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June 27, 2017

Fourth Industrial Revolution: Calling For A 'Growth Mindset' Over A 'Task Mindset'

Posted by Carly Cooper (View Profile | View All Posts) at 6:20 AM

Make to learn: Building your first robot [Source: https://www.youtube.com/watch?v=gGOWaKmQ51U]

The World Economic Forum predicts five million jobs will be automated by 2020 (The Future of Jobs, Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution, 2016). Furthermore, research by Frey and Osborne (2013) predicts, 47 percent of the total jobs in the US are in the high-risk category and could be automated or computerized within the next 20 years. Some of the facts, figures, predictions, as well as Hollywood productions (Westworld, Transcendence, Interstellar), have many of us fearful of the impact of artificial intelligence on the future. However, never underestimate the power of human potential.

The debate about technology impacting work is one that goes back hundreds of years. In 1776, Adam Smith wrote 'The Wealth of Nations' in which he described the division of labor - a separation of different tasks for different people in order to improve efficiency (1776). During the (first) Industrial Revolution (1760-1820), jobs were being 'automated'. Productivity increased with the invention of the steam engine and by allocating specialized tasks to workers. Now, one can only imagine the fear in the 1800s of "what will happen to me with this new technical advancement?" But indeed, society survived and even thrived. In the Second Industrial Revolution (1870-1914), the railroad, telegraph and machine tools were invented. In 1930, John Maynard Keynes noted, "The increase of technical efficiency has been taking place faster than we can deal with the problem of labor absorption" (Keynes, 1933). Keynes predicted "widespread technological unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor".

And yet, here we are approaching the Fourth Industrial Revolution. Scholars (Levy & Murname) pose four questions for this new age:

  • What kinds of tasks do humans perform better than computers?
  • What kinds of tasks do computers perform better than humans?
  • In an increasingly computerized world, what well-paid work is left for people to do both now and in the future?
  • How can people learn the skills to do this work?

Key skills, the World Economic Forum has identified will be in demand in 2020 are: complex problem solving, critical thinking, cognitive flexibility, mathematical reasoning, and active learning. And I would add, beyond skillsets the need to bring about a shift in the mindset, encourage a 'growth mindset' over a 'task mindset', and increase an individual's agility to learn. But how? How do we all become learners? One of the ways is to actively experiment, make, and create. The mindset and behavior of design thinkers are geared to focus on human values, have a bias towards action, embrace experimentation, to show and not merely tell, craft for clarity, be mindful of the process, and be radically collaborative.

With the understanding of the trends on the future of work and impact of AI, and an invitation to make with robots at the World Economic Forum - Annual New Champions Meeting in Dalian, China, I set out with a Hummingbird kit to build a robot with the help of my 10 year old niece. The Hummingbird Kit by Carnegie Mellon that I will use to coach executives in China is 'child's play'. Although children often learn by experimentation, we adults like to have a plan. (Spaghetti and Marshmellow challenge anyone?) But it's through experimentation, in a safe place, that we can actually learn. When we first opened our Hummingbird kit, the directions were not included, and so we installed every sensor, server, LED light and turned them all on to figure out how it worked. We googled 'hummingbird robots' to gain inspiration on what others had developed, and then together set out to develop a robot designed for and by a 10 year old girl, with the help and awe of a leader in tech. After several ideations and iterations, we have the robot ready for you to see in the video above. #YayRobots

Change is always a bit scary - imagine seeing the first steam engine. The invention of the switchboard, electronic typewriter, spellcheck, home computer, etc. You may have been one of the individuals that crossed the technology chasm as an early adopter, or you may have waited and watched the on others and then joined in. Innovation and invention happen because of people, our unique creative abilities to grasp change, and improve upon it. As we enter the Fourth Industrial Revolution, may we all reach our own next level of potential - let the robots do some of the routine work and let us be creative and have a bit more fun. #YayRobots.

June 23, 2017

Making Inclusive Growth a Reality─ Addressing Challenges Of IoT

Posted by Sudip Singh (View Profile | View All Posts) at 5:02 AM

Making Inclusive Growth a Reality─ Addressing The Challenges Of The IoT

The Internet of Things (IoT) is becoming the superstructure of modern life. But before we can truly harness its many opportunities, we will have to address its challenges. Machina Research, global advisors on machine-to-machine, the IoT and Big Data, predicts that by 2025, there will be 27 billion connected devices, and the IoT will be worth $3 trillion in revenue.

