Jump-start your innovation engine by removing barriers and empowering developers


By Himanshumali, Director – Solutions Architect Corp APAC, Mongo

Today, there is little debate about the need for innovation and its ability to have a significant impact on an organization’s fortunes. It’s no surprise, then, that the MongoDB 2022 Data and Innovation Report, based on a survey of 2,000 tech professionals, found that 81% of respondents agree that regularly building new applications and innovative features is critical to the long-term success of their organization.

Given that we live in the digital age, most 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 perform multiple functions, sustainable competitive advantage comes from innovative custom applications. It’s what sets an organization apart and what makes data and developers have a key role to play in this modern economy.

Of course, innovation is difficult. Research suggests that it takes 3,000 raw ideas to achieve a single commercial success. If so, how come some companies regularly come up with innovative products, while others struggle?

One way to explain this could be the concept of an “innovation tax”. For example, the MongoDB study found that while technology professionals spend 27% of their time working on new products and features, they must spend almost the same time maintaining existing systems. For example, developers have to work with complex data architectures, multiple frameworks, toolchains, and programming languages ​​just to make simple updates. This naturally slows them down and prevents them from doing their best. This wasted time that developers have to spend is a big part of the innovation tax. This costs organizations money and development cycles and affects developer productivity. Overall, this prevents organizations from launching innovations that businesses need and customers love.

Growing complexity can stifle innovation

As the requirements for modern applications grow, the underlying infrastructure swells as more stuff is added. In the MongoDB study, 63% of respondents described their organization’s data architecture as complex, while 86% said complexity is a limiting factor when it comes to innovation. This complexity often forces developers to spend time maintaining multiple data models, integrating data sources, supporting legacy systems, and hardening security patches.

Additionally, despite its many benefits, cloud migration and digital transformation also add a layer of complexity. In fact, 60% of respondents said digital transformation efforts are increasing the complexity of working with data. While the cloud helped them innovate, 26% said it made it harder to innovate.

At the same time, regulatory and compliance laws relating to data collection and use are constantly evolving. These changes slow teams down because they consume time and resources.

Facilitating the path to innovation

In the MongoDB survey, respondents identified data security and governance (30%), high volumes of data in different formats (29%), and integration of different data sources (29%) as their greatest challenges. 73% said working with data was the hardest part of building apps. Quite simply, the solution then is to make it easier to work with data.

How can this be achieved? Well, first of all, it is important to invest to better understand the impact of these factors on your team. Here are some sample questions I would use to assess this. Are your developers struggling to collaborate because the development environment is fragmented? Have you noticed that schema changes often take longer to deploy than application changes? Does your current IT environment allow for a 360 degree view of your customers? The answers to these questions should dictate how you manage your applications and data sources.

Teams should look for general-purpose solutions that can solve many different problems. For example, choosing a database with a powerful data model that suits multiple use cases, limiting the number of databases to manage, and helping to simplify data architectures. These technologies promise to radically improve developer productivity, providing developers with the most intuitive way to work with data and a repeatable and consistent experience across multiple application requirements – from backend database to analysis, mobile and looking.

While cloud migration and digital transformation are important, they should also be used to streamline data architecture. Additionally, organizations should use niche technologies when absolutely necessary, while being careful not to compromise the flexibility of data deployment.

With the right approaches and technologies, tech professionals can be better equipped to overcome barriers to innovation.


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