All posts by [x]cube LABS

[x]cube LABS is a leading digital strategy and solution provider specializing in enterprise mobility space. Over the years, we have delivered numerous digital innovations and mobile solutions, creating over $ 2 billion for startups and enterprises. Broad spectrum of services ranging from mobile app development to enterprise digital strategy makes us the partner of choice for leading brands.
Shot Learning
Blog

Few-Shot Learning: Everything You Need to Know

Table of contents

Introduction

So you’re setting up face recognition for yourself on your mobile device and it requires thousands of your pictures to recognize you and unlock your phone. Sounds like a technical nightmare, doesn’t it? But given the need to improve the accuracy of data models, isn’t accruing more and more data only fair?  Of course, the fact that data is the life-blood of any machine learning model and ensures its success holds true. A learning model fed with sufficient and quality data is more likely to yield accurate results. But accruing a lot of data can often get unrealistic and difficult to achieve- given the high costs involved and the ability to manage data.

That’s where a learning model like few-shot learning comes into the picture.

What is few-shot learning?

Few-shot learning or low-shot learning refers to the practice of feeding a learning model with a very small amount of data, contrary to the normal practice of using a large amount of data. The training datasets contain very limited amounts of information. It is mostly implemented in areas  where a model is expected to give appropriate results even without having several training samples, in computer vision, for instance.

Why is few-shot learning important?

A common practice in machine learning is to feed maximum data to the learning model. This is because feeding more data enables better prediction. Few-shot learning, on the other hand,  aims to build accurate machine learning models with training data. It is important because it helps companies reduce cost, time, computation, data management and analysis.

What are the factors driving the adoption of few-shot learning?

Few-shot learning models are driven by the concept that reliable algorithms can be created from minimalist datasets. Here are some driving factors behind its increasing adoption:

  • Scarce data: In the event of scarcity of data, supervised or otherwise, machine learning tools often find it challenging to make accurate predictions and make reliable inferences
  • Reducing data collection and computational costs: Since few-shot learning model requires less data to train a model, costs related to data collection and labeling can be reduced considerably. Additionally, less training data also means low dimensionality in the training dataset, which adds to reducing the related computational costs
  • Rare-case learning: By leveraging few-shot learning, machines can be trained to learn rare cases. For example, when classifying images of animals, an ML model trained with few-shot learning techniques can classify an image of a rare species correctly after being exposed to small amounts of prior information.

What’s the difference between Few-shot learning, Zero-shot learning and One-shot learning?

The aim of implementing few-shot learning is to predict the correct class of instances when a small amount of information is available in the training dataset. Zero-shot learning aims to predict the correct class without being exposed to any instances belonging to that class in the training dataset at all. In zero-shot learning, a learner observes samples from classes that were not observed during training, and predicts the category they belong to. In one-shot learning, the aim is to learn information about object categories from one training sample. The learner is exposed to one instance of each class and is required to make multiple predictions based on it.

What are some applications of few-shot learning?

Given the minimal datasets required and low cost involved, few-shot learning has found uses across multiple areas:

  • Computer vision: Few-shot learning is used in computer vision to solve problems related to character recognition, image classification, object recognition, motion prediction, event detection and more
  • Natural language processing: FSL enables natural language processing applications to accomplish tasks with limited text data. This includes parsing, translation, sentence completion, etc
  • Robotics: To increase robotic intelligence, FSL can be used to train robots. This includes visual navigation, movement imitation, action manipulation and more
  • Acoustic Signal Processing: Sounds can be analyzed using ASP augmenting it with FSL can power tasks such as voice cloning, voice modulation, voice conversion to different languages
  • Few-shot drug discovery: A research by the Massachusetts Institute of Technology states that FSL can be used to significantly lower the amounts of data required to make effective predictions in drug discovery applications

What does the future look like for few-shot learning ML?

