Equipment as a Service(EaaS): Access the equipment you need, when you need it

One of the buzzwords related to cloud computing that has been bandied about lately is SaaS. Software as a service (SaaS) is a software distribution model in which a third-party provider hosts applications and makes them available to customers over the Internet. SaaS is one of three main categories of cloud computing, alongside infrastructure as a service (IaaS) and platform as a service (PaaS).

In manufacturing today, the Industrial Internet of Things(IIoT) holds great potential for quality control, sustainable and green practices, supply chain traceability and overall supply chain efficiency. IIoT is the use of Internet of Things (IoT) technologies in manufacturing. It incorporates machine learning and big data technology, harnessing the sensor data, machine-to-machine (M2M) communication and automation technologies that have existed in industrial settings for years. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately, consistently capturing and communicating data. This data can enable companies to pick up on inefficiencies and problems sooner, saving time and money and supporting business intelligence efforts.

As the industrial internet of things brings automation to an array of verticals, the as-a-service model is evolving to fill an emerging market for the hardware – sensors and other devices – that make up the so-called “things” in the industrial internet of things. In a recent report, this growing market is referred to as Equipment-as-a-Service(EaaS).


Equipment as a Service (EAAS)

Pay-per-use for machines and equipment (also known as equipment-as-a-service, or EaaS) has become a successful business model in various industries, including office equipment, medical equipment, jet engines, and others. EaaS front-runners in industrial manufacturing have already applied this model for new revenue streams to differentiate themselves in the marketplace and/or meet customer expectations.

Equipment-as-a-service or EaaS is rapidly moving from a specialized notion pioneered by the providers of medical and other specialized devices to general adoption. Thanks to the ease of connecting all sorts of equipment and devices in the internet of things (IoT), EaaS is also becoming more feasible and affordable. Today, EaaS is poised to make rapid inroads into complex building systems, such as high-rise elevators or HVAC, as well as manufacturing environments. While their customers benefit from lower whole-life equipment costs, no upfront capital investments, turning CAPEX into OPEX, industry-leading equipment uptime and a transparent pricing structure, the vendors of the machines and equipment can also benefit from an EaaS model. If done in the right way, it can be an attractive business model for a long-term sustainable revenue stream for manufacturing companies.

When companies look at equipment and machinery, they realize that they have static assets that need repair and servicing from time to time. What they now aim to see is services whose main value is to provide what people and companies want to accomplish, and equipment and maintenance are both a part of that. In many companies, the view of equipment and services is rapidly and dramatically changing.

The makers of high-end, business-critical equipment used, for instance, in manufacturing, oil and gas exploration, mining, and construction, have long sold equipment together with service contracts. For the customers using these machines, an interruption to their functioning would seriously compromise their ability to deliver to their customer commitments, so they pay for scheduled and emergency maintenance and repair in addition to investing in the purchase of the equipment.

EaaS takes a step beyond that with more effective operations and a simpler financial model. Companies’ primary interest is the ability, for example, to manufacture parts for jet engines. Instead of making a large investment in machinery, they pay the vendor a fee for delivering that ability at a certain service level. Equipment and equipment maintenance are essential components within that service. The vendor generates recurring revenue and may be able to build a larger business from services, parts, and materials.

In order to make this work, companies need to be able to rely on their vendor’s uncompromised uptime commitment. The vendor has to perform regular preventive maintenance, and also needs to be aware of materials and parts that are not performing to expectations and are at risk for failure, so they can be replaced or repaired. That, in turn, requires timely, accurate intel from and about the critical equipment assets. Connected sensors within the internet of things can gather and transmit detailed data that tell the service provider about the performance, material conditions, operational details, and location of the equipment, enabling proactive maintenance. If EaaS is implemented with the proper business intelligence, well-maintained equipment may be productive much longer and failures will be rare. EaaS providers will also be able to gather data from customer sites that help them improve their designs to make machinery more robust and better-performing. Equipment data will also make it easier to assess the costs and operational impact to decide how long machinery should be maintained and repaired, and when it’s better to replace it. Eventually, to the benefit of both EaaS vendors and their clients, maintenance and repair costs can go down.



Implementing an equipment-as-a-service (EaaS) model allows you to acquire the latest hardware and software while ensuring peak performance through ongoing support services. Companies that provide these services can help develop a comprehensive approach that enables manufacturing companies to address global coverage requirements, accelerate technology migrations and take advantage of new advancements.


Industrial Manufacturing Examples

More and more industrial manufacturing companies are analysing this business model for machines and equipment, as well as for software and digital services for their machines. Companies like Kaeser (compressors) and Atlas Copco (mining equipment) are prominent examples of successfully applying this business model for industrial machines and equipment. Of course, manufacturing companies are not planning to replace their traditional business model and will continue to sell their machines and equipment, but plan to offer “Equipment-as-a-Service” as an additional model for selected machines and selected customers.


Challenges in Sales and Service

Many industrial manufacturing companies who had a deeper look in EaaS as a new business model have realized that it is not easy to provide this new model to each of their customers in a profitable way: it has an impact on most lines of businesses of the company and requires changes along the entire value chain, mainly across marketing, sales, service, and R&D.

Industrial manufacturers need to manage the financial risk of every EaaS case:

  • conduct a solid due diligence for every customer case
  • calculate the customer-specific price points, based on a solid lifecycle costing analysis
  • work out smart contracts, considering the specific customer situations
  • define exit criteria
  • analyze each customer case before renewing the contract

To minimize the risks and to ensure a profitable EaaS contract, the vendor needs to monitor each customer case to get the required transparency on the profitability and to clearly understand what needs to be adjusted or changed when the contract will expire and needs a renewal.

All these points could be covered with spreadsheets and manual work. However, when scaling this business model to a larger number of customers, manufacturing companies should consider a proper software support through an EaaS management cockpit in their sales organizations.


Aftermarket management

Managing the financial risk is a key point for many manufacturing companies who embark on an EaaS journey, but there are other key topics to be managed: the optimization of the operating costs of the machines and fully automated process for the subscription billing. Manufacturing companies need the right aftermarket service organizations to provide the required service level agreements for an enhanced asset performance and an efficient service delivery for an attractive cost model to their customers. Predictive maintenance and service powered by IoT technologies is a key point for the optimization of the operating costs of the machines and equipment – an enabler for an EaaS business model in industrial manufacturing.

