January 17, 2024
The enterprise software sector has long been viewed as stodgy and slow-moving.
This should not come as a surprise, given the large up-front investments necessary to install hardware, customize software, and train and support reluctant users.
The landscape of enterprise software implementations is littered with underwhelming—if not entirely failed—projects seeking to transform the business through digitalization.
However, the sector is undergoing a bit of a renaissance, characterized by rapid technological advancements and evolving business models.
As we plunge into 2024, here’s an overview of five key trends that we see influencing the enterprise software landscape.
The Software as a Service (SaaS) model has revolutionized the way many businesses operate.
It offers scalability, flexibility, and cost-effectiveness—and is handily compatible with remote and hybrid working environments.
While early adopters have reaped its benefits for years, we're now witnessing a significant shift among late adopters moving towards SaaS.
This is being driven by the relentless need for digital transformation—transform or die, as some would say—the aforementioned demand for remote working capabilities, and the desire to minimize associated capital expenditure.
The advantages of SaaS are numerous and well documented. It allows companies to access the latest technologies without substantial up-front investment, offers regular system-wide updates, and allows services to scale (up and down) according to business needs.
However, this shift is not without its challenges.
Data security and compliance, as well as the accumulation of subscription costs, are two sources of friction holding SaaS back from total market dominance.
Our verdict? As the developers of a cloud-native SaaS solution, we see this as a one-way trend that’s not slowing down.
Each decade, one or two major technological changes hit the inflection point in their exponential growth curve and break across the landscape like a tsunami.
Right now, it’s generative AI’s turn to shake everything up.
With its ability to create content, automate processes, and enhance decision-making, gen-AI is having a profound impact on enterprise software development and implementation.
It offers new ways to engage with data, automate routine tasks, and personalize customer experiences.
It can generate reports, create realistic simulations for training, and even propose solutions to complex problems.
What could possibly slow this freight train down?
The biggest concerns casting shade on the generative AI party are centered on ethical implications and potential biases in the content and advice it generates.
Debates are also raging about the impact it will have on the workforce, with fears of job displacement doing battle against the potential for enhanced job performance.
Our verdict? We’re still in the very early innings of what will be a long and spectacular game to see who can create the most value with AI-enabled tools. We’re squarely in the human-AI collaboration camp but will take our time to understand where AI is headed and how to develop the most value-adding applications for our customers.
Usage-based pricing models are gaining traction in enterprise software because of the flexibility and potential cost savings they offer, especially for businesses where software usage routinely fluctuates.
Proponents argue that usage-based pricing creates greater transparency and better aligns software costs with business value creation.
In the world of cloud computing, Amazon Web Services (AWS) stands as a prime example of successful usage-based pricing. Their pay-as-you-go model allows businesses to pay only for the computing resources they consume, and has been particularly beneficial for startups and small businesses, which can access high-end resources that would previously have been unaffordable.
Another popular example is the licensing model adopted by Adobe for its Creative Cloud suite. Switching from a traditional perpetual license to a subscription-based model has made its products accessible to a broader audience, including freelancers and small businesses, while ensuring a steady revenue stream.
However, opponents argue that the model can lead to unpredictable costs, making budgeting challenging.
There's also the risk of 'bill shock' if usage unexpectedly spikes.
For example, a sudden increase in the customer base or transaction volume can lead to a steep rise in costs for businesses subscribed to a pay-per-user model.
Similarly, companies leveraging cloud computing services often experience cost surges during periods of high demand, such as seasonal peaks in retail or when unexpected events create operational interruptions.
And then there are unintentional situations where users access premium services without fully understanding the pricing implications, when data analytics leads to extensive data processing, or when advanced AI applications require a dramatic increase in on-demand computing power.
Our verdict? While we’re all for providing our customers with flexible and predictable pricing, usage-based models require careful design and oversight to avoid unexpected consequences. In most cases, we think fixed but modular pricing structures perform most effectively in our areas of focus.
Product-led growth (PLG) is an emerging strategy where the product itself drives user acquisition, account expansion, and customer retention.
Organic growth is driven by user satisfaction and word-of-mouth.
For the software vendor, PLG helps to lower customer acquisition costs and leads to a deeper understanding of customer needs through direct product usage and feedback.
However, it depends on finding strong product-market fit and must deliver an exceptional user experience to be successful.
A less discussed but more insidious barrier to widespread adoption of the PLG model is the difficulty it can cause for traditional sales-driven organizations trying to adopt the new approach.
In some cases, two camps emerge within the same company, with traditional sales and product-led growth running in parallel and often in competition for resources.
Nevertheless, PLG is popular with business users, who have little interest in negotiating with a sales team for months before getting to implement a new product.
In a profound shift, self-service enterprise software means that anyone in the organization can research and adopt the tools that work best for themselves and their team.
In this sense, PLG is driving the democratization of software buying power, putting end users and teams in control of their own technology stack.
You can see why this might not be uber-popular with CIOs and corporations where centralized purchasing controls are still de rigueur.
Our verdict? PLG has its place and will continue to expand in the enterprise software sector. However, for complex software platforms that depend on seamless integration with other elements of the company’s data processing infrastructure, it’s unlikely that users will be allowed individual buying power.
The simultaneous adoption of cloud-based solutions and remote working has led to a dramatic increase in cybersecurity risk and incidents.
Consequently, addressing security and compliance issues has become paramount for software developers and buyers alike.
Businesses are investing heavily to secure their software infrastructure against ever more sophisticated cyber threats, and to ensure compliance with a growing body of regulations.
This includes adopting advanced security protocols, performing regular penetration tests and compliance audits, and training employees to recognize threats and mitigate risks.
Regulatory compliance is an essential part of earning and maintaining customer trust—not to mention avoiding legal penalties.
Our verdict? Ensuring the security of our clients’ data and providing them with optimal tools for compliance monitoring and reporting has long been a core piece of our business. We believe our cloud-based solution is orders-of-magnitude more secure than legacy on-prem and spreadsheet-based systems, and we will continue investing to stay at the forefront of data security and regulatory compliance.
The enterprise software sector is headed for a dynamic 2024. The transition of late adopters to SaaS models reflects a broader move towards cloud-based solutions. Generative AI is redefining possibilities, offering both opportunities and challenges. The debate around usage-based pricing highlights the need for flexible yet predictable costs. Product-led growth is a powerful strategy for organic expansion in certain sectors. Cybersecurity and compliance remain critical priorities.
As we look forward, which of these do we expect to dominate conference agendas and water cooler conversations?
For us, it’s a toss-up between the continued evolution of AI capabilities and the need to address cybersecurity threats in an increasingly digital world.
Whichever ends up topping the charts, both scenarios will significantly shape the enterprise software domain and how corporate leaders think about software development, adoption, and deployment.
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