What will the data generated from all these devices mean to an enterprise? Well, at its best, it could mean an opportunity to reimagine every process in order to optimize costs and resources at every level, and develop new products and services, which may have not yet been imagined. Behind the exciting possibilities of IoT is a mammoth task, when one considers the quantity of data to be analyzed, and the corresponding computing power needed.

In the manufacturing industry, where machines have hundreds of moving parts, it would mean access to terabytes of data per minute. The data collected could include GPS coordinates, weather conditions, images, videos, and more. For this staggering quantity of data to be analyzed, enterprises will have to rethink computing architecture and tools. And enterprises will truly be able to leverage IoT only when they are able to extract the utility value of their data.

Challenges posed by the ever expanding Internet of Things

One of the things that will hold us back from fully experiencing the benefits of IoT is the compartmentalized way of collecting and storing data. It is only when enterprises gain complete control over their data that they will be able to glean deeper insights. Another area of concern is that of data sharing. For instance, the temperature of a turbine would be relevant to the turbine manufacturers, the user, the supply chain network, and the regulator, but unless this data is made accessible to the relevant stakeholders, they will not be able to extract the insights it has to offer . Other challenges in the adoption of IoT that we will dwell on in this post are security, integration, implementation costs, and culture.

Security: While we prepare to embrace increased connectivity that IoT offers, data privacy and device security for tablets, PCs, smartphones, wearables and data encryption for microcontrollers, will need to be tightened. According to an Internet IoT Survey by Machina Research in 2016, 58 percent of enterprises in the US were concerned about security. Data is being transmitted outside the enterprise network to the cloud, and hackers can try to access it at any point - from when it is being gathered to where it is at rest, and in between. Prpl, an open-source, non-profit foundation focused on enabling next-generation datacenter-to-device portable software and virtualized architectures is already trying to address this security concern at the design stage of products by ensuring 'trust readiness' for the silicon chip within a device. In the 'Trust Ready' approach, OTrP (Open Trust Protocol) ensures that a connected device is on a trusted path, is running authentic manufacturer-installed software, and operating in its intended state, so a server can 'trust' the device and the device can trust it is accessing appropriate services . To further barricade against potential attacks, enterprises can ensure that their IoT devices are operating on updated systems and firmware, and that non-compliant systems are prevented from entering the network. With time, organizations will gradually move to a central, device-agnostic security solution that is easy to manage and control.

Complexity of integration: With the large number of devices, apps, and quantity of data generated, integrating sensors and data capture methods into existing systems and software is a challenge. And one that the old infrastructure may be unable to handle. For instance, imagine digital sensors on analog connection now having to manage large volumes of data and that too in real-time.

To integrate existing systems with IoT, enterprises will have to adopt an API-First strategy, choose the best technology in communicating between IoT devices, leverage the cloud for integration, and adopt an API management tool to ensure security and scalability . Edge Computing, a method of adding a network layer below the cloud resolves some of the issues of legacy systems. Edge Computing reduces latencies in the network and prevents bandwidth bottlenecks. More recently, it has been recognized that if IoT must succeed, the current architecture of products will need to be reworked to collect, transmit and store data.

Cost of implementing IoT: While the cost of sensors is falling, the costs of managing underlying networks, cloud storage and analyzing data is not. However, in the long term, implementing IoT is actually profitable as found by MPI's 2017 Internet of Things Study. According to the study MPI, a US-based research and advisory firm, manufacturers were able to increase productivity by 72 percent and profitability by 69 percent after implementing IoT in their plant and processes.

Cultural hurdle: As IoT becomes increasingly pervasive, more and more jobs will become redundant. Ensuring people are ready for the change - enabling them to prepare for it, and guiding them as they transition to intelligent tasks that machines cannot do - can be a daunting task for enterprises. But if done right, it can increase productivity and profitability. A case in point is motorcycle manufacturer Harley Davidson. A few years ago, they found that their core customers were aging, younger people wanted to ride different bikes, and they experienced intense competition. In 2010, Harley addressed their concerns by introducing IoT into their manufacturing process and began a large-scale restructuring process. The results were impressive. 80 percent faster decision-making due to workforce empowerment, continuous asset management that facilitated better decision-making, over six percent increase in production, and improvement in profitability by three- four percent.

