For example, U.K.-based Aviva plc, the largest insurance company in Europe, is architecting its global customer service processes to constantly search for innovation and efficiency gains to deliver value to its customers. It is common for customer support call centers to use technologies to route calls to appropriate agents (agents with specific skills and temperament based on customer needs) within an office. Aviva’s insurance underwriting and claims business processes are designed to dynamically leverage the appropriate competencies from its global service centers, ranging from Australia to the Philippines, India, Europe, and Canada. Aviva’s focus is on enhancing the consumer’s experience (N = 1) by dynamically routing customer service requests to different parts of the world to provide the best service for that customer without compromising the cost of that service. This requires a capacity for realtime matching of customer profiles with agent skill profiles on a global basis.

In its global customer support processes, Aviva worked with its partners, including a business process outsourcing (BPO) firm called 24/7 Customer in India, to capture metrics in every subtask of the entire customer engagement process to better understand its customers. The process adopted by 24/7 Customer is visible with performance metrics such as customer satisfaction and time to resolve the problem. Outcome measures such as cross-sale and transaction completion are tracked in real time for each call. In order to accomplish this dynamic routing, Aviva must have visibility to the type of customer, loads, and the quality of agents and their skills in various locations. In an article published in the Economic Times in India in 2006, Richard Harvey, Aviva Group CEO, says, “Because we take a lot of care to measure customer satisfaction on a completely arm’s-length basis, we can demonstrate that our customer satisfaction from India is as strong as or even stronger than the United Kingdom.”

An additional benefit of this transparency in its global processes is that it enables Aviva to constantly monitor the best-in-class process execution across its global centers and disseminate that knowledge to other centers. John Ainley, HR director at Aviva, admits that the company is building a culture within the organization to promote competition in process performance across its global centers, to prepare its employees to emerge out of the “not-invented-here” syndrome and to accept process innovations from other centers. This leads to continuous improvement across all centers. Aviva has certainly taken a lead in reconfiguring global resources to create customer value in the insurance industry. But it is not alone.

A visit to the Chennai (India) office of the Dallas-based Perot Systems reveals a new level of visibility in its processes and a capability to predict and reconfigure resources for its global clients. The business process service unit of Perot Systems provides backoffice support to a number of hospitals and health insurance clients. Its Chennai center has developed a customized technology platform that integrates operations, HR, and finance business processes in a single portal. The Chennai team has disaggregated every process assigned to them and carefully identified both the skill requirements and performance metrics around each task. For example, each claim can be broken into subtasks. Each subtask requires a specific skill. One can identify the performance metrics appropriate for each subtask. Such a detailed understanding of the business process (granularity) is a key ingredient in their success.

Granularity is as important as visibility. Granularity allows managers to examine in depth the process steps, as well as the appropriate skills needed to perform them. The training modules required for each task at Perot Systems processes are digitized so that individual agents can take a set of e-learning courses at a time convenient to them. As the back-office business processes for large health insurance clients are executed in its Chennai office, the integrated platform automatically tracks the performance of every process step by every agent in every work shift. The best and worst performance levels across the organization are derived in real time through live data. Performance goals for each agent are redefined periodically with an analytical engine to enable continuous improvements in their processes and hence value for their global client. The same analytical engine also computes profitability for every client at the end of each shift.

Anurag Jain, vice president for business process services at Perot Systems in Dallas, states that this integrated platform in the company’s India office allows it to assess the performance of its employees in a direct and transparent way by which individual employees are presented with their performance in a task as compared to the mean, best, and worst 10 percent of performers in that task within the organization. It is not surprising that this BPO unit of Perot Systems has bagged several awards. And Mr. Jain has now been promoted to the position of India head at Perot Systems, which means he is leading the overall consulting, applications, insurance, and BPO units in India. Perot Systems has also extended into a new business service that helps engineering services firms apply lean manufacturing concepts to their operations.

While this may be viewed as an invasion of privacy, the reality is that firms are beginning to operate at a new level of visibility to individual performance, a performance that is measured and compared with others in the organization. In a high-performance organization, there may be no place to hide for the employees, agents, or their managers. Vardhman Jain, heading the offshore BPO Chennai center of Perot Systems, claims that its primary motivation was to create a transparent culture in which there is constant peer pressure to perform as well as incentive to improve processes.