As always, marketing will analyze the market and competitors, identify potential customers, segment and classify them, and define the competitive solution portfolios for the EaaS offerings (considering machines and equipment as well as consumables etc.). And of course, R&D needs to ensure that the machines and equipment are enabled for an IoT-powered service and predictive maintenance and service, also leveraging latest technologies such as predictive analytics, machine learning, IoT technologies etc.


Final Thoughts

Imagine the scenario where companies can spec out their gear and pay a fixed dollar per month for use of the equipment. At the end of term, they can spec out the replacement, tweak the payment and keep on keeping on. This is the basis of Equipment as a Service (EaaS). The above concept does seem like what we call leasing today. But clients don’t really think of it quite that way. Most end users, manufacturers and dealers still see the process as one of formally obtaining financing where the EaaS feels far more like a “subscription” of sorts.

EaaS opens the door to a whole new way of thinking. More than finance, it would be a total cash flow approach to acquiring, paying for, managing and disposing of equipment. The life cycle management may be the major plus point but it also ensures a truly integrated customer experience. The agreement might even include maintenance, service, asset tracking or other value-added life cycle management things. Customers will get so used to the operational subscription-based approach, that haggling over implicit rate or spread will not even be a thing.

To fully benefit from the new technology, industrial organizations need to rapidly move away from the current practice of fixing equipment only after failure, or at pre-determined intervals. Remote diagnostics and maintenance solutions are a key factor in enabling original equipment manufacturers to offer equipment-as-a-service models. Early adopters are likely to benefit from the predictive maintenance that EaaS promises to offer.



New Bank Strategies Require New Operating Models

Disruptions in banking are pushing banks to take more explicit strategy decisions. Many banks have recognized that they need a truly differentiated strategy as the industry’s economics have come under pressure from new technology and entrants with disruptive business models. Large technology firms such as Internet giant Alibaba in China and messaging giant Kakao in South Korea have also been moving into markets such as payments, raising customers’ expectations for better digital tools and simple, convenient service. Ever-stricter capital and liquidity requirements by regulators have reduced banks’ own balance sheet leverage. Low interest rates and low economic growth intensify the pressure.

As a result, more banks are making difficult strategic choices. Some have exited countries where they had invested heavily for many years; Citibank and HSBC, for example, have decided to leave consumer banking in Brazil. Others are reinventing their core identity, with Citigroup CEO Michael Corbat characterizing Citi as “a technology company with a banking license.”

Difficult as strategic choices may be, banks are finding it even more challenging to adapt their operating models quickly to a new strategy—indeed, it’s often the biggest obstacle to implementing a distinctive strategy. Much effort and money today go into operating legacy processes and dealing with regulatory requirements to keep the bank running; Gartner estimates that banks on average spend roughly 60% of their IT budgets to maintain legacy IT systems vs. just 24% to grow the business and 16% to transform it. The global financial crisis, moreover, prompted a greater aversion to risk, and many banks’ legacy talent pools, processes and IT systems remain ill-suited to major change.

A core strategy choice that affects operating models

One key choice with implications for the operating model involves where to compete on the value chain spectrum. Banks can focus on “manufacturing” (creating products) at one end of the spectrum or on “distribution” (managing channels and customer relationships) at the other end. Most banks will choose a hybrid of the two, based on their relative strength in individual products, customer segments and internal capabilities (see Figure 1). Advances in technology make it easier to unbundle the value chain, and we believe the distinction between manufacturing and distribution will accelerate over time.

pic 2

Financial institutions pursuing a manufacturing-intensive strategy include Goldman Sachs, State Street and Black Rock. They aim to build world-class solutions for specific product needs and client segments, including other financial institutions. Succeeding through this model hinges on attaining large-scale product leadership and technological expertise. Some banks are relying on external vendors to perform parts of the process, such as FIS, IBM, SAP and Misys for core banking and product systems; Broadridge and First Data for servicing and business-process outsourcing; and IHS Markit, Bloomberg and Thompson Reuters for data and analytics.

The distribution model is attracting many regional and community banks, credit unions and parts of large banks that want to focus on areas where they have a competitive advantage. Distribution-focused banks tend to offer a full product suite, tailored to particular industries or customer profiles with a combination of non-bank, white-label solutions and partnerships with other banks. That means they outsource many products and processes such as credit cards, asset management or insurance, as well as utility-type activities such as mortgage processing. Success with the distribution model hinges on customer analytics, strong customer relationships, channels that are simple and easy to use, and economies of scope achieved by gaining a large share of the customer’s wallet.

Most large banks will choose to compete along the broad middle of the spectrum. They look for growth in select markets where they have a distinct set of products and customer segments, and they combine elements of scale and scope by, say, manufacturing in their local market and distributing overseas. Lloyds Bank, for example, manufactures trade-finance products in the UK, while it partners with Standard Chartered in Asia.

Redesigning the operating model for the new age

Just as banks have been relearning the art of strategy to build competitive advantage, they also must develop operating models uniquely suited to their strategy, rather than models based on generic industry benchmarks. Banks will have to rethink the role, structure and processes of critical functions such as IT, risk and compliance. For instance, more banks are moving to open architecture, which means they no longer have complete end-to-end control internally of their IT systems or data. This trend has been spurred by the migration to cloud solutions, and will further accelerate with the spread of distributed ledger technology, smart contracts and open application programming interface (API) systems that integrate activities across the financial system. Banks will have to redesign processes to understand and monitor activities handled by external providers, not by the bank itself.

Manufacturers must deepen their product innovation and ability to scale up. At times, they will rely on other financial institutions to market their products, via partnerships or white labeling. Banks taking the distribution route have the reverse challenge of unbundling activities, then finding and managing other parties to provide them.