Even with challenges, IoT will continue to evolve rapidly as technology advances. Enterprises will be able to derive greater value from the large quantities of data amassed from devices, especially orthogonal data (which can be used without effecting other program functions). This data will lead enterprises to ask farsighted questions, change business processes, make smarter insights-driven decisions, and in some cases even locate opportunities to launch entirely new disruptive business models. The possibilities that IoT has to offer are definitely exciting. And yet, these opportunities can't be unpacked and tested in isolation. This is where platforms such as the Annual Meet of the New Champions, at the World Economic Forum in China enable stakeholders like the government, enterprises and individuals to participate and shape the discussion on IoT with a focus on inclusion.

June 21, 2017

Sustainability: A Decade of Meaningful Contribution

Posted by Aruna C. Newton (View Profile | View All Posts) at 4:42 AM

Sustainability: A Decade of Meaningful Contribution

Building a sustainable ecosystem for our stakeholders through a responsible enterprise has been part of our ethos since inception. This led us to launch the Infosys Foundation in 1996. Since then, the Foundation has worked tirelessly for over two decades to contribute to education, healthcare, rural development, destitute care, and art and culture.

In 2008, we formally launched our Sustainability Policy and committed to the United Nations to become carbon neutral by FY 2018. We pledged to do this by reducing our per capita electricity consumption by 50%, focusing on renewables as our principal source of energy, and reducing our carbon emissions. In 2014, we became the first IT Company in the world to publish a sustainability report in accordance with the (Global Reporting Initiative) GRI G4 (comprehensive) criteria. The Global Reporting Initiative is the world's most widely used standard on sustainability reporting and disclosure. It is adopted by over ninety percent of the corporations when reporting on their sustainability performance.

In summary

In this tenth year of reporting on sustainability, we have achieved 51% reduction in our per capita electricity consumption against the 2008 baseline, a whole year ahead of our target. About 45% of our electricity requirement is being met through renewable energy, and our carbon offset project is well underway. The past fiscal year has brought us several recognitions and strategic partnerships but among our most successful initiatives have been those towards protecting the environment and nurturing 'responsible citizenship' through focused employee engagement. This has enabled us to multiply the impact of our efforts many fold across the larger community.

A Green Conscience

In fiscal year 2016, we became the first Indian company to join the RE 100, a collective of the world's most influential companies, committed to 100% renewable power. In fiscal 2017 we successfully executed an onsite solar photovoltaic plant at our campus in Hyderabad that supports two thirds of our energy requirements for the campus. We also joined the Carbon Pricing Leadership Coalition (CPLC), an initiative by leaders from across government, the private sector and civil society to expand the use of carbon pricing, and set our internal carbon price at US $10.5 per ton of CO2e. This internal carbon price sets us an ambitious target to reduce our carbon emission and become carbon neutral.

We currently have 11.1 million sq. ft. of built-up area across our campuses that are LEED Platinum rated and makes our buildings energy and resource-efficient. We also received the LEED-EBOM (Leadership in Energy and Environmental Design - Existing Building Operation and Maintenance) Platinum certification from the United States Green Building Council (USGBC) for our campus in Pune. With this, Infosys Pune becomes the largest campus in the world to achieve this distinction.

Water is a major concern in India, and we at Infosys have steadfastly focused on improving water conservation through the years. We have 270 injection wells and 25 lakes across our campuses in the country. Our smart water metering program is helping us monitor water consumption and plan efficiency programs. We engage in rooftop rainwater harvesting at our campuses, and our combined endeavor has resulted in an 8.33% reduction in per capita consumption of water as compared to fiscal year 2016. Our efforts to meet the commitment of zero waste to landfill and 100% food waste treatment within our campuses have advanced through innovation and automation.