It has become evident that few-shot learning in machine learning is proving to be the best-fit solution whenever training is challenged by the scarcity of data or the costs involved in training data models. A research by IBM predicts that machine learning will evolve around the following 3 major segments in the future:

  • Classic ML: One dataset at a time, one task and one heavy training
  • Few-shot ML: Heavy offline training, then easy learning on similar tasks
  • Developing ML: Continuous learning on various tasks

We can see that machine learning has undergone enormous growth in recent years. The increase in advanced algorithms and learning models, the powerful computing capabilities of machines, and big data management have all contributed significantly to this growth. A point to note here is that we can’t claim yet that ML advancement has reached its pinnacle. We will continue to see more breakthroughs in the form of techniques, optimization and use cases. It is, therefore, in the best interest of businesses to quickly identify their “intelligent” needs and adopt relevant solutions at the earliest.

If you’re a business that’s looking for adoption of AI and ML solutions and needs guidance on various opportunities available for them in this domain, get in touch with us.

Cyberpunk
Blog, Cyberpunk 2077, Sony Playstation

Sony Pulls Cyberpunk 2077 from the Playstation Store: All You Need to Know

Table of contents

Introduction:

A game 8 years in the making, a much hyped launch featuring collaborations with major tech companies with themed merchandise, celebrity endorsements and PR: sounds like the formula for great success right? However, it’s been proven time and again that all show and little go usually takes one nowhere, and that sad fate seems to have befallen Cyberpunk 2077. From what was anticipated to be one of the biggest launches of the year, the release of Cyberpunk 2077 has now turned into a PR nightmare, in true post-apocalyptic Night City and 2020 style.

Development Journey:

Looking back at 2012, when the project was first announced by CD Projekt Red, it barely created a ripple. With no launch date announced and the studio mainly focusing on its Witcher series, resource allocation for the new title was limited. However, over the next few years, the studio managed to consistently release teasers that began piquing the curiosity of the gaming community. Following the release of Witcher 3 in 2015, when a larger team was assigned to work on Cyberpunk, threads were started on what the game genre would be and enthusiasts started following announcements closely, assuming the release to be announced soon.

It was in 2017 when Projekt Red received a grant of $7 million from the Polish government, the largest cut of Poland’s national center for research and development fund yet, that a large part of the gaming world began to sit up, take notice and actively report developments on the game, driving an increasing fan following for the title’s social media accounts. Those accounts, however, were pretty dormant with no new trailers or release dates in sight. As speculations continued, the wait for official word finally ended in 2018 when the company finally began posting updates and even a peek of the early gameplay. Throughout the year, more trailers followed which gave rise to innumerable discussions, debates, memes and ultimately, a ton of interest for the product. Demand for a release date grew stronger, but the company remained tight-lipped on that till 2019.

2019 came along, and we finally had a release date, which was revealed to be April 16, 2020. The gameplay videos, characters and Night City were all receiving a great deal of attention, praise and critique by then. The art style looked good, the story relatable, Night City looked like it had just the right mix of adventure mixed with danger that you, as a cybernetic, mercenary hero, would like to explore and the studio definitely had accolades and pedigree going for them. Adding to the hype was the revelation of Keanu Reeves as Johnny Silverhand.

However, come 2020, in the first of multiple delays, the release date was pushed from April to September as the studio announced they needed additional time to playtest and fix bugs. With resource crunches and the COVID-19 situation adding to delays, the title was further pushed to November 19 and then to December 10. By November, themed merchandise started to appear with Cyberpunk branded Adidas sneakers, a custom, special edition OnePlus 8T mobile phone from OnePlus and others. With media blitz well and truly at its peak, we were finally able to get our hands on the game on December 10.

The Breakdown:

By the time it launched, Cyberpunk 2077 had amassed enough pre-orders to cover its entire development cost, making it one of the greatest hits of CD Projekt Red even before launch. However, the good news ended there as soon after release, complaints began pouring in about a host of performance issues hitting consoles, mainly the previous gen Playstation and Xbox, hard. The game, which eventually emerged as an open world RPG, received praise for story, art and gameplay but with bugs hindering progress in various ways, players were left frustrated with the evident lack of quality control for a title that’s been so long in the works.

While the players on PC are having it better, performance on previous generation consoles are especially worse. Apart from weird animation glitches, players have experienced crashes, lags and areas in the game that appear literally broken and unplayable. The severity of these has since resulted in CDPR issuing an apology and refunds to disgruntled players on these platforms.