A majority of its process improvement effort emanates from its own agents, akin to a Toyota production system. He adds that the company immediately spots development areas of employees who are unable to perform at expected levels and assigns training modules that specifically improve performance in targeted areas.

This same transparency in the company’s processes and analytics also enables it to accurately measure the cost incurred for each global client, and hence, the related client profitability. Performances of individuals or the profitability associated with a customer are not exercises performed periodically; rather they are performed continually. The company’s platform provides instant profitability of each client as it executes its processes. The analytical model can also predict future run rates of revenue based on demand patterns. This creates a capacity for Perot Systems to know profitability levels of potential engagements. This level of granularity and the capacity to execute the engagements allows Perot to submit proposals of great accuracy.

Large IT systems vendors in India, such as Infosys and TCS, have developed capabilities to constantly monitor the demand and resources needed for new IT services in their global markets. These firms recruit about 25,000 people annually, and their business models demand that they train these new recruits rapidly. These firms manage around 3,000 projects on site and offshore globally. They need to build capabilities to track latent demand for expertise in specific IT tools such as J2EE (Java to Enterprise Edition) or technology such as RFIDs and use these insights to manage their talent supply chain. Their annual training budget exceeds half a billion dollars. They need to understand resource needs and performance at the project level and profitability and experience at the customer level. Their challenge is to anticipate global demand for services, recruit and train for the right skills rapidly, and deploy resources to the right projects for the right clients globally to maximize long-term profitability. This is an analytical problem akin to a quantitative assignment problem familiar to operations researchers.

Nirvana, an emerging BPO company in Bangalore that serves global financial services clients in customer support and other back-office processes, is yet another example of a company’s unique applications of analytics and process discipline to constantly improve its understanding of customers and deliver value through global resource leverage. In addition to business process visibility and metrics- and measurements-based decisions in daily management, Nirvana has further integrated analytics-driven insights into its decision processes to build a capacity for dynamic resource reconfiguration. For example, while typical BPO organizations record at most 10 to 15 percent of the customer calls for customer support from India, Nirvana records 100 percent of the customer calls. This enables Nirvana to build a real-time customer profile based on both transaction data and keywords searched from customer conversations recorded digitally and mined for insights. In addition, Nirvana’s IT infrastructure also tracks the voice amplitude of each customer during the service call to sense the customer’s frame of mind or temper. For example, the voice of a male customer calling from Dallas is tracked and compared to the typical voice profile from similar callers. The variation in a customer’s voice amplitude is tracked in real time to be used as one of the inputs to build real-time customer insights and alter the company’s services appropriately, if needed. For example, Nirvana’s analytics engine based on data from multiple sources (transaction data, voice recordings, and keywords used by customers) has helped a large U.S. financial institution predict propensity to switch to a competitor at an individual customer level. This information has enabled the company to proactively alter its services to some of the high-risk customers and reduce its customer churn rate by
15 percent.

Similarly, consider the collaboration between the multi-billion dollar online retailer Overstock.com in the United States and 24/7 Customer in India. Virtual stores and sales chat agents are common in online retail sites because they try to enhance customer experience through either automated or human support “online chats” with customers. Unlike physical stores, online retailers, such as Amazon.com, eBay, or Overstock.com, have millions of visitors every day, and the majority of these visitors have no intention to buy and can easily switch to other shopping sites at the click of a mouse. Hence these retailers look for analytics to identify the right customers to engage in chat.

In this partnership with online retailers, 24/7 Customer experimented with analytics to crack the science of determining the right filters to apply in inviting customers to chat and at the same time matching the appropriate resources (that is, agents) for a given customer to enhance overall customer experience. First, the process of selecting customers and assigning agents is made visible to the U.S.-based retailer, and performance outcomes are transparent. Second, for individual customers who are invited to chat, the past data about those customers and their current requests or queries are combined to identify the appropriate agent to be assigned to that chat, illustrating real-time reconfiguration of resources.

