So, 2020 did not go as we expected—in really any facet of our personal or professional lives. Our plans were derailed, so planning for 2021 is even more daunting than our normal annual planning. Should we just extend our 2020 plans? Or start over with what we’ve learned this year? What can we expect to come at us next year?
Our 2020 plans did not hold past February. With severe budget shortfalls, continued focus on remote learning and working, and new competitive pressures, little that was planned for was completed. Looking toward 2021, we need to focus on agility and budgetary restraint, so consider a handful of technologies that can be employed to make strategic progress without breaking the bank.
While your development team may tell you they don’t need this toolset and that it will only complicate your architecture, you’ll find great benefit in adopting an enterprise standard low-code solution. Adopting this tech does not mean every user on campus will create applications, but it does mean that a wider group of staff can solve problems efficiently. You will need some rules of the road—but not too many. Reduce your developers’ backlog by reserving the most complex tasks for them and bringing a low-code solution to the table to solve simpler problems quickly.
You may not have to go looking to buy anything here, but you do need to look at the offerings inside the applications you have already purchased. Vendors are surfacing sophisticated AI inside applications. What functions are there that you have not yet explored, that take advantage of a known data model and have been invested in by your partner? These can appear to be shiny toys but can be leveraged to get real AI benefits for little to no additional investment. Are these AI toys that are just for marketing? Or are they real, enterprise-class AI applications? Your mileage may vary, but explore what is there. Your investment will be minimal, as you are not designing the AI or hiring the data scientists.
If you have not already taken a serious look at your integration architecture (as part of your broader data management program), you should be doing this now. iPaaS takes some time from a technical, cultural, and architectural point of view. Give your organization the time it needs to select and adopt this technology; then eventually you can require its use. You can adopt it slowly, requiring any code that is updated to be converted, or initiate small projects, making the conversion function by function. Please do not implement this technology for the first time alongside your new finance, HCM, and student systems. Give it a head start and build your team’s skills.
Investing in a data lake does not mean you are ready to decommission your operational data store, but building your capabilities in operating a useful data lake will bear significant benefits in preparing for that eventuality. Find a cross-functional, burning question that will benefit the institution. Build a cross-functional team to solve it using a cloud data lake, data discovery tool, and visualization tool. Or create some competition between two teams using alternate tech stacks. The technology investment is small to solve a single problem. Your team’s time will be harder to come by in 2021 but worth it for the investment in them and their skills.
What’s not on the short list for 2021 but should be considered?
With some judicious, forward-looking investments, you can bring new capabilities to your institution, which now requires more agility than ever. There is not likely any quick return to the 2020 priorities from our annual plans, so we need to think about how to manage going forward—toward the new, faster-paced, cloud-based and largely remote 2021.
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