Latest Developments:

As complaints kept mounting, CDPR stock prices crashed by over 30% and Sony decided to remove the game from its Playstation store on December 18, issuing notices to players that they’ll be eligible for a full refund. As for those with physical copies, CDPR says they are hard at work on patches that will help resolve ongoing issues and have their own refund programs running. While stock prices may not be the best indicators of company value at all times, there’s no denying that such a high profile launch going so wrong has definitely dented confidence in CDPR in a big way. The gaming community is historically extremely vocal and unforgiving of highly anticipated titles exhibiting obvious glitches and no matter how fast the company manages to release patches, it will be a while before they can rid themselves of this nightmare.

The Way Forward:

While it’s unfortunate that CDPR will probably have to slog through the holiday season to work on fixes, it’s in their best interest to ensure that happens. The right step to rectifying any error is to acknowledge it and encouragingly, the management has done that by admitting the rushed launch in response to growing demand was a mistake. The studio now needs to ensure players are adequately compensated with refunds, store credits and more and also develop a clear plan on eliminating the problems. Players, we’re sure, would be willing to wait if the developers can demonstrate that the fixes are genuinely coming together and the eventual quality will be worth the extra time. Amidst all this, the clear message to companies, as well as product owners, is to keep the marketing hype in check till they are assured of the product quality. A broken product that brings in a ton of money initially but goes on to cause irreparable damage to company reputation and standing among loyal customers should never feature in release plans, no matter the demand.

5G Network
5G Network, Blog, Digital Transformation & Innovation

What is 5G Network and What Does it Mean for Tech Innovation?

Table of contents

Introduction

A per IHS Economics’ report  “global 5G value chain will generate $3.6 trillion in economic output and support 22.3 million jobs by 2035.”

World is talking about 5G not only because it provides faster  internet speed or can support multiple devices at a time, but also it can bring positive changes in working conditions & styles.

Why Is 5G So Important?

We all have seen internet evolution from 1st generation to 4th generation and with each new network we have observed massive growth, changes in business and human needs.

5G’s promise to deliver ultrafast speed with low latency and increased reliability and flexible connectivity. It provides organizations a free hand to deploy both communications and computing infrastructures across location, organization can configure internal networks to address capacity, availability and requirements for lag free connectivity experience.

Global 5G landscape

The United States, South Korea, and China are the Market Leaders as they have already implemented 5G and are spearheading the 5G revolution.

India, Brazil, and Mexico are the Emerging Markets in the developing world.

How 5G will be used:

Use cases for eMBB, MIoT and MCS:

How 5G adoption can transform industries?

Most organizations are dependent on internet connectivity and in recent times due to COVID-19 we have created new ways to work. 5G can transform all industries with its effective use. Let’s see a few areas where adopting 5G can become a revolution:

Healthcare: Healthcare systems have changed a lot in 2020 due to COVID-19, Telemedicine & Telehealth have taken the place of direct consultation OPD.

Healthcare systems have complex, massive data transfer and analytic needs, hospital administration can benefit most from 5G due to its low latency and high data throughput to use innovative applications in areas like remote surgery and patient care with swift network and connectivity.

Get to know more about Telemedicine & Telehealth.

Self-driving cars: The life saving technology “vehicle-to-vehicle communication” may hit the roads in coming years and  with next generation 5G connectivity where the improved latency rate will allow vehicles to quickie connect, share their live location, speed, acceleration, direction, and steering.

Drone Services: As many companies are planning to use drones to deliver doorstep services, 5G will enable accuracy and real time tracking and controlling their traffics so that they don’t hit each other in operations and work efficiently in delivering tasks.

Manufacturing & CPG Industry: Supply chain, asset tracking & inventory tracking will be easy in manufacturing. Whereas, a major shift is observed in CPG from walk-in stores to online stores and people are doing most of their work using phone applications where speed is the differentiating factor. We have seen some companies have begun investing in VR/AR stores. 5G brings more opportunities and companies have a lot to innovate in this category. Read more about VR.

Public Places & Home: We have moved to the internet of things to do our jobs, share our lives on social platforms by uploading massive amounts of data coming from video audio files and live streaming with higher speed and precision, 5G will attract more business and investment to leverage technology with its ultrafast speed.

Smart Cities: As research report by statista shows “5G has the capacity to unlock the full power of the 30 billion IoT devices expected to be connected by 2030.”

