How To Incorporate Automation Into Your Education Tech Stack
As the education industry continues to evolve, leaders are turning to technology to improve operations and enhance the student experience. One key area of focus has been incorporating automation into educational technology stacks. Automation has the potential to transform how education institutions operate by reducing manual workloads, freeing up time for staff to focus on more strategic initiatives, and providing a more personalized and efficient student experience.
Gartner predicts that by 2026, robotic process automation (RPA) and artificial intelligence (AI) will improve the student experience while reducing staff and faculty by over 20% per full-time student . This statistic alone underscores the need for CIOs in the education industry to gain a more comprehensive understanding of incorporating automation into their operations.
In this article, we'll explore the best practices and strategies for incorporating automation into your learning technology stack using insights from Gartner's "4 Steps to Hyperautomation Success in Higher Education."  We'll cover the key steps you need to take to help you make the most of this powerful technology and position your organization for success in the years ahead.
What is automation in education?
Automation in education is using software to complete tasks that were previously done manually. In education, automation is commonly used to streamline administrative tasks, enhance the online learning experience, and manage student data efficiently.
Hyperautomation takes automation a step further because it is a disciplined approach to automating as many processes as possible. This involves the orchestrated use of multiple technologies, tools, and platforms, including artificial intelligence, machine learning, event-driven software architecture, robotic process automation, business process management, low-code/no-code tools, packaged software, and other types of automation tools.
For any change, the process is reimagined with an automation-first outlook.
4 steps to incorporate automation into your learning tech stack
So why should CIOs care about incorporating automation into their learning tech stack? The answer is simple: to optimize and modernize their technology environments. By incorporating hyperautomation, higher education CIOs can streamline processes, reduce manual tasks, provide a more personalized and efficient student experience, and free up staff time for more important initiatives.
When incorporating automation into your learning tech stack, it's important to take a strategic approach to ensure success. This approach can be broken down into four key steps:
Step 1: Define the desired business outcome
When institutions incorporate automation tools, they usually encounter several challenges, from the initial "how to get started" stage to "scaling up." To address these challenges, higher education CIOs must work closely with stakeholders to identify the business problems the institution is trying to solve with a thorough business process analysis.
Institutions have various goals that range from improving enrollment rates to streamlining procurement processes or eliminating paper forms. For instance, an institution may want to automate its recruitment process to improve the prospect and application experience, resulting in a higher conversion of prospects to applicants. To achieve this goal, the institution can provide quick answers to common prospect questions via chatbots and nudge prospects to complete applications.
Or an institution may want to streamline the procurement process. RPA software can automate supplier checks, ensure greater consistency and fewer errors, and make sure there are no conflicts of interest.
The institution's goal could be to eliminate paper forms for faculty-facing processes to automate the faculty onboarding process. Low-code software platforms and workflow software can effectively reduce development time for forms and workflows, prefill forms from university systems, and route the results effectively so action can be taken.
Step 2: Redesign the process
Once it's been decided that automation is necessary, the next step is to redesign the process to ensure it meets the desired business outcomes. This step can help organizations identify inefficiencies and bottlenecks that can be addressed before any automation tools are selected.
The redesign process involves considering four options: enhance, convert, eliminate, and hide. These options are not mutually exclusive and can be combined to achieve the desired results. However, higher education CIOs should not underestimate the time and effort needed to complete the redesign process. Many processes cut across internal teams that may not see the end-to-end process and may be protective of their part of the larger process:
Enhance: Identify steps that you will keep but could work better. Ask yourself what "better" would look like. Is it faster, less expensive, more transparent, or more accurate?
Convert: Identify steps that can be converted to another method. Are there steps that require manual keying today but could be automated because the data doesn't change and the process is static?
Eliminate: Identify steps that can be removed. For instance, you can remove steps in an approval process where the approver adds no value.
Hide: Identify steps that can happen in the background without human intervention. This step can help make the process less confusing to students or employees, especially when the steps don't affect the outcome.
After the process has been redesigned, leaders should ask specific questions about the new process to determine which forms of automation to implement. These questions should cover the following topics:
Workflow: Determine the process's volume, input, processing path, and time frame, and whether it is internally or externally focused.
