Analytica - February 2023

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About Us

Organon, the Analytics Club of IIM Rohtak is a student-driven initiative whose basic idea is to generate and cultivate student interest in Analytics and technology. Our primary goals and responsibilities include conducting seminars and webinars covering on-demand topics, skills and tools that will help students of IIM Rohtak fraternity gain expertise in various analytical tools. These skills will help students apply analytical tools in their respective fields during placements. We conduct Analytics related events, competency builder events, Case Study Competitions, Quiz questions

5G in Operational Management and Digital Supply Chain in India 01 Internet of Behaviour 04 Predicting the Future: How Machine Learning and Predictive Analytics are Revolutionizing Business Intelligence 08 Content

5G in Operational Management and Digital Supply Chain in India

Indian Institute of Management, Shillong

When 4G was introduced in India in 2012, it was considered the most significant achievement of the decade. However, for India, it was just another step toward the dream of building a better nation. Soon 5G was introduced, which took the technology and operations to a new level and paved a path to a modern and efficient India. With the wide adoption and easy availability of such a technology, it was bound to flourish, and so it is flourishing.

Through the Internet of Everything, 5G technology enables end-to-end connectivity in real-time at a highly granular level and the associated end-toend visibility. India wants to transform its logistics industry digitally, but this effort has yet to be stymied by its inability to bring advanced technology to be remote and rural areas A recent survey on rural internet connection shows that around 50% of Indians have very poor or no connectivity to digital services Due to significant technological expenditures, the shift of the supply chain from independently managed systems to a linked network has excluded more petite supply chain actors from its operational and productive advantages. Businesses with modest technology budgets may benefit from the quick adoption of 5G connectivity and its performance

by establishing less expensive, centrally managed, unified networks to automate procedures and build cutting-edge digitalized supply chains The five main capabilities of the digital supply chain and intelligent operations are that 5G can improve our intelligence, visibility, transparency, dynamic networking, and connectivity. The management and engineering of the supply chain are critical issues in the contemporary economy. Technological advancements encourage rethinking and reinventing supply chain management, operations, and designs from the standpoint of data-driven, flexible networks.

In many facets of supply chain and operations management, connectivity, networking, end-to-end visibility, and transparency are critical drivers of future improvements. There is no denying the advantages of this hyper-connectivity. It is possible to create data-driven, intelligent planning and control models and algorithms. Innovative digital business models can be implemented strategically

Despite the declaration of these and other possible 5G benefits for supply chain and operations management, there is still a paucity of literature on the theoretical underpinnings and structured conceptualization of application areas,

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underlying implementation and usage challenges, and the role of 5G in future transformations of value creation. This conceptual note provides some explanations of the research gap that exists in the operations.

The interfaces of artificial and human intelligence, entailing cyber-physical viewpoints in operations and supply chain management, are rapidly driving the development of digital supply chains. Artificial intelligence and humanmachine interfaces may establish a high degree of connectedness in the supply chain using digital engineering technologies like additive manufacturing, drones, autonomous guided and linked vehicles, and mobile robots. Future industrial networks will be built on collaborative cyber-physical systems used in intelligent manufacturing These networks' supply chains feature dynamic architectures that change over time. Alternatively, structural dynamics are present Notably, manufacturing procedures for various client orders may have unique machine architectures, while flexible stations can carry out various tasks following unique operations inside the jobs. In Industry 4.0 contexts, 5G may assist scheduling and routing choices in customized supply chains. Today's businesses are dealing with supply chain challenges, which should be considered a long-term challenge that should be resolved as soon as possible. Using 5G in supply chain operations can foresee significant disruptions and suggest solutions to lessen them.

The supply chains that are IoT-enabled show it. IoT capabilities and sensor-based technologies are now readily accessible and inexpensive Tracking the micromovement of items through any step of the supply chain is possible with instant, quick communication to these devices. Data from these devices may boost productivity by leveraging cutting-edge analytical capabilities, reduce substantial impacts by discovering abnormalities, and improve customer happiness by giving them the most precise progress updates.