5G opens doors for IoT enabled devices in configurations of dynamic and robust environments in smart cities where laying fixed cabling is cumbersome and uneconomical. Active management of its high capacity networks need to be interconnected with streets, buildings, public and personal devices, 5G can become an integral part of the whole IoT system.

Industry-specific Factors that may impact 5G adoption:

We have seen the true potential of the internet in COVID-19 where the internet played a vital role in fueling business needs from home.

5G adoption can advance the IT industry & its future. In fact, PSB research reports 91% of IT managers believe 5G will drive new products and services that have yet to be invented. Moreover, a report from IHS Economics predicts that the 5G will enable $13.2 trillion of global economic output by 2035 and the 5G value chain will support 3.4 times as many jobs.

The technological challenges we are facing today are shaping next generation tech advancement. Learn how we at [x]cube LABS are leveraging them to craft innovative solutions and solving problems for enterprises.  Explore [x]cube LABS’ services.

The Internet is transforming lives around the world but with greater speed, it can add more value to industries and lives depending on them, to know more, connect with our experts- Contact Us.

Artificial Intelligence - Agriculture Industry
Agriculture, Artificial Intelligence, Blog, Digital Transformation & Innovation

5 Ways AI and ML are Transforming the Agriculture Industry

Table of contents

Introduction

Agriculture is the oldest and the most pivotal profession known to mankind. We cannot put a date to when agriculture as an activity began but it is well recorded that agriculture techniques have been transforming from century to century in order to gain more bountiful yields from the crops. With the growing number of people on Earth, the needs have grown exponentially but it is very well known that resources are scarce. This has left a lot of scope for innovation and the technology advancements in the past couple of decades have proven to be a ray of hope for better yields and efficient agriculture techniques.

Worldwide, the agriculture industry is estimated to be a $5 Trillion industry, which is more than the GDP of a bunch of small countries. This lays emphasis on how not only agriculture forms the means of survival but how important agriculture as an industry is as it forms a substantial share of the world economy. The industry has been adapting Artificial intelligence (AI) as a means to better their efficiency in all aspects.

Scrutinizing farm data for better results 

The agricultural land produces millions of data points everyday, AI has made collection and analysing of those data points possible. Farmers are able to make informed decisions in time, it has been an age old problem that has been solved through the application of AI. The farmers have been able to judge weather conditions beforehand that has aided them in choosing the right time to sow their lands, water usage is another problem that has been solved through AI.

AI has made evaluating hybrid seeds and their yields even before actually sowing them into the lands which has left very less scope for failed harvests and upping the productivity.

Weather forecasting with AI

Not just the bigger agricultural lands and farms but the smaller farms in developing countries have been greatly benefitted with the weather forecasting models that are devised through application of AI. Forecasting has helped farmers into making accurate decisions when and how they should be harvesting their lands for better productivity. Seasonal crops rely heavily on forecasts as they can’t be grown around the year, there is a specific time frame and weather conditions that the farmers have to adhere to.

Precision Farming and its benefits 

Precision farming is a sustainable agriculture culture technique that is being taken up by a lot of farmers, it has been touted as one of the century’s greatest innovations. PF is a technology backed approach that observes and analyses farm lands to attain effective and efficient agricultural yield. Precision farming comes up with tailored made suggestions for specific crops and plots. The conventional way of using the same techniques for all kinds of crops and land led to a lot of wastage of resources, PF has not only helped curb that but also reduced the overall negative impact on the environment.

Drones and their capabilities

There has been an increase in the use of drones to inspect the farm condition in the recent years. Drones help give a more accurate view of the farm and spot problem areas on the land. Soil and land health are the major factors that affect the eventual produce, it is of grave importance that they are kept under check throughout. Timely diagnosing such issues can help the farmer in the long run and also give them time to control these issues.

A German based startup PEAT has developed one such application, Plantix, that can detect defects through image recognition. Drones can reach far ahead than humans and give out better possible results in pointing out potential improvements that could help better productivity of the farms. There has also been an increase in the use of chatbots to solve farmer’s problems.

Image recognition can also keep a tab on quality inspection, making it a non destructive method of quality check unlike the manual way of doing it. Dlib is one such machine learning library supporting capabilities to detect defects in tomatoes.