At Zero Distance to Client and Community

Over 1,35,000 design thinkers at Infosys, at Zero Distance (ZD) to our clients and technology, and have successfully undertaken more than 14000 ZD projects. This has leapfrogged our client satisfaction scores to the highest in the last 12 years since the inception of the survey. Zero Bench (ZB), an engagement to leverage the competencies of Infoscions between client projects has seen 25,700+ small projects and around 280,000 sign-ups from 44,000+ Infoscions.

Powering professional and personal aspirations, Compass, our digital platform with over 110,000 users, also boosts learning and intra-organizational networking. The empathy inculcated in Design Thinking has also benefited employee engagement in the community. For instance, our employee-driven CSR undertakes a host of community activities such as delivering food, water, basic supplies and computer education to underprivileged families and children in villages. In 2016, Sneham, our CSR club in Chennai alone touched the lives of 20,864 people and contributed over 119 lakh rupees worth of commodity items to the community.

Our Campus Connect initiative is another example through which we reached out to 416,185 students in 2016. This initiative focuses on improving the employability of engineering graduates across the country by offering training on soft skills and technologies.

The many other rich contours of our approach to business responsibility can be found in our latest Sustainability Report.

June 15, 2017

Has WannaCry Set A Precedent? Enterprises Need to Stay Prepared

Posted by Shyam Kumar Doddavula (View Profile | View All Posts) at 10:12 AM

Has WannaCry Set A Precedent? Enterprises Need to Stay Prepared

The WannaCry virus attack wreaked havoc in mid-May as it hit over 200,000 computers world-wide. The virus affected computers in 150 countries across North America, Europe and Asia, and the attack was the largest ransomware delivery campaign till date.

The National Health Service (NHS) in the UK was affected. Critical medical procedures had to be postponed, hospitals were unable to admit patients, and ambulances had to be diverted to other hospitals. Doctors had to briefly go back to pen and paper. In China, college and university students found their data encrypted by the virus. In Germany, the railway was affected, as was one of the largest mobile companies in Spain, Telephonica. The virus made its way to numerous other industries and businesses around the world.

The WannaCry ransomware, also known as Wanna Decryptor, leveraged a weakness in Windows SMB (Server Message Block) called EternalBlue, which allows remote hackers to hijack a computer running on an unpatched Microsoft Windows operating system. Once infected, WannaCry scans for other unpatched PCs connected to the same local network, as well as for random hosts on the Internet, and spreads quickly. After encrypting data on affected computers, the ransomware asked users to pay anywhere from $300 to $700 bitcoins to decrypt the data. Users were given an ultimatum of three days to pay-up or lose their data.

Wondering how your enterprise can prepare for these increasingly common virus attacks? Shyam Kumar Doddavula, Associate Vice President, Principal Product Architect, Blockchain Center of Excellence, --Infosys Center for Emerging Technology Solutions (iCETS) explains. In this QnA with InfyTalk, he shared how enterprises can locate potential vulnerabilities, and find ways to protect against future virus attacks.

InfyTalk: After WannaCry, there is much anxiety around virus and hacker attacks. Could you shed some light on how enterprises should respond to such attacks?

Shyam: 2015 and 2016 have seen over a 1000 attacks each . Yes, the scale of this recent attack has been unprecedented and brought the criticality of security back in the limelight. Enterprises cannot afford to respond to a security breach in a reactive manner, and need to have policies that are continuously reviewed, tested, and improved as vulnerabilities are identified. One of the weakest link in an enterprise are its employees. Ensuring they are knowledgeable on the various types of viruses and phishing mails is important. This can be done through awareness programs, which are integrated into the security policy.

If a ransomware is suspected on a system, it should be immediately isolated from the network to stop its spread. And antivirus software with the latest updates should be used to clean the system. If in error, a user does run a file that could contain a potential virus or ransomware, the user should be instructed to quickly disconnect from the network. The virus can be stopped from spreading by shutting down the network and restoring backups.

Viruses and hackers continuously explore and exploit new vulnerabilities in software. Manually monitoring and preventing them is not a viable solution. Enterprises need to invest in technology solutions that can continuously learn and adapt to dynamic situations of threat. At Infosys, we apply machine learning algorithms and AI techniques to immediately detect attempts to breach security. Our solutions find anomalies and correlations across various IT telemetry data in near real-time, like DNS lookups, network flows, proxy lookups, web logs, application logs and others using machine learning algorithms, and automate the isolation of suspected machines for further analysis.