5G technology's infrastructure capabilities can enhance data exchange and communication amongst supply chain actors Instantaneous communication between devices helps improve inventories, warehouse space, routes, fleets, and robot operations Data from people, devices, vehicles, and things may be combined to make better judgments and improve performance. To aid decisionmaking, 5G can help connect real-time data from every supply chain node without delays. It can improve digital supply chain twins, which help businesses become more adaptable and resilient by analysing the dynamics of change, comprehending supply chain behaviours, and predicting anomalies

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'5GEnterpriseMarketShareEstimatesfrom2021to 2030'

In order to accelerate their strategic business growth, firms must be prepared to rethink supply chain models in light of the explosion of digital applications and the quickly advancing modern technological wonders.

conclusion

the advent of 5G technology in India could significantly transform the way operational management and digital supply chain are conducted. 5G technology, with its increased speed and connectivity, is expected to bring about a paradigm shift in how businesses function and operate. In operational management, 5G technology can enable real-time decision-making, improved automation, and enhanced efficiency. Its ability to support a wide range of devices and the low latency of the network will enable the use of new technologies such as IoT, AI, and AR/VR for improved monitoring, control, and maintenance of equipment and facilities.

In the digital supply chain, 5G technology can use advanced technologies such as IoT, AI, and AR/VR to track, forecast, and optimize logistics and inventory management The increased connectivity and speed offered by 5G can enable realtime monitoring of the supply chain, leading to improved coordination and responsiveness among supply chain partners. This, in turn, will lead to reduced costs and improved customer service. Overall, 5G technology has the potential to bring significant benefits to the Indian economy and businesses. It can enable the creation of new business models, improve competitiveness, and foster innovation. Implementing 5G technology in operational management and the digital supply chain can create new jobs and boost the growth of the Indian economy. Now we are stepping into a new world full of opportunities to grab all due to the changing and advancing technology.

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Internet of Behaviour

What is Internet of Behaviour?

It is imperative to understand Internet of Technology (IoT) to understand Internet of Behaviour (IoB) IoT is known as the network of interrelated devices that share and gather information with support of internet. With time IoT is getting advanced in its complications With time data present on the cloud is evolving. The collective data available on cloud provides information about a person’s interest, behaviour and preferences. The entire process right from collection of data to analysing and then studying the data from Behavioural Point of View is called Internet of Behaviour (IoB). Collection and use of data to drive behaviours is known as Internet of Behaviour (IoB). Individual’s online activities, modern electric appliances, and wearable technologies such as smart watch, VR headsets, smart clothing etc. collects the data which can provide valuable information about user’s interest and behaviour. Based on human psychology perspective such as purchasing or tracking a brand online helps interpreting an individual’s interest and behaviour by using emerging technological innovations and development in machine learning (ML) algorithm. Indian start-ups such as Epigamia, Unacademy, Kisan Hub are leveraging IoB to their benefit

Facial recognition, location tracking etc. are mapped to behavioural events. Using IoB businesses are now able to make more informed decisions, improve the quality of their products and services as per user’s development and come up with new products or services that required in the market. IoB is the combination of 3 fields: Technology, Data Analytics, Behaviour Science. The analysed data help businesses to find answers on How to market their product or services, promote and develop from behavioural point of view of their target audience.

IOB Market Size

The base year for the analysis is 2021. Historical Period 2016-2021 and Forecasted Period is 2022-2027 covering the whole of India. The growing trend of automation in industrial processes to monitor products and address quality defects in real-time is primarily driving the India Internet of Things market. India IoT market is expected to exhibit a CAGR of 13.87% during 2022-2027. In India, the sudden outbreak of COVID-19 pandemic has led to the rising adoption of IoT owing to the increasing demand of automation to remotely enhance security and operational efficiency especially during the lockdown scenarios

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Based on the vertical, Indian IoT market can be bifurcated into Healthcare, Public, Transportation, Retail and others. Currently the energy sector accounts for the majority of the market share.

Competitor Analysis

Leading providers of in IoB are management consulting firms like MBB, Big 4, Roland Berger, Alvarez & Marsal, AT Kearney, Indian and global software service providers and behavioural analytics start-ups In the industry, software engineering service providers, system integrators and consulting firms don't have any specific Internet of Behaviour dedicated solution or framework but they reinvent and recreate IOT offerings after coupling with behavioural science to provide IOB services.

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IOB Technology Stack & Use Cases

1.SaaS Platform

Growth Drivers for IOB Platform:

Real Time Insights: Businesses are changing from being ‘Reactive’ to proactive & real time customer engagement

Need for Automation: Huge focus on automation of human led processes to reduce cost and improve efficiency

Data Backed Forecasts & Predictions: Growing need to accurately predict business scenarios for improved decision making

Enablers for IOB Platform:

Big Data: Growing volume and variety of available data available with businesses

Low Cost Processing Power: Exponential growth in processing power especially due to onset of cloud

Declining Storage Costs: Increasing affordability of storage solutions for use in case of large data sets

Technology: Data collection & mining using emerging technology touch points

Stakeholder Mindset: Behavioral patterns, desires, wants and psychology of internal and external stakeholders

Future Strategy

1 IoB faces the challenge of collecting, storing and using data. It is impossible to monitor the level of access, and therefore, all organizations must be mindful of Internet of Businesses’ responsibility to use it

2. Software that actually connects users to a whole network from a single application continues to be bought by Google, Facebook and Amazon without their authorization.