Bots and Chatbots in agriculture

The agricultural industry has sought after chatbots since they are more convenient and give out facts and instant solutions to farmer’s problems. With the help of machine learning, chatbots of today have been made so sophisticated that they have recommendations for all kinds of problems faced by all kinds of lands. One such company called Trace Genomics is helping farmers analyse potential problems with their soil using ML. In the recent years there has also been a great amount of research that has been done to come up with the best possible Farm-bot to solve the problem of labor shortage that the industry is facing as there has been a seismic shift from being an agrarian society in most parts of the globe.

Conclusion

Food is the most fundamental need for the world. The global population is only going to grow, hence the requirements for food to keep the population fed will grow as well. The past couple of decades have only established that AI and ML will only make the agriculture industry stronger and more efficient. Even when people shift from working in the farms to moving to cities to find urban jobs, technology is what is going to keep the produce under check and make sure that the global requirements of food is being met.

Digital Transformation
Artificial Intelligence, Blog, Digital Transformation & Innovation

Hyperautomation and its Role in Digital Transformation Across Industries

Table of contents

Introduction:

As per Gartner’s prediction report “by 2022, 65% of organizations that deploy robotic process automation will introduce artificial intelligence, including machine learning and natural language processing algorithms.”

Hyper-automation tops the list of “Top 10 strategic technology trends in 2020” by Gartner but what is hyperautomation and why do we need it?

How does Hyperautomation work?

Hyperautomation is a blend of advanced technology pools like:

  • Artificial Intelligence
  • Robotic Process Automation
  • Intelligent Document Processing
  • Intelligent Process Discovery
  • Advanced Analytics
  • Digital Operational Tools

Gartner’s research says ”Business driven hyperautomation refers to an approach in which organizations rapidly identify, vet, automate as many approved Business and IT processes as possible through a disciplined approach. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms.”

Hyperautomation further refers to the sophistication of the automation such as:

Hyper-automation Is Different From Automation:

In automation, a bot or robot is trained to perform certain tasks and optimises a process but in hyper-automation the same tasks are performed with an extra skin of intelligence, where the augment human brain.

How Hyperautomation is used in Digital Transformation?

It has affected many industries since most of the companies are already using digital technology to transform their business needs. A few of the examples are listed below:

Some hospitals have started using the Digital Nurse concept to interact with patients, at the initial stage where doctor support is not required. The Digital Nurses ask patients relevant questions about their health and symptoms to properly guide them to care centres.

Medical transcription uses Machine learning algorithms that allows voice recognition systems to transcribe speech requests into texts. ML models can be trained with thousands of different speech requests to work more efficiently and effectively.

Also, billing and claims can be automated with hyper-automation using AI where it can collaborate bills and claims from different departments and consolidate them and RPA can then submit claims with necessary supporting documentation.

A quick overview of Artificial Intelligence.

Banking institutions have started using advanced analytics in application screening, for assessing the repayment capability of a customer by looking at various parameters which is usually impossible via manual screening. This can help banks in identifying non performing assets.

How Hyperautomation leverages automation technologies?

Hyper-automation is an extension of automation tools used to automate & optimize the process by leavering various advanced technologies together.

Augment your business processes with AI to accelerate hyper-automation. An organization can start by integrating DigitalOps tools with intelligence:

  • Artificial intelligence (AI)
  • Machine learning (ML)
  • Natural language processing (NLP)
  • Optical character recognition (OCR)
  • Conversational chatbots

The DigitalOps toolbox offers a wide array of technologies beyond RPA, such as BPM, workflow engines, decision management suites, process mining, low-code application platforms (LCAPs) and others.

It’s important to plan a way ahead in the journey, lay out a roadmap for your desired outcome and areas that need to be optimized. Once the roadmap is ready, an organization can start exploring their ways to implement hyper-automation.

Below exhibit provides an insight towards the approach to implement:

How Hyperautomation has emerged as a digital transformation strategy for organizations?

Hyper-automation results in creation of dual twin of the organization (DTO)

  • It can reduce lead time by completing tasks in a short period of time
  • It can help reduce extra workforce which can be placed to address other tasks that need human intervention
  • It can free top management who can focus on strategies formation
  • It fetches great revenue by decreasing cost
  • It eliminates risks
  • By optimizing process, it can industrialize and scale the business

At present, Oil & gas industries, mining sectors, healthcare and utilities are attracting hyper-automation.