The performance of agents, in terms of closing sales and overall customer experience and loyalty, is constantly assessed as feedback inputs to this analytics engine. The goal here is not to optimize product-agent selling output but to develop a real-time analytics engine that uses data from multiple sources to assess agents based on a set of customer, product, and experience attributes to determine the best available agent to talk to a given hot-lead customer. This process has also improved the performance of some agents by over 60 percent because it matches the right agents (based on their strengths and knowledge in specific product and customer categories) with the right customers. Now, if the company extends this by allowing customers to define profiles of the agents it would like to chat with, we will be moving closer to anticipation of demand and resource needs and cocreation of value.

It must be obvious that in order to perform analytics for insights, we need to focus on the visibility, granularity, accuracy, and timeliness of data. Visibility to the processes is a necessary first step. The premium paid by large businesses for logistics services offered by UPS or FedEx is not for mere visibility. These businesses are also paying for accuracy, timeliness, and the ability to reroute the businesses’ packages based on their current needs—that is, the capacity to reconfigure resources. Dave Barnes, senior vice president and CIO at UPS, states that his company has undertaken several time and motion studies to continuously optimize every step in the package delivery processes. These studies have revealed methods for loading the trucks in better ways through new heuristics and analytical methods such as training their drivers to fasten their seatbelt with their left hand while turning the ignition key with their other hand. Package routing information is constantly tracked and planned for each delivery truck, allowing for any changes in the routes if required either by the customer or by other interferences such as traffic or weather.

The examples of Li & Fung, UPS, the Department of Defense, 24/7 Customer, Perot Systems, and Nirvana illustrate increasing sophistication in the means available to create visibility and transparency to business processes. These examples also highlight the learning capability to reconfigure resources in real time, continuously improving the skill base of employees such that consumer needs and employee skills can be matched, and finally, building a personalization component in activities that appear simple and commonplace, such as delivery of parcels. These advances call for the integration of analytics with explicit business processes defined with fine granularity. Such integration demands extreme levels of training and intense measurement of both people and business processes. These systems are measurement intensive, and they prosper with the capacity for real-time feedback and corrective actions.

R = G needs to be appropriately configured to serve N = 1. The building blocks of analytic capabilities for R = G are depicted in Figure 3.2. It should now be obvious that visibility to processes and data within global supply chains (R = G) is crucial for building the multiple layers of capabilities that are critical for dynamic reconfiguration of resources. This visibility also helps managers anticipate consumer behaviors such that they can add or subtract appropriate resources to the whole supply network. In this process, we will also be able to get new insights—be it for operational improvement as in the case of UPS or for strategic redirection and course correction as in the case of the DOD supply chains that require integration of three distinct supply chains into one.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

Let us start with a well-known example. Access to global resources requires the capability to tap into a complex web of resources, expeditiously, and at the best global price. Li& Fung, a premium global trading group covering high-volume, time-sensitive goods including fashion accessories, furnishings, handicrafts, and home products, is a good illustration of process innovation through analytics. Li & Fung started as a pure trading company, sourcing its products from China for exports. However, within a decade Li & Fung had put in place a global network for managing supply chains for a large number of retailers in Europe and the United States. Unlike the traditional trading business model, Li & Fung does not own any production facility or large warehouses. As stated by Victor Fung, the CEO:

Everybody thinks that a trading company is just taking an order from the right hand and giving it to the left hand. The idea is that, maybe foreigners don’t know which factory to go to, so you perform an introductory role, maybe a quality control role, and there it stops. . . . Whenever we go in, we don’t just give them [the suppliers] an order and hope that they know what to do. We hand-hold them through the whole process. That’s why we say we almost are a virtual factory. . . . It is the way we orchestrate the production, come up with samples, and feed them information. All that is going way, way beyond that original matching function.

Li & Fung manages a large number of quality-conscious, cost-effective producers who can effectively deliver orders on time for customers such as JCPenney. More recently, the company identified the need to expand in locations near Europe and the United States to cut lead time for delivering physical goods. The overall business model of Li&Fung is based on the “end-to-end business process knowledge”—that is, from the point-of-sales data emanating from a specific branch of JCPenney in the United States (for example, how many white shirts, cotton, size 16 inches/32 to 33 inches, pattern XYZ) to its ability to replenish the inventory in that location through articulating its supplier network in maybe three countries.

