Service Level Management in the Digital Age

Posted: 08/11/2018 - 00:55
In recent years, the art and science of the Service Level Agreement (SLA) has evolved from monitoring metrics around systems and applications to a focus on business outcomes and business performance. Rather than measuring server uptime or network availability, customers want insight into how efficiently they’re shipping orders and executing transactions. 
This shift involves a business emphasis on collaborative innovation and rapid development of new features. Multidisciplinary client and provider teams increasingly work together to deliver functionality as quickly as possible. In an Agile development setting, for example, pod developers participate in client meetings, report on how they’re delivering business value and proactively suggest features that will impact business goals and KPIs.  
Today, customers expect the provider team to understand the business and to help it grow. The challenge, however, is that the SLAs assigned to the Agile pod can still be traditional measures of productivity, innovation and quality. This creates a potential scenario in which the team is meeting all its SLAs but remains out of touch with what the business requires.
To close this gap, clients and providers must jointly embed SLAs into service delivery and share responsibility for achieving business objectives. This involves a shift from reactive to proactive thinking, from manual to automated management and from fixed SLAs to flexible metrics that evolve during the life of the agreement in response to changing needs. In the process, fit and culture between client and provider become more important than ever.
The Digital Customer Experience
The growth of digital technology has also significantly impacted SLAs. Data analytics deliver detailed insights from operational data, while cognitive tools enable proactive and predictive modeling. As a result, SLAs are transformed into real time management tools, rather than measures of historical performance that are reviewed a month after the fact.
Digital’s focus on the user experience, meanwhile, significantly raises the stakes for SLAs. Managing the availability of a customer-facing mobile app, for example, requires the ability to respond immediately if an issue arises with that app. In other words, the issue is no longer just the uptime of a back-office corporate system; rather, you’re talking about a potentially dissatisfied (and potentially vocal) customer. And since an unpleasant user experience can very quickly go viral on social media, even a minuscule negative trend can have an adverse and measurable impact on brand value. 
Internet of Things
Another factor influencing SLAs is the Internet of Things (IoT), which creates networked “systems of systems” including intelligent devices, sensors and tools that continually communicate and share information. Traditional, static metrics don’t account for this dynamic interchange, so SLAs need to evolve to monitor and track how ongoing data communication impacts products, services and customer satisfaction. 
A specific challenge here is to ensure that SLAs bridge the gap that often exists between IT and operational teams. Traditionally, IT and operations have functioned as discrete entities in isolated towers, complicating the task of data sharing and reporting. Since the IoT, by definition, requires the integration of IT and operational expertise, developing SLAs that drive collaboration and shared responsibility between the two functions is imperative.
Service Level Agreement Best Practices 
An effective approach to service level management begins at the foundational level of outsourcing strategy. An organization that integrates its provider into the value chain and shares its business direction, priorities and pain points will likely be more successful at developing meaningful, outcome-based SLAs. 
A retailer, for example, wants to know how its mobile app performs in terms of average user ratings, the frequency of use and percentages of deletes. A provider that has insight into the retailer’s business goals can align with those measures and focus on driving improvement. Absent that partnership-based insight, providers typically default to generic metrics such as monthly updates – metrics that provide minimal business value.
Indeed, the stubborn elusiveness of truly outcome-based agreements reflects the scarcity of genuine partnerships in the outsourcing marketplace.
Focus and Prioritize
Strategic SLAs should be tailored to the specific needs of the enterprise. A baseline understanding of the business is therefore essential to gain the insight necessary to develop and support outcome-based SLAs. Prioritization is also key. The CIO should focus on the top ten (or so) SLAs that gauge the overall health of IT and the relationship with the outsourcer, and that enable analysis and improvement. The next layer of more detailed metrics within the SLA contract should be pushed down to the manager level. Relying on generic, cookie cutter SLAs simply adds overhead and distracts the business from what’s important. 
SLAs should combine penalties and incentives. A basic SLA measures a minimal level of performance, and missing that performance should incur a penalty. However, CIOs should go beyond table stakes and build a reward system for service providers to exceed expectations and improve service.
Finally, SLAs for the digital era require digital tools to enable real-time responsiveness. Excel spreadsheets and manual data collection are no longer adequate. Processes and activities around documentation, compliance, contract management and verification need to be streamlined and largely automated via digital inputs and intelligent tools that drive accurate and consistent records as well as autonomous checkpoints, milestones, alerts and verifications. 
With this framework in place, SLAs can transcend their traditional role of historical reference points and become actionable and real-time management tools.

About The Author

Rajeev Tyagi's picture

Rajeev Tyagi, Chief Operating Officer of Softtek US & Canada, heads the company’s automation and artificial intelligence initiatives.