To be clear, what we mean by operating model is the blueprint for how resources are organized and operated to get work done. It takes shape through choices in five areas (see Figure 2):

  • structure—the matrix of products, geographies and segments that will work best for manufacturing or distribution;
  • accountabilities—aligning roles and responsibilities to excel in key capabilities;
  • governance—speeding up the critical decisions in capital allocation, IT, capex, product design and vendor choice;
  • ways of working—calibrating a culture that fosters collaboration across functions and with vendors, which has not been a strength of traditional banks; and
  • capabilities—combining people, processes and technology to reinforce the elements of the strategy that will enable a bank to stand apart from the pack. Most institutions can truly master only three or four capabilities. Manufacturing tends to lean heavily on back-end capabilities like cost discipline, product design and straight-through processing. By contrast, distribution relies more on customer advocacy, strong relationship managers and marketing.

So how can bank executives design and build an adaptive operating model that will sustain growth and profitability? Leading banks are making inroads in five areas that allow them to build models that suit their strategies-in-the-making and can flex as new priorities emerge (see Figure 3).



Get Agile fast

Most banks have started to use Agile methods in their software development. Few, though, have taken it to scale beyond a few individual projects. New competitors move faster than banks in making and implementing decisions, and as technology such as open APIs makes it easier for customers to switch providers, banks risk increasing customer churn. A practical way to speed up the metabolism of the organization is adopting Agile to improve the overall customer experience.

Banks that have taken a year to develop products through traditional Waterfall methods now can do so in a matter of weeks through Agile. While Agile does not work well for every activity (such as closing the books each quarter), it can accelerate time to market for new products and services, and adapt quickly to changes in the market environment (see Figure 4).


Among banks that have started to take Agile to a larger scale, a few have focused their Agile teams on redesigning and managing entire customer episodes, rather than just products. Episodes consist of a task that a customer must complete or a need he or she wants to fulfill, with a clear start and end. They range from a single interaction (paying another person online) to an intricate series of interactions (buying a home, which includes securing a mortgage). Focusing on episodes forces the team to take the customer’s perspective and to involve any function that influences the quality of the experience.

A leading financial services company turned to Agile to support its goal of organizing around customer experiences rather than products. In doing so, it sharpened the focus on raising speed to market and ensuring consistently high customer loyalty scores for sales and service delivery, especially in predominantly digital channels. The company uses Agile, cross-functional teams of 8 to 10 people, aligned to specific customer episodes. Each team brings together the requisite capabilities in business, design, processes and technology. The company now is taking its experience-led Agile approach to scale across the enterprise, through waves of applied learning sessions, and is well on its way to improving productivity by three to four times. To fill gaps in capabilities, the company retooled existing resources through training and added employees with design and data skills.


Modernize your legacy IT.

Strategy doesn’t stand still, and neither should the technology that supports it. Moving away from legacy IT is such a complex task that many banks have delayed it. In effect, they are kicking the can down the road. The proliferation of fintechs and the encroachment of large tech firms into banking make it abundantly clear that digital technologies have provided compelling and distinctive customer experiences, often at a lower cost than the previous generation of experiences. Banks that accelerate their replacement of legacy IT stand to gain a competitive edge that will be hard to erode.

A few general principles will keep IT relevant: Cap legacy IT spending and reduce it wherever possible to free up funding for new IT, such as the cloud. Enable all channels with digital technology. Move to straight-through, paperless processes. Build a single, smart view of the customer. And use modular systems architecture that can flex.

Strong, flexible IT also requires traditional banks to make organizational changes. Banks should determine where to maintain standardized, centralized IT solutions—say, in payments infrastructure—and where execution should be handled by the business units, as in the development of mobile applications.

The C-suite will need to step up its knowledge and commitment as well. Senior executives may not understand all the implications of disruptive technology or appreciate how the entire company, not just the IT group, must work differently. But they cannot allow risk aversion to paralyze the organization. While accepting the role of legacy IT systems for the foreseeable future, senior executives should methodically pursue modernization and retirement of outdated systems based on risk/value trade-offs.


Find and redeploy new types of talent.

As automation pervades more activities and, at the same time, banks sharpen their focus on delivering a better customer experience, their workforce must evolve. Thousands of roles are becoming obsolete, including tellers, back-office processors—even routine call-center agents, as chatbots take on simple inquiries.

We have seen conventional technologies help banks to double labor productivity every few years, through digitalizing processes and applying more sophisticated industrial methods like capacity planning and Lean Six Sigma. Opimas, a research firm, estimates that by 2025, the rollout of artificial intelligence (AI) technology by financial institutions will reduce employment in the capital markets by 230,000 people, with the largest impact in the asset management industry, where machines will replace around 90,000 people.

Taiger, for instance, combines machine learning with natural-language processing to automatically identify, extract, cleanse and validate pieces of information from many types of documents. The banking applications include client onboarding, due diligence and fighting money laundering. After a large European bank shifted to Taiger’s technology for client onboarding, its cost fell 85% and turnaround time shrank from several weeks to seven minutes, with no loss in quality. As AI spreads throughout the industry, bank professionals who previously performed those activities may need to retool their expertise.

The greatest talent challenge for banks may be attracting technical specialists. Banks have run into a dearth of talent in advanced analytics, new technologies such as blockchain and customer experience design. The shortage is compounded by competition from culturally more attractive fin-techs and companies in other industries. Banks will have to get creative in attracting and nurturing top talent, through such tactics as mobility programs for top performers in key roles, and by adapting their cultures.


Questions for executives

As bank executives consider how to redesign their operating model to suit an evolving strategy, they can start by asking a few pointed questions (see Figure 5):

1. How should we adapt our organizational structure? Should we design fit-for-purpose operating models for different business areas?

2. Do we know what capability gaps exist and how to close them?

3. Does our IT respond to clearly defined business unit requirements?

4. What workforce changes need to occur and how will we attract the talent we need?

5. How do we finance the change? Is our corporate center set up to actively prioritize resources?


Perhaps the most important question: How much time do we have? Adjusting operating models can involve getting agreement with regulators, workers councils and other stakeholders, which can easily drag out the process even when banks feel some urgency. At the same time, banks are facing competitors that started from scratch and have the passion of insurgents. The disruption caused by technology and evolving customer expectations will not let up. Banks that take too much time to realign or overhaul their operating models risk being left high and dry.