3. In addition, there are considerable legal and security challenges to the freedom of privacy that are different between jurisdictions worldwide.

4 In future, this will explore the consumer experience from the beginning and the end. This will handle the consumer's interest in the product starts, his journey to buy up to the point of purchase and build further contact points to enable positive customer engagement. It will also discover new ways to engage with customers to interact with the brand before purchasing.

5. The Internet behaviour concept involves an overview of user behaviour, including knowledge about how they live on social networks and other media. Data is obtained via the web of ordinary consumers, coffee makers, thermostats, home control systems, wearable devices, etc It is used for obtaining information on developments

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in each person's lifestyle and, in turn, can provide an awareness of the use of such goods and services.

6. For the market analysis, IoB will supply sufficient data It may also be used to improve the safety of facially recognized public locations. It would provide people with more market possibilities. It would reduce industry monitoring costs. This provides a more tailored product and service targeting to deliver a more fabulous consumer experience.

7. In the modern age, Smartphones will trace our online activities and recognise our positions in real life. There are emerging new applications and solutions Deep behavioural trends and customer insights can be understood and transformed into practical approaches to affect our conduct.

8. A significant number of people are almost tied to our computers, making our devices the apparatus that is most apparent for companies to analyse and change their behaviour.

Implementation of XAI to tackle cybersecurity issues:

Attempting to influence and change user behaviour is sensitive, as it may encounter resistance and other psychological factors related to comfort and trust.

Emerging technologies such as XAI (Explainable Artificial Intelligence) will help provide the user with the required understanding and trust of any system that uses AI models. XAI aims to use methods and techniques to explain to the user what an AI model does and why, thus, giving a better perception of system operations. Therefore, the process of tracking, analysing, and influencing user behaviour will become much simpler.

Marketing Strategies

Increase traffic by having Q&S related to consulting services & IP platform, hence enhancing a chance for search keywords matching the page content, allowing content quality and optimization

Freelancing content writers and bloggers for writing about IOB, Digital Transformation and Tech Consulting

Animated Explainer Video which can be used in YouTube ads for internet advertising

Sending IOB and digital consulting reports to directors & above of Indian technology companies and service providers via e-mail marketing

Giving interviews to Your Story and Entrepreneur India

Putting up blogs and content on LinkedIn and YouTube

Preparing case studies based on IOB and publicizing on LinkedIn

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PredictingtheFuture:HowMachine LearningandPredictiveAnalyticsare RevolutionizingBusinessIntelligence

In today's world, we all want to know what's going to happen next, whether it's the weather, the stock market, or even the outcome of a sports game. And when it comes to running a business, predicting the future can mean the difference between success and failure That's where predictive analytics and machine learning come in. These technologies are like having a crystal ball for your business, allowing you to make smart decisions and stay ahead of the competition So, forget about tea leaves and tarot cards – it's time to harness the power of data to see what's coming next!

With predictive analytics, you can uncover patterns in your data that you might not have noticed before. It's like having a secret weapon that can help you identify potential risks and opportunities before they happen. Plus, by using machine learning algorithms to analyze your data, you can make even more accurate predictions and stay one step ahead of the game

And the best part? These technologies are becoming more accessible and easier to use than ever before. You don't need to be a data scientist or have a PhD in computer science to take advantage of them. With the right tools and a bit of know-how, any business can start using predictive analytics and machine learning to improve their operations and make better decisions.

So, whether you're a small business owner or a Fortune 500 executive, it's time to start thinking about how you can use predictive analytics and machine learning to predict the future of your business Who knows, you might just be the next Nostradamus of the business world!

Have you ever tried to find a needle in a haystack? It's tough, right? Now imagine trying to find a particular needle in a stack of needles That's the challenge that businesses face when they try to analyze data without the help of predictive analytics Sure, they may be able to find some insights, but they'll have to sift through a whole lot of irrelevant data to get there Predictive analytics is like a magnet that can find that needle in the haystack of data, and it does it faster than you can say "needle in a haystack." With predictive analytics, businesses can see patterns in the data that they never would have found on their own, and they can use those patterns to make better decisions It's like having a crystal ball that tells you what's going to happen in the future (except it's not as mystical and it won't show you the winning lottery numbers).

So, whether it's predicting which customers are most likely to leave or which products will sell the best, predictive analytics gives businesses the power to see into the future (sort of). And with that power comes great responsibility.

