Eight technology predictions in not-for-profit for 2020 (part 1)
Posted by William Millard
As an industry partner, it’s a privilege to witness the evolution of enterprise technology, and the change in attitudes that inspire it, writes William Millard, Unit4’s global head of not-for-profit.
The very definition of ‘foundational’ enterprise technology is changing so fast. The former monolithic, on-premise hardware stack — with multiple, disparate applications — has given way to cloud-based platforms with a single, flexible, app-based architecture and common user interface (UI). This has increasingly become recognized as a critical foundation which sets organizations up for meaningful progress on their digital transformation journeys for the realities of today, but more importantly, of tomorrow and the day after.
With that in mind, here are our technology predictions for the not-for-profit (NFP) sector in 2020 (part 1).
1. More CIOs will join strategic leadership teams
NFP organizations will continue to throw off the traditional strategy of investing in technology at a functional or departmental level, and switch to an organization-wide architecture approach to solving challenges with technology. As such, we’ll see more NFP organizations hiring chief information officers (CIOs) with increasingly strategic responsibility for how digital supports the enterprise. They will also be crucial to ensure the smooth transition from legacy stack to digital platform and the cultural change management required to make it.
2. Customer experience is the opportunity to capture and keep donors
Boosting engagement by creating an enhanced customer experience (CX) for tech-savvy donors and constituents will become the key to survival for many NFPs. To achieve this, NFPs need a more unified, integrated platform approach. By integrating the back- and front-office solutions, it will be possible to show stakeholders the direct link between their funding and outcomes. This focus on CX will present an opportunity for NFPs to capture and re-engage donors in 2020.
3. Platform and cloud maturity will revive investment
More NFPs will invest in cloud ERP platforms to future-proof their organizations as cloud technology matures and platform capabilities evolve further, and as other organizations show their success. These technologies are built to scale with you due to their flexibility and extensibility through microservice functionality. They allow you to use and develop applications with common interfaces and connectivity across a shared infrastructure. Combined with the Common Data Model (CDM), artificial intelligence (AI) and machine learning (ML), cloud platforms form the basis of a solid future-proofing strategy. (Read more about NetHope and Microsoft’s CDM.) As such, I predict that platform and cloud maturity will revive investment.
4. Better people experience will sharpen end-users’ focus on the mission
With the improvements in end-user flexibility — made possible by AI, ML, common UIs, plus microservices and low/no-code environment — people in the field will gain new levels of freedom, enablement and engagement. They will be set free from tedious admin and over-engineered head office policies and procedures. They will become more enabled by a common data set for field reporting, which will help them uniformly measure and demonstrate impact across programs, as well as make course corrections along the way. This enhanced people experience (PX) improves employee engagement. By making your people’s work-lives easier, they can get on with the value-add work that drives them; and focus on the mission they signed up for.
Two provisos: this will only be possible through a strong governance framework and with more lean organizational structures that need less intervention and fewer approval levels.
Examples of improved PX we’ll see more of in 2020 will include: using conversational AI through a digital assistant like Wanda; machine learning to enable management by exception; analytics dashboards; augmented invoice capture, smart expense receipt capture, and optimal grant allocation using ML.
Part 2 of this blog will be published here next week.