By Himanshumali, Manager – Solutions Architect Corp APAC, Mongo
Today, there is little debate on the need for innovation and its ability to significantly impact an organization’s fortunes. So it’s no surprise that the 2022 MongoDB Report on Data and Innovation, based on a survey of 2,000 technology professionals, found that 81% of respondents agree that regularly building new, innovative applications and features is crucial to long-term success of their organization.
Given that we live in the digital age, most of the innovation will come from software and applications, the currency of the new economy. While there is a plethora of off-the-shelf software and cloud services available to fulfill several functions, a lasting competitive advantage comes from innovative custom applications. That’s what sets an organization apart and what makes both data and developers have a key role to play in this modern economy.
Of course, innovation is hard. Research suggests that it takes 3,000 raw ideas to achieve just one commercial success. If so, how is it that some companies regularly deliver innovative products, while others struggle?
One way to explain this could be through the concept of an ‘innovation tax’. For example, the MongoDB study revealed that while technology professionals spend 27% of their time working on new products and features, they need to spend almost the same amount of time on the maintenance of existing systems. For example, developers must work with complex data architectures, multiple frameworks, toolchains, and programming languages just to make simple updates. This naturally slows them down and keeps them from doing their best work. This wasted time that developers must spend is one big part of the innovation tax. It costs organizations money and development cycles and affects developer productivity. Overall, this keeps organizations from launching innovations that businesses need and customers love.
Growing complexity can be a drag on innovation
As requirements for modern applications grow, it causes the underlying infrastructure to bloat as more things are added. In the MongoDB study, 63% of respondents described their organization’s data architecture as complex, while 86% said complexity was a limiting factor when it came to innovation. This complexity often requires developers to spend time maintaining multiple data models, integrating data sources, supporting legacy systems, and bolting on security fixes.
In addition, despite its many advantages, cloud migration and digital transformation also add a layer of complexity. In fact, 60% of respondents said digital transformation efforts increased the complexity of working with data. While the cloud has helped them innovate, 26% said it made innovation harder.
At the same time, regulatory and compliance laws around the collection and use of data are constantly evolving. These changes slow teams down since they consume time and resources.
Smoothing the path to innovation
In the MongoDB survey, respondents identified security and governance of data (30%), high volumes of data in different formats (29%), and integration of different data sources (29%) as their biggest challenges. 73% said working with data was the hardest part of building applications. Quite simply, the solution then lies in making it easier to work with data.
How can that be achieved? Well, first, it’s important to invest in getting a better understanding of how these factors are impacting your team. Here are a few example questions I’d use to gauge this. Do your developers struggle to collaborate because the development environment is fragmented? Have you found that schema changes often take longer to roll out than application changes? Does your current IT environment allow for a 360-degree view of your customers? The answers to these questions must dictate how you manage your applications and data sources.
Teams should look for general-purpose solutions that can solve lots of different problems. For example, choosing a database with a powerful data model that suits multiple use cases, limiting the number of databases that need to be managed, and helping to simplify data architectures. Those technologies hold the promise of radically improving developer productivity, giving developers the most intuitive way to work with data and a repeatable, consistent experience across multiple application requirements — from the core database to analytics, mobile, and search.
While cloud migration and digital transformation are important, they should also be used to rationalize data architecture. In addition, organizations should use niche technologies when absolutely necessary, while taking care that they don’t compromise on data deployment flexibility.
With the right approaches and technologies, technology professionals can be better equipped to overcome barriers to innovation.