Data: Consider data configuration, data availability, and data usage, including any ethical or personally identifiable information issues.
Systems: Consider integrations, training and learning, legacy extensibility, prebuilt higher education content, and the skill level required to implement the chosen automation technology.
Step 3: Choose automation tools by mapping needs to tool characteristics
Once the process has been redesigned, the next step is to choose the appropriate automation tools that match the process requirements. To match the right tool to the specific process requirements, it's important to break down the process into its underlying characteristics. The following are some of the key automation tools and their characteristics:
Key automation tools
Robotic process automation (RPA): RPA automates repetitive and rule-based tasks. It works best for high-volume, transactional processes with static input and fixed processing paths or where multiple applications need to be integrated.
Analytics: Analytics software enables data-driven decision-making and is best suited for processes that require a historical view or are predictive.
Natural language processing (NLP): NLP tools enable computers to understand and respond to natural language and are a good fit for processes like customer service or chatbots.
Optical character recognition (OCR): OCR tools convert scanned images or PDFs into editable text and work well to replace processes that require manual data entry.
Machine learning: Machine learning tools enable systems to learn from data over time and are well-suited for tasks that have a large amount of data.
Chatbots: Chatbots use NLP to provide conversational interfaces for users to interact with and can streamline customer service or support.
Intelligent business process management iBPM): BPM tools provide a platform for automating business processes, which is good for processes that need end-to-end process management and orchestration.
Low-code solutions: Low-code platforms enable users to build applications without the need for coding and can help streamline processes that require custom applications.
Step 4: Assess business value change
After implementing automation technologies, it is essential to assess the business value of the changes made. CIOs in higher education must align metrics to desired business outcomes, such as increased enrollment, improved student retention, decreased time to graduation, increased fundraising, and other higher education business outcome metrics.
Cost reduction and efficiency may be part of the picture, but they are not the only metrics that should be used. Business outcome metrics such as revenue increases, student satisfaction improvements, cost savings, error reductions, increasing number of users, and compliance improvements are also powerful drivers to engage institutional leadership and the larger university community in the initiatives.
Assessing the business value change after automation is critical, and the assessment should be in terms of specific, quantifiable value statements. By evaluating the business value change and comparing it to the pre-automation state, CIOs can ensure that the automation initiatives are driving the desired outcomes and adjust the approach accordingly.
Key challenges when incorporating automation
While automation offers numerous benefits for higher education institutions, there are challenges associated with this initiative.
One of the most significant challenges is the need to balance efficiency gains with other important institutional priorities. Higher education CIOs must strike a delicate balance between the need for cost savings and the importance of maintaining quality, retaining students, and securing research grants.
Another challenge is the complex and rapidly changing technology landscape. Higher education institutions face a wide range of technologies with overlapping features, and selecting a single tool for any specific situation can be difficult. It is crucial to avoid becoming fixated on specific technologies, such as AI or chatbots, and to build an IT culture that is focused on the best functionalities of each technology to solve a business problem. An array of technologies can have an exponential impact compared with automation technologies that are adopted in isolation.
Institutional culture can also be a barrier to successful automation implementation. Many higher education institutions have a culture that is resistant to change, making it difficult to gain buy-in from stakeholders.
Finally, higher education institutions must also grapple with data security and privacy concerns.
Automating business processes involves collecting and processing sensitive data, and institutions must ensure that they have the necessary safeguards in place to protect this data from cyber threats and other risks.
While automation offers numerous benefits, it is important to approach implementation with a clear understanding of the challenges that must be overcome. By aligning metrics to desired business outcomes, building an IT culture focused on the best functionalities from each technology, gaining buy-in from stakeholders, and implementing appropriate data security measures, higher education institutions can successfully harness the power of automation to drive efficiency, quality, and innovation.
Are you ready to automate?
It's important to plan and implement automation initiatives strategically, following a series of steps such as assessing the current state, identifying areas for improvement, selecting appropriate technologies, and assessing the business value change.
Higher education CIOs must also align metrics to desired business outcomes and build an IT culture focused on identifying the right tool for the right automation task rather than being obsessed with specific technologies.
By taking these steps and addressing the key challenges, higher education institutions can successfully leverage automation to achieve their strategic goals and remain competitive in this rapidly evolving landscape.
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