Driving Supply Chain Revolution through Blockchain Technology

Looking at the applications of Blockchain in the industry beyond the rise of cryptocurrency and its role in revolutionising Supply chain management.

What is Blockchain?

Blockchain is a distributed database that holds records of digital data or events in a way that makes them tamper-resistant. While many users may access, inspect, or add to the data, they can’t change or delete it. The original information stays put, leaving a permanent and public information trail, or chain, of transactions.

If the entire blockchain were the history of banking transactions, an individual bank statement would be a single “block” in the chain. Unlike most banking systems, however, there is no single organization that controls these transactions. It can only be updated through consensus of a majority of participants in the system.

In short, blockchain is a record-keeping mechanism that makes it easier and safer for businesses to work together over the internet.

Blockchain principles

This technology relies on three principles:

Transparency: everyone can visualize the transactions recorded on a blockchain from the time it was created.

Decentralization: blockchains operate on a network and are therefore not centrally controlled by a single entity.

Security: transactions carried out on blockchains are encrypted, making it impossible to forge data.


Beyond Bitcoin

The most popular application of Blockchain is Bitcoin and other cryptocurrencies. Block chain has enabled a systematic peer to peer exchange of currencies that has enabled users to transact without the need for any 3rd party.

But blockchain’s applications is more than just recording of financial details. It includes the recording of all kinds of data. Thought it was initially intended for financial transactions, businesses of all kinds are getting creative with the blockchain ledger, as it can be used to record, track, and verify trades of virtually anything that holds value.

From ride-sharing to cloud storage to voting, companies in all industries are beginning to see blockchain’s potential. Every time a product changes hands, the transaction could be documented, creating a permanent history of a product, from manufacture to sale. This could dramatically reduce time delays, added costs, and human error that plague transactions today.


Advantage of Blockchain in SCM

Some supply chains are already using the technology, and experts suggest blockchain could become a universal “supply chain operating system” before long. Consider how this technology could improve the following tasks:

  • Recording the quantity and transfer of assets – like pallets, trailers, containers, etc. – as they move between supply chain nodes
  • Tracking purchase orders, change orders, receipts, shipment notifications, or other trade-related documents
  • Assigning or verifying certifications or certain properties of physical products; for example determining if a food product is organic or fair trade.
  • Linking physical goods to serial numbers, bar codes, digital tags like RFID, etc. Sharing information about manufacturing process, assembly, delivery, and maintenance of products with suppliers and vendor

This will result in Automated Buying process, Better transaction flow, secure supply chain, integral tractability, more reliable and streamlined document storage. It can be implemented across the chain as depicted in the diagram given below.


Industry Application

Blockchain is being adopted by the industry at a rapid pace:

Automated meter reading and SMART metering: Feeding energy consumption data digitally into a blockchain, to verify a customer’s usage with 100% certainty, generate accurate bills, and collect payments on the blockchain without incurring fees associated with bank transfers. South African Bitcoin startup Bankymoon built the world’s first blockchain smart metering solution for modern power and utility grids.

Energy delivery: Car charging with the charging station acting as a point for both customer authentication and payment processing, leveraging blockchain-based smart contracts to authenticate users and manage the billing process to cut costs and improve customer experience.

Smart energy use and lower power bills: Enabling household customers to constantly search for cheaper energy prices and instantly change providers for a better deal, all of which is automatically handled by the blockchain-based application.

Green energy and energy credit: Blockchain can be leveraged as a public ledger with recording of solar energy production and feeding production data directly into a blockchain and owners automatically being rewarded for the energy produced in SolarCoin.

SMART grid: Consumers can use blockchain-based applications to join a smart grid in which participants can track their energy use and production (such as via solar panels) and sell excess energy to others on the smart grid, leading to more competitive energy pricing for consumers.

Blockchain in the Internet of Things: Blockchain combined with IoT can be leveraged to create mesh networks (a flexible and secure network that connects computers and other devices directly to one another) to solve complex utilities infrastructure problems. Filament, an American company, is experimenting with “taps” on power poles, with motion detectors on each pole that can detect any trouble on another pole up to a distance of 10 miles and communicate to the company through the closest internet backhaul location within 120 miles.


In a nutshell, applications based on blockchain are being explored globally and a new ecosystem of blockchain community comprising energy startups such as LO3 Energy, Grid Singularity,, Power Ledger, Wattcoin Labs BlockCypher, Ripple, etc.), utilities (Vattenfall, RWE, Fortum, etc.), technology providers (Ethereum, Tendermint, Tierion, Monax, MaidSafe, Ascribe, Digital Asset, and Blockstream, etc.) and consulting companies is emerging. Many pilot partnerships are being established by major utility players (such as RWE and Vattenfall) and investing in utility startups.

The blockchain is a fast-moving disruptive innovation technology across industries, including utilities. While it is difficult to predict how quickly this technology will be adopted in the sector on a large scale, current areas of interest unveil a clear picture of innovation initiatives around blockchain in the near future.



Blockchain has great advantages in terms of cybersecurity, but there are several challenges associated with maturing this technology for supply chain purposes:

  1. The technological talent is scarce and expensive; much of it has been scooped up by fintech startup firms.
  2. There are network effects associated with deriving value from blockchain in logistics. The more entities that participate, the more valuable the solution is. But this network effect makes things difficult at the start.
  3. It is likely that to get to scale, large companies will need to require their supply chain partners to participate. But this could hinder the drive to create the necessary standards. Further, while several organizations are seeking to play the necessary role of standards body; none has yet achieved the necessary scale.
  4. “Miners” are used to validate that the data added to a blockchain is valid. With Bitcoin, this process can take several minutes. There are supply chain processes where less latency would be very desirable.

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Digital Transformation: It’s All About the Outcomes

Digital Transformation: It’s All About the Outcomes

Digital transformation isn’t about finding the needle in the haystack of big data – it’s about the relentless focus on deriving new business value from digitizing and optimizing your operations. And leading companies are already proving just how impactful such data-driven business improvements can be.