Gartner projects that by 2024, a minimum of 30% of operational costs will be lowered if companies adopt hyper-automation technologies.

It’s high time that industries take a quantum leap to the future by implementing hyper-automation.

However, working with the right innovation partner can take a lot of overheads off your plate and enable you to build quickly, go to market faster and stay ahead of the competition. If that’s the kind of help you are looking for, get in touch.

Blog, Devops Services, Digital Strategy, Digital Transformation & Innovation

The DevSecOps Approach: Everything You Need to Know

Table of Contents:

Introduction

Shifting to DevSecOps

Why do DevSecOps matter to IT leaders?

What is the difference between DevOps and DevSecOps?

What are the main benefits of DevSecOps?

How to implement DevSecOps?

What are DevSecOps tools?

Conclusion

Introduction

Business leaders around the world who are still on the fence regarding transitioning from the traditional to more digitally-driven methods, explain that a major concern behind their reluctance is the vulnerability of digital platforms to data theft. Those used to end-to-end control over their customer data are often afraid that digital solutions will introduce too many new variables over which they’ll have no control and it only takes one significant security breach to lose the trust of customers.

Shifting to DevSecOps

Looking at instances of data theft that are periodically reported by even large enterprises, such concerns cannot be dismissed outright. However, for businesses to really know their customers better, offer them more convenience and explore new revenue streams, a shift to digital cannot be put off any longer. Even before the pandemic hit the world and forced companies to revisit their ways of ensuring business continuity, one can find ample examples of how a refusal to go digital cost established brands dearly. The way to go, therefore, is to keep the pace of digital innovations up while ensuring adequate security measures at every stage starting from inception. This is where we meet DevSecOps, a culture shift that’s becoming indispensable in the software industry.

Why does DevSecOps matter to IT leaders?

Previously, organisations would keep revisiting the security elements of their software and release periodic updates. Depending on what they found, the frequency of these updates would be monthly, or even yearly. However, modern digital solutions involve a number of components facilitating rapid computing and real-time data analysis. We have seen the rise in popularity of public clouds, containers and microservices which break applications down into smaller parts for greater efficiency. These developments have led to an approach we know today as DevOps. It integrated the development and operations teams into a single, high-performing unit which could build and scale infrastructures without having to go back and forth between multiple teams. 

What is the difference between DevOps and DevSecOps?

These two are different only from the security perspective. Put simply, when you add the security elements right from the beginning of a DevOps approach, you get DevSecOps. In the early days of DevOps, security often failed to keep up with the speed at which code was being written. Gradually, as cybersecurity became more and more crucial, the need was felt to plan development with security in mind right from the beginning. Thus, DevSecOps came into being.

What are the main benefits of DevSecOps?

So how do you stand to gain with a DevSecOps approach? We started the article talking about how business leaders are often afraid to take the digital route owing to data security concerns. Well, DevSecOps addresses this exact pain point. Overall, the benefits include:

  • Security teams function with greater speed and agility
  • Change requests and new requirements are addresses quickly
  • Teams work well together as one, seamless unit
  • Quality assurance for builds happen faster and with greater automation
  • Any issues or vulnerabilities with the code can be discovered and fixed early
  • With top-notch security implementations at every stage, the product shapes up to be of the very highest quality from the PoC stage itself

How to implement DevSecOps?

Before you get into the actual development methodologies, it is important to view the DevSecOps approach as a fundamental, cultural shift within your organization, just like true digital transformation would be. Embracing this change could be a bit daunting at first, but once you realize the benefits, it’ll be clear that the initial hiccups could pave the way for great returns. Roughly, here’s how the system is supposed to work:

  • Code analysis: change your code delivery process to release small chunks of it so that thorough reviews can be done and vulnerabilities addressed quickly
  • Change management: accelerate the process by allowing team members to submit changes and dynamically determine whether to accept or remove the change
  • Monitoring compliance: with increased data gathering and storage, solutions need to ensure a number of regulatory compliances to avoid data being misused. Monitor such compliances at every stage to stay on top of the processes
  • Threat investigation: be vigilant towards emerging threats every time you update your code and take action quickly to eliminate them
  • Vulnerability assessment: once vulnerabilities are identified following quick code delivery, ensure they are assessed and eliminated to make the piece of code robust and error free
  • Security training: ensure your team is up to speed with the latest security advancements and compliance guidelines 

What are DevSecOps tools?