InfyTalk: While WannaCry affected enterprises across industries, do you see any that is particularly more vulnerable than others?

Shyam: Enterprises that do not invest in preventive and predictive IT solutions are vulnerable to virus attacks like that of WannaCry. Enterprises need robust IT solutions that are monitoring their infrastructure and uncovering vulnerabilities. The maturity of implementing security best practices varies by industries. Those industries that have been slow to adopt security best practices have been affected in recent times. Many enterprises in these industries do not have strong security incident handling and response solutions, are slow to install software patches, and protect their assets.

Some of the industries that deal with sensitive data like healthcare are especially vulnerable. In 2016, the industry experienced 450 breaches in the US, almost double from the previous year . 43 percent of these breaches were a result of human error. And these breaches came with a heavy price tag. According to research, each leaked record costs $402 , and when one considers the number of data points related to each individual - social security number, treatment record, payment information and sensitive personal information, a data breach can be potentially devastating to a healthcare enterprise.

InfyTalk: Do you think 'online security' and 'hack-proof' have just been redefined by the Shadow Brokers who stole information from the US National Security Agency (NSA)?

Shyam: Absolutely. The NSA getting hacked only goes to re-iterate that no organization is beyond a malicious breach. An enterprise can have best-in-class security, but it is often the weakest link in the chain that hackers exploit. The way to safeguard against hacking is to adopt a 'defense in depth' policy, wherein all the layers of security are constantly tested to ensure they can withstand an intrusion. Security has to be a collective responsibility. Security engineers need to have SLAs that require proactive monitoring and employees must be made aware of possible vulnerabilities through passive and just-in-time training.

InfyTalk: Data loss is expensive, by way of penalties, regulatory strictures and fines. How do you think enterprises can avert such attacks?

Shyam: Cyber-crimes are slated to cost $6 trillion by 2021 . The solution lies in adopting a proactive, intelligent and comprehensive security management solution. Enterprises should invest in advanced threat detection and prevention solutions which use AI and machine learning algorithms, which can adapt and learn quickly to detect and prevent attacks. A proactive process that focuses on prevention and fast recovery such as installing security updates, disabling unnecessary default settings and taking backups of critical data, is another important aspect. Employees should be trained and sensitized about security best practices like setting strong passwords, and identifying phishing mails.

InfyTalk: What are your thoughts on the ransom being collected in bitcoins?

Shyam: Unlike transactions with credit and debit cards, those with bitcoins are anonymous. This enables the hackers to keep their identity confidential. In the case of the recent ransomware attack victims, were told to deposit the ransom amount in a bitcoin wallet, linked to a bitcoin address . And since these wallets were publically accessible, online viewers could easily monitor the amount being deposited into the wallet. And yet, nobody could know the physical location of the person to whom the payment was being made. This instance highlights the dark side of blockchain, which on the one hand is gearing up for primetime and on the other, its use in the recent ransom case creates a bad use case.

With computing devices increasing and BYOD becoming the norm, enterprises must have stringent policies to protect their network and data. In today's digital economy, it is data that is the true competitive differentiator.

June 7, 2017

AI- Going Beyond Labor Substitution to Data-Driven Experiences

Posted by Sanjay Nambiar (View Profile | View All Posts) at 5:34 AM

AI- Going Beyond Labor Substitution to Data-Driven Experiences

Many enterprises fail to capitalize on the potential that artificial intelligence and automation have to offer by equating it with labor substitution. For instance, I was recently interacting with the client team of a large bank. Their target was to reduce costs of internal and customer transactions by implementing 500-600 Robotic Process Automation (RPA) bots in a single year. They had already tried doing this with a toolset they had invested in, but were unable to meet the target. A few questions on overall process design revealed that they had not really thought through their plan. For instance, they had identified 50 use cases for immediate automation since these had a large number of people associated with them. However, the company did not know how to systematically identify new problem opportunities in the enterprise. I encountered a similar situation in a large manufacturer that was looking at IT outsourcing. They were keen to learn how artificial intelligence (AI) could help them automate work drivers and outsource the rest of the work. A retail customer, on the other hand, had already implemented RPA but needed assistance to leverage AI to respond to evolving consumer expectations.