Digital transformation is helping automaker Ford, for example, manage more than 2 million product variations in real time across its plants. It also gave mining company BHP Billiton a twentyfold increase in access to production data to help increase uptime. And it’s helped PepsiCo achieve a 90% reduction in troubleshooting time.

These companies are giants in their industries, but what they’re doing – connecting their operations, gaining access to relevant data and digitizing processes – can be done by anyone, using modern technologies that are already available.


Opportunities in Your Supply Chain

Most companies are interested in digital transformation for its ability to optimize their supply chains.

In consumer-focused industries, this could mean improving your ability to predictcustomer demand and make the corresponding adjustments in areas like procurement and production scheduling to satisfy that demand. In heavy industries, it could mean meeting demand requirements by delivering the highest possible quality at the lowest possible cost.

Digital transformation makes these optimization opportunities possible by unlocking value that has long been hidden in silos in most enterprises. It enables a digital thread, for example, through which you can seamlessly collect, analyze and share your data. It also allows you to create “digital twins” of your physical assets or processes, so you can test systems before they’re built, evaluate production changes before they’re made, and validate performance at runtime.

These and other capabilities can be applied throughout the production lifecycle, including design and commissioning, operations, maintenance, and R&D innovation efforts. However, most companies need some help when it comes to identifying and rolling out the technologies that are right for them.

Charting Your Course

Embarking on a journey to digital transformation doesn’t need to be a long, arduous venture into the unknown. Those that have already made the journey provide a rough roadmap for you to follow.

In short: begin by identifying the business problems you want to solve. From there, consider getting an outside perspective on what technologies can help you address those problems. Once the solutions are selected, run pilot programs to prove the realization of business value, and then scale and deploy those programs across your operations.

Those that have embarked on a digital-transformation journey also can prove out the technologies that are key to the process. Four successful examples of these technologies in use include:

Software applications for digitization and IT/OT convergence help companies achieve workflow adherence, collaboration and tracking in their plants. Software can scale from focused applications, such as for quality or performance, to industry-specific suites of applications, or comprehensive manufacturing execution systems (MES) for multi-plant rollouts.

Chinese pharmaceutical maker Zhejiang Medicine Co. (ZMC) deployed a pharmaceutical industry-specific software platform to help its new facility go paperless. This software platform integrates production processes from the plant floor to the enterprise, while also digitizing paper records and automating document management. ZMC estimates this will help the company save 5% to 10% in labor costs by eliminating manual recording, while also reducing batch-product-review cycle times by as much as 75%.

Our own digital-transformation journey at Rockwell Automation included deploying a single, multiplant MES to replace the different MES solutions that were in place across our facilities. The flexible MES includes applications that can be used in all our facilities and a common manufacturing platform that can be expanded to different regions and product groups. Its real-time KPI monitoring has helped us increase efficiency and improve quality, including a 50% reduction in parts-per-million defects.

Scalable analytics software helps companies quickly and easily derive value from their data through analytics at every level of their organization. When combined with scalable computing, from edge devices to cloud computing, analytics software can process and present actionable information at all levels of the enterprise including closest to the data source.

Dairy protein producer Milk Specialties used analytics to optimize its operations and meet rapidly growing demand. The company deployed a manufacturing intelligence system that collects and correlates process, business and lab data to create actionable analytics. Now, in-plant scoreboards help workers meet production targets. And at a higher level, the analytics help justify key operational changes, including process improvements that have led to a 7% throughput increase.

As part of our journey, we’ve deployed scalable computing and analytics at the controller level and in the cloud. We use computing in the controller to run real-time analytics that drive real-time actions on the plant floor. In our printed-circuit-board production, for example, we use real-time predictive analytics that can tell operators to slow down production or take other actions to prevent failures. Meanwhile, in the cloud, we collect and analyze data from about 20 plants and use it to bring lagging machines up to the performance level of top-performing machines.

Collaboration and design tools support seamless collection and sharing of knowledge to empower teams with better decision-making. The tools can be used for sharing and discussing information about incidents, devices, alarms, trends and almost anything else that might be useful for improving performance.

Just consider the full lifecycle benefits of a digital twin. When a machine is being designed, for instance, its digital twin can be run in simulation mode. This can help reduce the time and costs associated with commissioning. Using digital twins in operations and maintenance can decrease downtime by allowing users to simulate changes to a process or updates to equipment before deploying in the physical machine. And digital twin technology is being combined with virtual, augmented or mixed reality to enhance visualization of operations and maintenance, and to support operator training.

In our own operations, new mobile apps that seamlessly connect workers are helping improve collaboration on our plant floors. If there’s an alarm on a machine, an operator can use the app to connect to the specialist who knows how to respond to it – even if that specialist is in another time zone. Regardless of where they are, the specialists can see the same alarm display and data as the operator, troubleshoot the issue, and guide the operator to a resolution.

Connected services help companies maximize their use of connectivity and production data, especially as part of continuous-improvement initiatives. Services include training and supplemental support of in-house teams, such as through remote monitoring. These services can help companies through their digital-transformation journey by helping design and implement networks, secure smart-manufacturing assets, and provide ongoing optimization support.

When an oil and gas company upgraded the pumping equipment at its offshore oil-drilling platforms and operations, it used a vendor service to remotely monitor the new pumps. The service collects real-time data from the equipment and can alert support engineers of potential issues to help reduce downtime and increase pump efficiency.

In one instance, the vendor was on the phone to discuss the problem with production staff within five minutes after a well tripped offline. The vendor helped staff verify the issue, replace the part and get back online immediately. This saved the company at least six hours of troubleshooting – significant savings considering that downtime can cost the company $100,000 to $300,000 per day.

An Unstoppable Force

Digital transformation is already happening, and it’s inevitable in any organization that wants to prosper in our connected world. But companies shouldn’t undergo digital transformation simply for the sake of doing it. Rather, they should align every aspect of it with specific business outcomes and carry it out as efficiently and cost-effectively as possible using lessons learned from those that have already made the journey.


DHL shifts to Asset Heavy Strategy

Global logistics group DHL is planning to introduce internet-connected trucks and emulate technology-enabled logistics start-up Rivigo Services Pvt Ltd’s driver relay model to improve customer experience and increase efficiency, according to an industry executive with direct knowledge of the matter.

