case-resolving content and customer journey insights to your agents for delivering accurate first responses. In addition, it augments agent onboarding by using ML to provide in-the-moment guidance to your new agents.
- Leverage Real-time Search Analytics: Interacting with an organization can trigger an immediate and lingering effect on customer loyalty. Cognitive tech provides real-time and actionable search analytics extracted from enterprise-wide data so that you can make informed decisions and deliver stellar customer service. Thus, a step closer to the desired Optimized SS quadrant.
- Automate Knowledge Creation: Agents struggle to find the right contextual knowledge at the right time. At times, it doesn’t even exist, which makes it even more frustrating. For a new agent, the existence of knowledge gaps can be a nightmare! But with applications like KCS Enabler, it becomes easy to prevent your service desk from all the content findability havoc and help bridge the knowledge gaps. With such next-gen apps, your agents can effortlessly populate new knowledge base articles while resolving undocumented cases.
- Harness Power Of Intelligent Swarming:
According to TSIA, “Two-thirds of overheated Support organizations have yet to adopt a single-tier support model and the result is a less efficient/effective Support organization that places a higher effort level on both the customer and the employee.”
In a time where customers expect immediate responses – the Intelligent Swarming℠ model reduces inconsistent response times. Conjoined with cognitive apps like Escalation Predictor, it promotes intelligent ticket triaging. This way, the ticket is routed to the best agent with expertise on the said topic to minimize the mean time to resolve (MTTR).
Improve Your Support Ecosystem with Cognitive Technology
Adopting cognitive technology can help you with seamless connectivity to enterprise knowledge, personalization with advanced machine learning algorithms, and an insights engine that powers data-driven decisions. Want to know how? Our recent webinar in collaboration with TSIA dives deep into the role of cognitive technology in transforming the AX and CX and thus, your support function.