Consistently engaging in problem finding can be a struggle for enterprises, especially if they do not refer to the data existing within the enterprise. Many of today's enterprises find themselves overwhelmed by data. Unlocking the right data and making it available across the board gives users the opportunity to engage with stakeholders in a more meaningful way than ever before.

Adopting the right approach to AI and automation is crucial in data-driven enterprises. Here are a few pointers that should help you set off on the right course.

Process discovery and design

In the automation journey, the obviously manual processes are the first to be identified. However, rather than a one-time activity, it is necessary to continuously identify automatable processes. For instance, the bank I wrote about earlier was shown how to deploy a 'problem finder' probe by Infosys. The probe unearthed insights on how end-users worked with the current enterprise resources. This enabled the enterprise to identify areas of redundancy and optimization. Sometimes, analytics from these probes indicate that the enterprise needs to digitize their operations more comprehensively, and capture data from their customer interactions, supply chain, equipment, and internal processes to make the right decisions.

In process discovery and design, enterprises have the opportunity to completely reimagine a customer engagement - right from the way data is generated, collected, organized and acted upon. In a retail scenario, it would require knowledge about the brand a customer likes, when the product needs to be replenished, ordering it for the customer in the right amount and variant through a virtual assistant, and placing the order with the right retailer.

Operational execution in automation process design

Enterprises must plan on how to respond to scenarios where robots repeatedly fail. Robots may fail due to changing business processes, and redundancy of the past method of resolving transactions. A scalable method of recording changes in business processes based on actual data, and maintaining a digitized reference-able knowledge hub of the initial process as well as changes, can prevent this.

In industries where enterprises rely on a standardized set of data for decision-making, introducing fresh orthogonal data (data that can be used without considering its effects on other program functions) to supplement data sets already in use can change the basis of a product design and experience. This is how, for example, a large CPG enterprise can identify anomalies in the customer sentiment towards their product, and a positive sentiment towards the competition. This opens up an opportunity for possible change in the customer's product experience.

The senior executives of the large bank with whom I was interacting were impressed by the scalable and repeatable ways of introducing data gathering probes into the various sources of truth, and how these could discover automation opportunities across business and IT operations.

Driving next-generation operating models

In the case of IT outsourcing that the manufacturing client was considering, an AI system of systems could completely reimagine their current model of executing IT programs. The erstwhile 'people only' model can be replaced by a 'people + software' model. So what does this mean? The new operating model could enable 'robot personas' to do the work, and augment it with human personas wherever needed. For instance, the role of an Oracle database administrator in an IT outsourcing deal can be fulfilled by a 'robot DBA' avatar. There can be a similar robot meeting the requirements in an infrastructure scenario or as a 'procurement specialist' in a sourcing-and-procurement business process function.

In conclusion, organizations preparing to automate need to adopt a sustainable process design. Knowledge gained from their current data-driven experience is key to building an automation-based foundation. This knowledge is the fabric of the enterprise. It constantly evolves and learns from past decisions so that evidence-based decision-making gets better with every passing day.

June 5, 2017

How Sustainability is Disrupting Today's Supply Chain

Posted by Jonquil Hackenberg (View Profile | View All Posts) at 12:16 PM

How Sustainability is Disrupting Today's Supply Chain.jpg

Sustainability burst onto the scene ~10 years ago as the price of oil shot past $100 per barrel and the discussion on CO2 concentrations in the atmosphere moved from science labs to the board rooms. The increased dialogue on the environmental impacts of business was a positive development. However, the core tenet of sustainability - optimizing usage of resources - has always been about minimizing costs and maximizing financial performance.

Today, the explosion of data powered by the proliferation of smart sensors, or the Internet of Things, has rapidly raised the competitive bar. It is no longer enough for companies to add insulation to their factory walls and plant gardens on their roofs. To win, they must also embrace big data in a way that stiches together fragmented, custom e-commerce orders with reactive, optimized supply chains and factory production.

This blog post explores the framework enterprises can adopt to be sustainable and deliver on Industry 4.0 targets.