Rivigo currently owns a fleet of over 2,000 internet-connected trucks and operates through a unique driver relay model. Rivigo utilises technology enabled trucks that are fitted with sensors for location tracking. This has enabled Rivigo to reduce their transit time by 50-70% and hence enhance their services.

The company employs multiple drivers on one route and each one typically drives for four to five hours before handing over the truck to another driver at a pit stop, returning home with another truck.Rivigocurrently has at least 70 such pit stops across India.

DHL has been planning to invest over $100 million in supply chain operations in India over the next 3-4 years and is planning to emulate the same model. DHL will need to find ways to leverage their strong customer access and established network footprint to create a differentiated value proposition. Also, asset ownership will be a key decision point for players in the sector.

DHL has traditionally had an asset-light model. On the other hand Rivigo has demonstrated the merits of asset ownership in improving operational efficiency. But owning truck fleets comes at a cost. Rivigo’s annual loss widened to Rs 137.1 crore in the year ended 31 March, from a little over Rs 5 crore in the previous year mainly due to high bus purchase costs.

Given that the logistics space in India is currently very inefficient and conglomerates with good consumer connect and good value proposition for consumers can disrupt it in a big way.

The average distance covered per day by trucks in India is 250-300km, less than half that in the US, where trucks cover approx. 700-800km per day on an average. Therefore, there is a major scope for firms in this sector to leverage technology and provide greater efficiency and performance.


How eCommerce is Changing the Manufacturing and Supply Industry

eCommerce changed the face of retail forever. It’s been a major influencer in shaping how buyers think and what they expect.  It’s no surprise this revolution has spilled over into the arena of B2B commerce. As early as 2013, Forrester noted that B2B eCommerce will dwarf B2C retail eCommerce, $559 billion to $252 billion. Since then the gap has only grown.

Just as in retail, early eCommerce adopters in the manufacturing and supply sectors will gain market share and dominate the landscape for years to come. Digitizing isn’t without challenges, but the benefits are substantial if you know how to choose the right solution.

The B2B buyer has changed
B2B buyers are now eCommerce savvy B2C consumers; and they bring their digital retail expectations to work with them each day. These buyers are changing the B2B purchase journey one transaction at a time. B2B buyers are still proactive, but instead of pouring through catalogues, thumbing through Thomas Register, and making phone calls, they turn to search engines and manufacturer web sites. The self-serve model they love for B2C is driving their behaviour on the job. Manufacturers and suppliers that reward these buyers with an online experience that includes eCommerce will earn their loyalty.

eCommerce Advantage for Manufacturers and Suppliers

Increased sales are a major benefit, but that’s just the start. The right eCommerce platform will support digital marketing efforts, integrate with other business solutions, and free sales and customer service to focus on what they do best: build relationships and serve customers.

Access New Markets. eCommerce fits hand in glove with digital marketing. Scaling into new territories and new markets is much easier and more cost-effective when you go digital. Face it, strategic use of digital boots on the ground just costs less and results are easier to track. Increased reach and greater brand awareness yields more sales possibilities. Those digital boots need not step on the toes of your existing distributors either. Provide your existing distribution chain exclusive offerings and your distributors won’t perceive your eCommerce presence as competition. These offerings can be as simple as unique colors, finishes, or sizes or as complex as exclusive products. Then, additionally tailor your products for new markets and you will increase your reach without competing with your existing network.

More Efficient Operations. With all of those new sales to handle, you’ll be glad that your eCommerce site can improve back-end efficiencies. An effective eCommerce solution should easily integrate with your ERP, CRM, PIM and any other alphabet soup of systems you use. Seriously, solutions that don’t integrate aren’t solutions at all. So, it’s important to plan for integration during the platform selection process to maximize the potential of digitizing.

Customer Centric Focus. Your forward-facing operations benefit from eCommerce as well. When customers are free to order online and check the status of an existing order whenever and wherever they want, you don’t waste time taking orders and answering order status questions over the phone. The customer service and sales functions can focus on nurturing leads, building relationships and providing true customer service, sales, and warranty support. Digitize the freight quoting process and let shipping focus on getting orders out the door and off the loading dock. As a bonus, when you eliminate the need to rekey data into an order system, fulfilment and shipping errors are decreased dramatically.

Online shopping e-commerce concept mobile shopping man holding smart phone credit cards vector set

Leverage the Power of Online and Mobile for an Omnichannel Experience

By 2015, nearly two-thirds of Americans owned a smartphone.  B2B buyers rely heavily on mobile search. According to ComScore, 72% of those phones have a Facebook app on them, almost 60% have Google Search, and 45% have Instagram. Why is this relevant? 84% of C-level and VP level buyers are influenced by social media. 75% of tech buyers rely on search and 40%‘s buying decisions have been influenced by mobile ads. Where tech buyers lead, other buyers soon follow. Clearly B2B buyers want an omnichannel experience that includes mobile and online options. Major manufacturers are figuring this out. You should too. For example, Sweden’s Volvo AB is testing direct internet sales of its autos in Belgium and in the U.S., Ford Motor Company is working with dealers to create multiline showrooms to achieve economies of scale and revolutionize their brick and mortar operations. All of this after they began selling cars online in Britain.

It’s not enough to have a website, it must be mobile friendly as well. Buyers want to look on-line and call if they have questions. Click to dial is a must-have feature if you want to provide a seamless omnichannel experience. Global players such as Jimi Electronic Company, a China-based manufacturer of GPS and wireless communication equipment, pair their own eCommerce site with global marketplaces such as EC21 to meet the buyers desire for self-serve wherever they are. On desktop or mobile, on an eCommerce platform or at a marketplace, you must be prepared for today’s buyer.

Myth busting B2B eCommerce

It’s clear that B2B eCommerce provides the experience buyers want. So why are manufacturers and suppliers slow to implement?  There are many myths that provide stumbling blocks. We’re here to tear them down.

