Enhancing Productivity Using Low Code Technology

Enhancing Productivity Using Low Code Technology

What are some of the major challenges and trends that have been impacting the No Code Low Code Platform space lately?

What it has solved

It is clear to see there are not enough skilled developers in the world to develop the number of apps required to move the digital transformation needle in organisations, with the use of low code technology this is now achievable at scale and pace.

Supporting bespoke applications is not cost-effective and can often result in large amounts of downtime of critical digital solutions, using low-code SaaS has removed some of that burden

What it is yet to solve

Highly complex applications still require a steep learning curve as low-code technology is still evolving, you don’t yet have the same level of complexity a traditionally developed application offers. The use of AI in this space is evolving allowing users to enter free test details of the desired outcome and AI writing the necessary low code to achieve it.

It still very much relies on the data driving it to be at a satisfactory level of quality (especially in the low code BI space) large organisations can still struggle from technical debt in this space.

What keeps you up at night when it comes to some of the major predicaments in the No Code Low Code Platform space?

We need to be careful not to just create ‘Excel in the cloud/app sprawl’, by this I mean shadow IT without any governance or control. We need to ensure we encourage shadow IT in a controlled way creating tramlines to work within and adequate monitoring of the underlying platform. It is essentially to create an open and approachable community.

 

Working with highly sensitive data means we have to utilise a self-service cutting edge governance process for each solution to ensure we do not fall out of compliance is critical to what we can achieve in this space. It is important that we can audit and notify out of the platform on this. Good data governance is important to prevent generating multiple sets of master data, we must utilise data cataloguing technology to enable users to self-serve on master datasets.

Can you tell us about the latest project that you have been working on and what are some of the technological and process elements that you leveraged to make the project successful?

A productivity app was recently developed to capture delays of engines going through the test cycle. This traditionally was managed using a paper-based system and transformed into more structured and robust solutions as part of a larger programme (Project 10) aiming to test all engines in under 10 hours.

Using the low code solution RR Civil is now able to capture test delay cause data at a granular level to look for insight helping to prevent this reason for delay happening again, or at least reducing the time. Having access to data like this in a structured and robust fashion will allow for the utilisation of AI to predict potential future delays allowing the business to plan accordingly. This data is now easily auditable and stored in a secure environment removing the risk of data loss or corruption. This solution was built by the engineering business and supported by the engineering business giving them the control required to be agile.

What are some of the technological trends which excite you for the future of the No Code Low Code Platform space?

We are starting to look into low code RPA allowing us to automate day to day processes across our different enterprise systems in a secure and compliant way. Low-code data science platforms will allow us to put the technology that allows us to predict the future in the hands of the business SME’s and quickly gain insight. Low code augmented reality will become critical to the build and manufacture of our engines on the shop floor.

What are some of the technological trends which excite you for the future of the No Code Low Code Platform space?

We are looking to run sessions at some upcoming conferences with our strategic partners to give insight as to how we have approached the use of such low-code technologies in a sector that deals with highly classified data and security constraints.

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