Why You Should Be Using AI And Machine Learning For Rapid Development

It is the time of Artificial Intelligence (AI) and Machine Learning (ML) applications running in a majority of the industry. Have you ever thought about an application of AI and ML to be used for agile development, testing and portfolio management?

We all want to deliver better products and meet the customer needs faster. Many companies are using the Agile methods from nearly two decades for faster and timely delivery of products in the market.

What is creating this need for faster delivery?

1. It’s all about data.

We are in the era of receiving instant pleasures and luxuries we desire. With age of instant pleasures “Amazon Now” orders are delivered to your doorstep in just two hours. The continuous and instant delivery practices create new bug fixes and functionality app and daily software for the rapid and instant delivery of products. The digital era has also changed customer behavior in the past two decades. The way customer’s searches, buys, uses and reviews any product and technology is far different. Customers may have a higher expectation from the digital world; the companies have their detailed insights into customer behavior patterns. With in-depth insight, the organizations set a perfect stage online that creates customers.

As the leaders of the digital economy, you strive to deliver on these constant and instant demands. Many organizations have created an agile portfolio management systems to meet the immediate demands. The portfolio management helps the organizations to meet timely market demands. Because of the immediate demands and competitive pressure created in the market, companies need to embrace and adopt new methods.

Artificial intelligence and machine learning is the future across engineering, testing and portfolio management. Imagine how faster your time will be to market a product if you don’t have to rely on people. With traditional software systems, you need to rely on your team or within your code. AI has a system that will automatically predict the accurate schedule of the product delivery.

Imagine a smart machine could do everything for you, look for patterns, coding anomalies, changes in team output or analyze plans for deliverability. An intelligent algorithm will analyze changes in team output and overlays your development data to detect issues and learns how to predict their frequency and impact. This concept can also be used in your portfolio management where the AI and MI recognize trend/misappropriation in investments, funding allocations and program derailments.

This is an excellent option for an agile and program management office. But most of us far away from the stage of artificial intelligence or machine learning. The crux is, what can we change today to put us on the path of fast delivery. Can we do this with careful planning and better programs without AI or ML?

2. Getting Your Data In Order-

It is a massive world of application and software delivery; organizations need transparency when it is about agile work and portfolio team management. Companies should create a way to energetically visualize, plan and track work across their entire portfolio. You need to create a dynamic visualize, plan and track work in the whole portfolio. For delivering products to the customers as per their demand with speed and precision organizations need to create a format where access is available of the right data, at the right time in a format that makes everything accessible and actionable.

Having a divergent team is not enough especially without roll-up capabilities to run any project faster or harder. This system comes up with new problems with a mix of delivering the customer value. The team members need to spend quality time to understand each other, to understand what exactly they are building and how the strategy will connect to the execution of work. They need to understand why their plan is not working. Any organization needs to have a clear vision, without a clear vision your company is jeopardizing the product or software that is built for the same.

The future of agile planning and data reporting lies in the hands of clean and customized data reporting and manipulation. Organizations can get a centralized storage system like the Docupile to standardize their program, project and work structure. A well structured centralized storage system not just helps in organizing projects but it is also future-oriented with advanced technologies like self-service business intelligence or a machine learning based predictive analysis. As leaders, we need to deliver “Now” as per our customer’s demand.

Use Agile Data For Predictive Plans

With time organizations have also advanced the agile systems, data analytics, and metric needs. The advanced agile systems can compile and synchronize data across many teams or an entire portfolio.

Organizations may be flying blindly without having a clear picture of how teams are precisely working and delivering their work. Hence, Agile metrics has a bright future ahead as it has concrete efforts in gaining accurate visibility.

The hierarchy image for a better business outcome with Agile data discipline-

 

AI and Machine Learning

It is time to turn your organization into an AI and ML platform. Using Agile data is one of the parts of implementing artificial intelligence and machine learning. What are your views on Agile data and implementation of the same in your businesses?

 

2018-09-07T04:30:22+00:00

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