Complex Ordering Process. Too many manufacturers believe that because no two orders are alike, orders can’t be processed on-line. The myth: price lists and catalogs personalized by customer and the RFQ process just can’t be handled on-line. It’s just not true; but this myth did come from somewhere. In the beginning, B2B sellers tried to use B2C eCommerce software to do the job. It was ill-prepared to handle the complexities of B2B eCommerce and required extensive and expensive customization. Today, B2B eCommerce platforms are built from the ground up for B2B transactions. Products like OroCommerce provide customizable workflow engines for multiple, complex scenarios.

Multiple Decision Makers. Many B2B sales are the result of a process that includes multiple decision makers. The myth: eCommerce can’t handle this level of complex approval. Debunked! B2C isn’t up to the job, but a solution with robust account management allows the buyer to configure their own corporate account structure. Customer users define roles and authorities and create purchasing rules for their own account depending on roles.

Ordering and Re-ordering is Slow. When it comes to repeat purchases, most buyers know what they want. It’s just easier for a buyer to upload a file with SKUs and quantities to place an order. The myth: on-line repeat and bulk ordering is tedious as you must search to populate the order form. If your eCommerce platform can’t handle bulk orders and re-orders easily and efficiently, you’ve got the wrong platform. As a matter of fact, Forrester reports that 44% of companiesthat receive orders through an on-line portal experience higher average order values.

Payment Terms. Most B2B purchases aren’t made with a credit card or PayPal. Buyers need to check out a shopping cart with terms. The myth: eCommerce doesn’t provide for PO processing, net payment terms, or credit applications.  Once again, this might be true for B2C platforms, but a B2B platform should have a flexible workflow engine and integrate to handle a variety of check-out scenarios. Also, look for platforms with technology partners to help extend terms or process payments.

Choosing the Right Solution
As manufacturers and suppliers began to develop eCommerce sites, B2C platforms tried to adapt their systems to meet the need for B2B. Unfortunately, they missed the mark and were unable to build the scalable and customizable solutions that the B2B marketplace needs, mainly because B2C platforms don’t provide a customizable workflow engine.

When evaluating B2B solutions, look for true B2B capabilities, time to market, total cost of ownership, flexibility and scalability, support and a healthy partner ecosystem. It’s not a decision to be made lightly. Luckily Frost & Sullivan researched B2B eCommerce platforms recently and their findings can help you make an informed decision.

Oro provides open-sourced business solutions for B2B eCommerce and CRMthrough its products OroCommerce and OroCRM. With over 150,000 active installations, it has a strategic global footprint with features and tools made for B2B companies going online.


Game Theory: Application to Supply Chain Management

For people who’ve watched the 2001 Russell Crowe starrer hit “A Beautiful Mind”, the name John Nash and the terms “Game Theory” and “Nash Equilibrium” would probably ring a bell. The most popular scene from the movie is probably where a group of guys are looking at a group of girls. All the guys prefer one of the girls; the blonde. Nash then describes how, if they all go for the blonde, they will block each other and none of them will get her. Going for her friends afterwards will not be the better choice because her friends will now be mad because they were the second choice. Nash proposes that they all start out by going for the friends such that they each get a girl and no one gets the blonde. Here’s the scene:

However I must warn you that in fact the scene depicts a Nash Equilibrium INCORRECTLY!!!!


A Nash Equilibrium is one where there can be no unilateral deviation i.e. each player is happy with his payoff (gain). In this case, however, there is an incentive for each of Nash’s friends to deviate i.e. leave the girl that they’ve chosen and go for the blonde.

nashBut enough of that. The objective of this article is not to undermine a multi Oscar winning movie but rather to see if Game theory, and in particular Cooperative Game theory model, can help us in assessing and improving a Supply Chain.

Basics of Game Theory

Game theory is the study of human conflict and cooperation within a competitive situation. It involves 2 or more participants (players) who are assumed to be rational and derive a certain gain/loss (payoff) in the different outcomes that results due to the occurrence of the game. Check out the links below for a better understanding.





(You would have appreciated the joke more if you had actually gone through the links)

Application of Game theory to Supply Chain

We can make a distinction between decentralized and centralized supply chains. In case of the latter a single decision maker determines the optimal solution that improves the supply chain’s global performance.

In a decentralized supply chain, each supply chain member is an independent decision maker, and thus this situation can be modeled using Game theory where each member can be treated as a player.

An illustration of the application can be in transportation and logistics.

 'I hear your distribution network is second to none.'

Unless a company has Santa as its logistics partner, the chances are that the logistics costs are pretty high (which is bad since transportation forms part of the 7 deadly wastes which add no value to the customer).

A research paper by Lotte Van Meirvenne calculates the total benefit that can be gained out by sharing of logistics providers by companies and so can logistics companies by coordinating among themselves better. But you already knew that companies can gain immensely by better coordination in the area of logistics (Duh!!).

However cooperative Game theory comes to the rescue to determine exactly how the total benefits can be divided among the players. This is done using something called a Shapley value.

One can look at the savings in transportation and logistics as the spoils of a loot which is to be divided among the scurvy eyed pirates. The question of how to distribute gains in a multiplayer scenario is not a straightforward task and is one where Shapley value can be immensely helpful.


There are many instances where coordination between players of a supply chain can help in increased efficiency. These players can be in the same supply chain or competing supply chains. The benefits of cooperation are :  elimination of excess inventory, reduction of lead times, increased sales, improved customer service, efficient product development efforts, low manufacturing costs, increased flexibility to cope with high demand uncertainty, increased customer retention and revenue enhancements.

The supply chain members can either compete to improve their individual performance or they could work together and make an agreement to coordinate their strategies in order to improve the global performance of the supply chain next to their own individual profits. In the cooperative situation, it is important that the benefits and costs are divided between the supply chain members in such a way that each member is satisfied; otherwise no supply chain member would be prepared to form a coalition.

The application of theoretical concepts for improving business efficiency is as important as the study of business processes to build up theoretical concepts. The article was aimed to bring out the continuum that exists between business and academia by showing its readers how a very relevant pain point in business can be solved by looking at seemingly unrelated theoretical models.

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The Jethalal conundrum: Warehousing and Agent based simulation

cropped-warehouse2_cropped1Warehousing is a quintessential activity wherever production of physical products is involved, be it your mother’s kitchen where the good old refrigerator acts as a warehouse or a steel production facility spread over hundreds of acres of land belching out tons of steel products. The following article introduces the basic activities that are carried out in a warehouse and how simulation can be used to optimize those activities.