Identifying the benefits of going sustainable

By some estimates, 40% ($36 trillion) of the world's revenue is generated by enterprises that consider 'energy cost and energy source' of strategic importance to their production lifecycles. Of this, 27% of the enterprises are in energy-intensive industries where energy costs account for over 5% of their production lifecycle.

Given the scale of these numbers, improving energy usage by even a conservative 2% has the potential to reduce a whopping $30 - $50 billion from corporate cost structures. Additionally, energy prices are notoriously volatile, giving firms one more reason to reduce this line item and achieve greater margin predictability.

Let's take an example. Imagine knowing the cost of making each unit of a product, say a light bulb or a car. Monitoring energy usage throughout the production lifecycle for a single unit provides data about raw material and energy costs.

Surprisingly, very few firms have this knowledge. Yet with such knowledge, it is possible to make strategic decisions about what time of the day to manufacture the product (when energy consumption is at its cheapest) and when to buy additional energy to manufacture bulk orders of that product. Here, enterprises can use integrated weather forecasting tools to understand when to buy additional, cheaper, renewable energy on the energy exchange market, when the sun is shining, and; even modularise production to maximise the energy potential of a given production line.

As a long-term objective, such knowledge can also drive strategic decisions around investment in own energy production, namely, through solar, wind or biomass. This is particularly relevant for highly energy-intensive industries such as mining.

Where firms are today

With the Industry 4.0 initiative well underway, Infosys Consulting decided to find out how firms in Germany were addressing the energy costs in production. Surprising, 85% of firms acknowledged the potential benefits of energy optimization. But only 15% had actionable strategic initiatives in place to realize these benefits. Fortunately, there is a solution here by way of The Infosys Consulting Value Realization Management (VRM™) Framework.

The Infosys Consulting Value Realization Management (VRM™) Framework


This framework helps enterprises translate strategy on energy consumption into actions that can be measured and valued.

To implement VRM enterprises first define change initiatives that align with corporate strategy. Then map them to operational processes that can trigger the desired change. These process changes are attached to KPIs that measure overall impact. Ultimately, these operational KPIs are translated into value drivers to quantify the contribution of these changes to financial performance.

To give an example, let's consider the German organization Osram. In February 2017, Dr. Olaf Berlien, CEO of Osram, noted in his address at the annual general meeting that the company wanted to leverage innovation to open new lines of business in support of energy-efficient smart cities. This aspirational statement serves as the strategy component of the VRM framework.

Translating this strategy into process changes required supply chain modularization and the installation of predictive analytics to measure equipment downtime. This introduced energy efficiency within both the production process and the end product − supply chain planning, production planning, and procurement.

The corresponding operational KPIs to measure these process changes were: lead-time between first client contract and first order completion, asset downtime and planning accuracy (%) of production lifecycle.

Translating these KPIs into value levers would quantify increased capacity utilization and operational cost reduction, which would impact the enterprise's financials through increased product margin and a reduction in both cost of sales, general and administrative expenses. It would also support the sustainability strategy that translates into a triple bottom line: reduced costs, increased margin, and decreased carbon footprint. By following this framework, companies can measure relative progress at each step of the journey and incrementally course-correct as needed.

Where sustainable supply chains are headed

At their core, many Industry 4.0 advances are being powered by the Internet of Things. Here physical systems contain connected sensors that share data. This dynamic, in which factory 'command centers' are tethered to the cloud, enable real-time monitoring as well as demand-driven configuration. Additionally, supply chains flexibly optimize themselves based on changes in demand or production capacity, and energy is delivered in an optimized manner.

These concepts, which would have seemed the stuff of science fiction just a decade ago, have become standard table stakes in a world where virtual shopping for customized objects has become the norm. Under this paradigm, it is no longer enough for enterprises to produce thousands of the same product. Shoppers now expect personalization, which in some ways is a reversion to manufacturing's roots -- akin to a blacksmith crafting a plow blade for a farmer whose equipment he knows intimately - but at massive scale and in near real-time.

To serve the demanding customer of tomorrow, enterprises must harness their data in ways that allow them to not only keep up with orders, but to optimize their use of resources and keep the costs of personalization in line with their margin expectations. Those that do, will not only help the environment through decreased energy usage, but will also please shareholders via expanding enterprise value - economically and sustainably.

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