In the initial days of DevSecOps, the lack of automated tools to quickly scan and tweak various code parameters were understandably in short supply. However, developers soon took it upon themselves to craft tools that would complement the DevSecOps process and improve its pace. A few notable ones are mentioned below:

  1. Contrast Assess: Extremely helpful for review and testing, this tool integrates with apps and runs in the background, monitoring the code continuously. As soon as a security issue is discovered, it alerts the team and also enables them to devise fixes quickly.
  1. CodeAI: Taking security fixes a step further, Code AI not only identifies and displays a list of security threats, but also proposes viable solutions to mitigate them.
  1. Grafana: Analytics solutions involve 2 indispensable parts-algorithms for data analysis and an intuitive dashboard to present the results. Grafana is an open source analytics platform that allows you to customise your dashboards as you choose. In case that seems too cumbersome, you can take your pick from a range of community-built interfaces to best suit your needs.
  1. ThreatModeler: It’s an automated threat modeling system that intelligently scans your data and alerts you of potential threats from the entire attack surface by continuously keeping itself updated on new threats evolving globally.
  1. Chef InSpec: As discussed earlier, it’s imperative that you develop keeping all the latest compliance parameters in mind. This tool helps you run automated checks to ensure compliance, security and policy requirements. True to the DevSecOps spirit, these checks are run on traditional servers, containers and cloud APIs at every stage of development

Conclusion

Innovation is an all round process. With technology transforming industries and businesses of all types, organisations are devising creative solutions as well as equipping them with the right armors to protect themselves. For anyone worried about data security, it’ll be heartening to know that partnering with companies that follow the right approaches such as DevSecOps will enable them to achieve the success they deserve while taking care of security that’ll ensure peace of mind. At [x]cube LABS, our top-notch DevOps teams operate with efficiency that gets solutions to market quickly, with zero compromise on security. Get in touch, to discuss how you can put digital innovation on the fast and safe track, with us.

Digital Transformation
Blog, Digital Transformation & Innovation, Retail, Technology

Top Digital Transformation Trends for the CPG Industry

Table of contents

Introduction:

On an average, CPG companies have reported an 8 percent increase in technology budgets over the past three years, indicating an increase in digital technology investments.

Consumer goods companies are more likely to focus on their sales & marketing side, but lately the transition has shifted to providing digital solutions for the manufacturing process & supply chain in Industry 4.

A research done by Mckinsey and IDC says that the percentage of adoption for digital transformation is increasing each passing year and projected to be adopted by at least 89% of the CPG companies.

Below exhibits shows sales impact with digitisation: 

Consumer Shift:

In the CPG industry, consumer shifts are observed especially in their buying behavior. They tend to compare prices, read reviews & check product ratings on their smartphones even when they are standing at a physical store.

To facilitate customer experience, companies are experimenting with mobile apps, PWA and E-commerce websites, VR stores, “click to collect” etc.

Below exhibit shows the future of digital adoption:

The traditional CPG industry has its share of experiences with old fashioned selling and product manufacturing, now it’s going through a major transition where customers are functionally digitized with the new age internet, the new generation of digital customers expect customized and digitized product, where they can have everything on the go with one click.

When a leading company approached us to discuss how they could leverage technology to scale their business.

We strategized and delivered multiple solutions which resulted in a 40% increase in their average revenue per user and a 20% increase in paid users.
Read how it helped them achieve the desired results.

For the past few years, companies have started experimenting with technology and seeing the growth of 70% in goods and services, they are moving towards automation in every step.

Areas of manufacturing, Retail & supply chains where digital tools can observe transformation and advanced analytics to optimize manufacturing processes. 

Like many organizations are using IoT to keep a check on their inventory,  blockchain technology is being used for security and transperancy purpose, it eliminates chances of breach and misuse of data as it needs consensus from all the authorities to make changes, mostly used in banking and data security, public, transparent ledger system for compiling data on sales, tracking digital use and payments to content creators.

