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How to Turn a Service Desk into a Data-Driven Operation

What Does It Mean to be Data Driven?

People rely on data when making decisions every day, often without even realizing it. For example: think about that new pizza restaurant down the street. Are you more likely to try it because it looks good, or because it scored 4.5/5 stars on Yelp, offers dishes between $7 and $21, and accepts Apple Pay?

When you use Yelp, you’re not only analyzing data to inform your decisions; you’re also inputting valuable customer data that businesses analyze to inform their decisions—from the amount of salt in their sauce to the UI of their online ordering tools.

Take Domino’s, for example. As a response to mounting criticism on social media sites, like Yelp, the company embarked on an endeavor known as the “Pizza Turnaround.” The data they gathered not only inspired recipe changes, but also motivated them to design and implement The Pizza Tracker app—a system that allows customers to order pizza from their mobile devices and even track the pizza creation and delivery process. These changes resulted in store growth, rising stock shares, and a 12 percent rise in customer satisfaction scores.[1]

Nowadays, customers and businesses are more likely to make decisions based on data than intuition because decisions based on data tend to produce better results. This methodology is referred to as being data driven, and IT leaders who apply a data-driven methodology to their Service Desk benefit from more insightful Business Intelligence (BI), allowing them to drive Continuous Service Improvement using an IT Service Management (ITSM) framework. As a result, they are able to optimize their performance and make informed decisions about their services, teams, applications, infrastructure, tools, and best practices.[2

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Why Should My Service Desk Be Data Driven?

A Service Desk makes strategic decisions about processes that support a business’s cross-functional goals. Often, these decisions impact budget significantly and have ripple effects on other departments within the organization. As a result, shifting to a data-driven Service Desk can pose a challenge for many organizations, but the benefits of becoming data driven ultimately outweigh the risks for many IT leaders. These benefits include:

  • Data helps IT leadership allocate resources and balance workloads for technicians.
    Ticket data allows the Service Desk to collect valuable information about incidents, identify which technicians are the most qualified to handle certain kinds of incidents, and assign tickets accordingly. This not only enables IT leaders to balance workloads, but also to make staffing decisions based on ticket volume. Ticket trend data may show that 90 percent of tickets are generated during normal business hours, so rather than staffing each shift evenly, the Service Desk may allocate fewer resources during off hours.
  • Data quantifies and measures the business value of the Service Desk.
    Data-driven Service Desks can establish clear, measureable, and achievable goals, and then use quantifiable data to show that those goals have been met, ultimately proving their business value.
  • Data acts as compelling evidence to justify IT budget decisions.
    Hard evidence is much more influential to decision-makers than recommendations based solely on opinion. A data-driven approach allows the Service Desk to provide concrete justification for budgetary requests and IT spending decisions.
  • Data allows support teams to contribute to the overall health of the service.
    Measuring data allows the Service Desk to determine necessary performance improvements and contribute to the overall health of the organization. For example, if onboarding takes three days on average before employees can be productive, the Service Desk may implement an automated onboarding process to set up user accounts and deploy necessary equipment, cutting onboarding time by 40 percent.

Transitioning to a Data-Driven Service Desk

So, how can you turn your existing Service Desk into a data-driven operation? It can be a lengthy process, but before you start, consider the following aspects:

1. Identify Your Needs
1. Identify Your Needs
If you’re making the choice to become data driven, be sure to identify not only why you want to become data driven, but why now. Avoid rushing into the lengthy process of altering your business intelligence (BI) strategy without a clear understanding of what prompted your decision. What needs to be measured, do you have the data, and how will those measurements improve your business?
2. Be Prepared to Change

2. Be Prepared to Change
For most companies, becoming data driven has the potential to affect your corporate culture. This cultural shift begins when IT leaders agree to prioritize data and act as executive sponsors for making a transition. By nature, data-driven Service Desks need to adopt different decision-making processes, assign data management responsibilities, and consider any cross-functional impacts of change.

3. Determine Standards, Methods, and Tools
3. Determine Standards, Methods, and Tools
Most Service Desks use IT Service Management (ITSM) tools that offer a variety of out-of-box data points; however, simply having access to data is not enough. In order to turn mountains of data into actionable information, you’ll need to identify standards, methods, and tools to manage the data you collect. Then, you will need to organize and present your data in a meaningful way, such as a dashboard, to make it useful.
4. Evaluate Your Skills Gap
4. Evaluate Your Skills Gap
Combing through terabytes of complex Big Data is a specialized skill that falls outside the realm of many Service Desks, so it’s important to consider whether your company has the right skill set to make data useful. To address this challenge, many organizations have begun hiring Data Scientists, a relatively new IT position that is underrepresented according to 83 percent of the participants in a recent CrowdFlower poll.[3]
5. Start Small and Scale
5. Start Small and Scale
Use data to drive a small project with minimal stakes before diving into something big. The processes of becoming data driven involves some trial and error, so starting small will allow you to experiment with your processes and with minimal impact to your organization. On the other hand, demonstrating success at a micro level will help you prove the business value of prioritizing data, which will help you secure executive sponsorship and allow you to scale to larger projects.
6. Review and Re-Evaluate Your Measurements
6. Review and Re-Evaluate Your Measurements
Don’t be discouraged if your initial set of measurements doesn’t provide the insight you expected—you can continuously refine the questions your data needs to answer by re-evaluating your existing measurements or investigating new areas for data collection.

Transitioning to a data-driven Service Desk model requires dedication, but forming a carefully planned strategy can help companies minimize the period of trial and error that typically accompanies a data-driven change. Some companies have the bandwidth to strategize on their own, while other businesses may choose to leverage the experience and insight of a Managed Services Provider (MSP) to streamline the transition. In either case, making the switch to a data-driven methodology is a worthwhile way to increase the effectiveness of your IT.


[1] https://www.marketstrategies.com/blog/2014/12/the-pizza-turnaround
[2] http://www.gartner.com/it-glossary/business-intelligence-bi
[3]
 https://visit.crowdflower.com/data-science-report.html

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