The warehouse operation consists of 5 key activities:

  • Goods receipt
  • Put away
  • Storage
  • Order Picking
  • Goods dispatch

Flow Proses Warehouse Activity

Goods receipt: is a document issued to acknowledge the receipt of the items listed in it. In other words, it is a document used to register the specifics of items physically received in the warehouse

Put away and storage: Put away is the process of moving received inventory from the dock/wharf or production area to a storage bin

Order Picking: The activity by which a small number of goods are extracted from a warehouse system, to satisfy a number of independent customer orders. It is the most labour intensive and costly activity and forms as much as 55% of the total warehouse expense.

Goods dispatch: This is the customer facing side of a warehouse where the picked goods are dispatched to the customer usually via 3rd party logistics partners

Now imagine M/s Jethalal and Sons hire you as an operations consultant for his biscuit factory. Mr Jethalal has recently ramped up the production capacity of his Gurgaon factory and wants to build a warehouse in Pune to serve his distributors Just-in-Time. He wants you to come up with a plan for warehouse operations which will enable his company to serve customers at the minimum cost and maximum efficiency. You toil hard, crunch the numbers and come up with 3 possible layouts. However there is no way to test these layouts and come up with the one which is the best fit for the company and the associated product. You now wish you could build miniature Lego models and assess your layouts.


Introducing…. Agent based simulation

Agent based simulation

It is a decentralized and individual centric approach to model design. When designing an agent based model the modeller identifies the active entities, the agents (which can be people, companies, projects, assets, vehicles, cities, animals, ships etc.) defines their behaviour (main drivers, reactions etc.), puts them in a certain environment, establishes connections, and runs the simulation. The global behaviour then emerges as a result of interactions of many individual behaviours.


Agent based simulation can be used in a wide variety of situations like traffic management, supply chain planning, network planning, production facility planning and of course: warehousing facility planning.

Coming back to our problem, by using simulation, one can easily visualize the proposed warehouse facility without actually building it. A simulation enables the designer to calculate put away and picking time thus helping him identify the bottlenecks that exist in the entire process.

You build a warehouse model for Mr Jethalal and identify the most time consuming processes of the warehouse. You recommend an FSN classification of product SKUs and propose a layout with unidirectional flow of material and multiple loading and unloading points. Mr Jethalal is happy and promises you free biscuits for life (well, this had to have a happy ending, right?).

The choice of software is critical for simulation activities. A few recommendations are- Anylogic (3D supported, student licence is free), Netlogo (2D but completely open source), FlexSim (Trial license free, 3D supported)

Check out a video of the FlexSim and CLASS warehouse simulations:

Find older JIT articles here

Quality – Case in point : Mumbai Dabbawala

91a230667e75f99526f918819b08fdedOn the walls of the main lobby of Toyota’s headquarters in Tokyo hang 3 portraits. One portrait is of the company’s founder, another is of the current chairman and the largest portrait is of Dr. Deming, the US based statistician whose work was seminal in Japan’s quality revolution.
Quality essentially is an exercise in consistency. Quality control is where we have a production process, and we want to ensure that high quality is maintained throughout the operation. We sample from the production process, and we take corrective action whenever we believe that the process is out of control- producing items that, on average, lie outside our specified target limits.

Variation and Causes:
The cause of variation in output properties can be subdivided into two groups : Assignable and Unassignable causes
Assignable Causes of variation are those identifiable reasons that can be determined. For example : improper raw material, operator mistake, jigs and fixtures errors, improper tools etc. These variations result the observation fall beyond the permissible limit.
Unassignable causes of variation are the result of randomness in the nature, sometimes called as natural variation in the process. These types of causes may include variations in the machine, fluctuations in working condition, change of state of mind of operator etc. The minimization of this type of variation requires high cost. Generally these are very small in magnitude and sometimes called as allowed variation of the process. The observations with these variations fall within permissible limit and the process is supposed to be in stable condition.

Some tools for quality control are :

Control Charts

Control chart is an effective tool to maintain quality. It is a graphical display of measurements of an industrial process through time, with which a quality control engineer can identify any potential problems with the production process. The idea is that when a process is in control, the variable being measured (eg the mean of every 4 observations) should remain within the stipulated “tolerance limit”.



Below is an example of a control chart


Pareto Diagram

Pareto diagram is a bar chart of the various problems in production and their percentages which is used to identify the problem(s) which should be addressed first.

Taguchi Methods

taguchi-methodsThe basic ideology of Taguchi was that the quality of a large system deteriorates as we add the small variations in quality for all its separate components. For example, if we look at a car, the car’s quality may not be good even though all its components are within desired levels when considered alone. To solve this problem Taguchi developed the idea of a total loss to society due to the lowered quality of any given item. That loss to society is to be minimized. This is done by introducing a loss function associated with the parameter in question and by trying to create production systems that minimize this loss both for components and for finished products.

Mumbai Dabbawalas
146The Mumbai Dabbawalas is a 120 year old organization which solves a very critical problem for working Mumbai residents.
Mumbaikers don’t want to carry their tiffin boxes along with them on the local
1. The working Mumbaiker starts early in the morning. If he leaves home at say 7 o’ clock in the morning, he doesn’t want his wife/mother to wake up at 6 just to cook his food!
2. It’s just too crowded on the local!

Boarding a local with empty hands is difficult, with a tiffin in your hands, it becomes a mammoth task just to get on the train.
Hence come the dabbawalas who supply fresh home cooked food right to the working Mumbaiker sharp at lunch time and then carry the empty dabbas back to their homes, all at a monthly charge of approx Rs 450.

The ISO 9000 certified system are delivered 99.9999% of the time which comes at around 1 mistake per 6 million deliveries is an excellent example to demonstrate the power of standardized operational procedures. The dabbawalas have an average education level of around 8th grade and yet by following set operational procedures, the system is almost error proof with beyond six sigma quality even though there is no IT infrastructure involved.

Check out this quora article to know the entire supply chain model

Also do check out a documentary on the subject