CPG Manufacturing:

Manufacturing companies are investing time in Lean Transformation and adding digital technology, lean operations are gaining new heights.

Old methods of working:

For an instance company A has all the resources at place and lean operations but follows a traditional process of collecting data, tracking inventory, receiving orders, sharing information, tracking performance, operation planning, machine data, machine/equipment downtime etc.

Problems:

It’s difficult to analyze huge data with accuracy which can lead to situations where orders will get delayed, sales channels can get affected which leads to delay in marketing.

How digitization could help:

It’s important to understand where a company would like to implement digital technology and what areas, like consumer goods manufacturing, supply chain, sales & marketing.

Above situation could have been avoided had the company invested in cloud technology where they could have real time data for day to day operations and planning new initiatives, improvement plans. Using IoT could track units loaded to ship the products, prediction of machine/ equipment breakdown before occurrence could save time and efforts.

Using analytics  and machine learning could give insights to all operational data in a single dashboard. Management can have company-wide information on intuitive dashboards and heat maps, allowing them to detect performance gaps and compare metrics by product, site, and region etc.

A leading enterprise approached us, we developed a “stock capture transfer” solution that uses machine learning and Analytics to analyze data by which our client can have a 360 degree view of data to gain insights by generating area wise reports, client can track the shipment, manage inventory effectively and coordinate with retailers, the sales team leverage the readily available information.
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    CPG Industry After COVID-19:

    Covid has impacted the CPG industry permanently, consumers have become more aware about their needs and urge to buy everything online to be safe.

    CPG industry has to work towards reforming customer experiences as many new segments have emerged as most stocked up & needed:

    1. Preventive essentials
    2. Emergency Homebasics &  staples
    3. Snacks & Baking
    4. Fruits & vegetables
    5. Beverages- Alcoholic & non Alcoholic
    6. Frozen food category
    7. Perimeter food category

    Many companies have accommodated customer needs during lockdown and now the customers have become brand loyal towards the services these companies have provided benefitting the Covid situation.

    And this customer shift is permanent in many ways as they have become habitual to these products and services which guarantee their satisfaction towards product safety and health.

    Yet there are still loopholes to be fixed as many companies couldn’t keep up with the production,supply & demand and customers buy the same product wherever it’s available.

    To maintain these categories companies have to invest heavily on the digital sides to fulfill supply & demand (current and future forecast), the main focus point here is to gain data insights from manufacturing to supply/ availability at stores.

    A large food chain giant approached us. We designed an “on-demand delivery” solution for them. With Upshot AI, the app received increased customer engagement at the platform, it received a high number of downloads within the first month of its launch. Business could retool itself as per customer insights received.
    Read all about it here.

    There are few implications on companies due to COVID:

    1. Companies have to ensure staff safely and product sanity
    2. Optimizing entire manufacturing process
    3. Enhance supply and delivery channels 
    4. Managing/tracking Inventory, SKUs.
    5. Including immunity boosters OTC drugs
    6. Keep a track on global pricing models due to increased demand and availability and marking 
    7. Improving e-commerce applications as per customer shifts and govt norms for safety guidelines

    Setting An Approach:

    How should a company make sure their efforts and time are put in the right direction to maximize company benefits by investing in digital solutions:

    Above mentioned exhibit is a starting step to reach a decision if an enterprise wants to invest its resources and time to pull through a crisis experienced in any step from manufacturing to selling out.

    Going by the current trend of digitization, it will be a bit difficult for a company which is running on an old on paper methodology.

    But as researchers suggest cognitive technologicals innovations like AI/ML, analytical tools, blockchain etc. have benefited companies which adopted it, be it ecom platforms or optimizing manufacturing processes. Customer shifts also prepped CPG businesses to gear up for future forecasts, for which digitization is the key for the future.

    Conclusion:

    To implement digital innovations an organization needs to have people on board with a seasoned workforce who is technologically sound to replicate all your needs while designing your system.

    However, working with the right innovation partner can take a lot of overheads off your plate and enable you to build quickly, go to market faster and stay ahead of the competition. If that’s the kind of help you are looking for, get in touch.