I.K.GujralPunjabTechnicalUniversity(IKGPTU),
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SWARAJSWAIN
Jalandhar

Just think, with great predictive analytics comes great predictive responsibility Okay, that might be a bit of an exaggeration, but the point is, predictive analytics is a gamechanger for businesses that want to stay ahead of the curve.

But predictive analytics isn't the only cool kid on the block Machine learning is also making waves in the world of business intelligence. You know how some people say they can "learn by osmosis?" Well, machine learning is like that, but instead of osmosis, it uses algorithms. By analyzing data and identifying patterns, machine learning algorithms can learn and improve over time It's like having a really smart intern who never complains and never asks for a raise With machine learning, businesses can automate decisionmaking and save time, reduce human error and bias, and make more accurate predictions.

All in all, predictive analytics and machine learning are revolutionizing the way businesses approach data and decisionmaking.

They're like a dynamic duo that can help businesses see what's coming and make better decisions. And in a world where data is king, businesses that can harness the power of predictive analytics and machine learning will be the ones that come out on top. So if you're not using these technologies yet, it's time to jump on the bandwagon. Because let's face it, if you're not using predictive analytics and machine learning, your competition probably is

Now, I know what you're thinking: "But I'm not a data scientist! How am I supposed to use predictive analytics and machine learning?" Well, fear not my non-data-scientist friend, because these technologies are more accessible than ever before Thanks to userfriendly software and cloud-based platforms, even non-experts can harness the power of predictive analytics and machine learning It's like having a personal data scientist in your pocket, but without the awkward small talk. Plus, there are tons of resources available online to help you learn the ins and outs of these technologies. There are online courses, tutorials, and even

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YouTube videos that can teach you everything you need to know.

And who knows, maybe you'll discover a hidden talent for data analysis! Just don't quit your day job yet.

But let's be real, no technology is perfect

Predictive analytics and machine learning still have their limitations, and they're not a onesize-fits-all solution. They require careful planning, data preparation, and continuous monitoring to be effective So before you jump headfirst into the world of predictive analytics and machine learning, make sure you have a solid plan in place and the right people on your team. And don't forget to have a sense of humor, because let's face it, there's nothing more entertaining than a machine learning algorithm gone rogue

All jokes aside, predictive analytics and machine learning are powerful tools that can help businesses make smarter decisions and stay ahead of the competition. So if you want to future-proof your business, it's time to start exploring these technologies. Who knows, you might just discover the next big thing. So, how do these technologies work their magic? Well, it's kind of like having a magic 8-ball, but instead of a toy filled with murky liquid, you have a computer filled with data. Predictive analytics uses statistical algorithms to identify patterns and relationships in the data It's like looking at a bunch of puzzle pieces and figuring out how they fit together to form a picture Meanwhile, machine learning uses algorithms that learn from the data and adjust themselves accordingly. It's like having a really smart robot that can learn from its mistakes (if only we could all be so lucky) Together, these technologies can help businesses make predictions and decisions that would otherwise be impossible. It's like having a team of psychic geniuses on your side, except they don't charge an arm and a leg for their services (unless you count the cost of the software and hardware)

To dive a little deeper, predictive analytics and machine learning can be used in a variety of ways. For example, businesses can use them to predict customer behavior, such as which products they're most likely to buy or how likely they are to churn They can also be used to optimize operations, such as predicting equipment failure or identifying areas for process improvement. And let's not forget about their use in finance, where they can be used to predict stock prices or identify fraudulent transactions. The possibilities are endless, and it's up to businesses to determine how best to apply these technologies to their own unique situations.

But like any technology, predictive analytics and machine learning aren't foolproof. They require good quality data and careful analysis to be effective And as anyone who's ever played with a magic 8-ball knows, predictions aren't always accurate It's important to remember that these technologies are just tools, and they should be used in conjunction with human expertise and intuition. After all, sometimes the best decisions come from a combination of data and common sense As the saying goes, "garbage in, garbage out." So before you start making predictions left and right, make sure your data is clean and your algorithms are properly trained. Remember, just because you have a fancy predictive analytics tool doesn't mean you can sit back and let the algorithms do all the work. As the saying goes, "you can't automate everything, especially not common sense." So use these technologies wisely and don't forget to trust your gut (and your human coworkers) when it comes to making decisions. After all, as powerful as machine learning and predictive analytics are, they can't replace good old-fashioned human intuition (at least not yet). So keep your wits about you, stay curious, and who knows, maybe you'll be the one predicting the next big thing before anyone else even sees it coming!

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