The complexity of the company’s supplier network demands a capacity to manage information regarding regulatory restrictions across countries, managing the skill base of its suppliers and hiring in specific locations, and finally, integrating all this information to provide a seamless one-stop shop for its customers. The insights derived through the company’s accumulated data on various markets and individual supplier capabilities enable the company to deliver unique value. This system cannot function without a detailed, constantly updated understanding of all the suppliers—capacities, capabilities, costs, skills, and distances. This also demands a detailed understanding of the customers’ needs—urgency, quality, locations for delivery, and profitability. R = G must start with this level of visibility to all variables that can impact the appropriate resource configuration—“plant A in Thailand to serve JCPenney in Dallas for this order”—decisions.

In an R = G world, establishing the visibility to the entire chain is a good first step. Schneider Electric is the world’s largest manufacturer of electrical distribution systems and components. The company has a healthy growth rate; sales are U.S. $8.8 billion, and it has 70,000 employees in 130 countries. Schneider’s purchasing organization procures for four leading markets (each worth U.S. $1 billion): raw materials and means of production, fabricated metallic and plastic components, electronic and electrical devices, and nonproduction services. The global purchasing operation works with these four markets and a total of 33 commodity groups and multiple country organizations. The complexity of a supply chain such as this makes business analytics a necessity to effectively compete. Many large companies operate such supply chains without full visibility, and the consequences are obvious as they expose their supply chain to unknown global sources. For example, Serge Vanborre, a senior manager at Schneider Electric’s purchasing headquarters, says, “We want to know who is buying what from whom. We want to know the global purchases, be able to do an analysis in order to repartition our purchases and verify if the supplier policies are followed.”

A well-known example of visibility in a global supply chain is exhibited by leading logistics firms such as UPS and FedEx. For example, Atlanta-based UPS moves over 15 million packages around the world in a day, and it provides complete visibility to the end consumer on each and every packet. FedEx recently integrated the software systems of its ground, air, and freight businesses to provide full visibility to all of its customers and employees for the 6 million plus packages it handles every day.

Similarly, in one of the largest radio frequency identification device (RFID) projects implemented so far, Unisys has created full visibility for the global supply chain of the U.S. Department of Defense (DOD). Prior to this new system, the department operated three different supply chains for the army, navy, and air force with minimal integration. Furthermore, there was almost no visibility. In contrast, the new system connects global suppliers with 30 centers of DOD to any location in the world from Taiwan to Tacoma, providing complete visibility through RFID tags. As a result, when the military runs out of spare parts for a tank in Iraq, it has the capacity to locate the floating warehouse in the nearest ship instead of having to source the parts from the nearest depot, which in the past has often been far away.

Similarly, Homeland Security demands that it know where the cargo shipments that reach U.S. ports have been. So far, this has been an elusive goal. For example, a Sara Lee innerwear shipment manufactured in Pakistan and loaded in a container at Karachi can travel through a feeder ship to Mumbai, India, and then to Sri Lanka, through the Suez Canal, to Nova Scotia, and finally to New York. The items in the ship are invisible during their circuitous course of travel in the sea for almost a month!

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

Foresight is a result of understanding, through structured and unstructured data, the unfolding of competitive dynamics. There is value in identifying new patterns of relationships, predicting the
behavior and evolution of systems, and mitigating risk. In an N = 1 world, the behavior of individual consumers as well as broad patterns of change must be understood. In R = G, the capabilities of each vendor in the ecosystem in terms of costs, time, and quality levels must be understood and matched with the specific demands of a single consumer at a point in time. Furthermore, given the complexity of the entire ecosystem, the impact of change in any single variable, such as order entry, will have a ripple effect on other related subsystems such as inventory, spare parts, and manufacturing lead times.

A “small change” in order entry could trigger multiple changes in the totality of business processes. Managing the systemwide impacts of changes cannot be left to the gut feeling of managers. However, individual managers can, based on their experiences, interpret the signals differently (especially in a rapidly evolving system). Hence, foresight based on the real-time analyses of both structured and unstructured data is indispensable. Intuition and gut feeling are still useful, but not as a substitute for analytics.

Keeping business processes current and compliant with all changes and at the same time gleaning insights about the evolving behavior of consumers and the supply network require a commitment to analytics. Consider, for example, the Indian IRS. It is known that not everyone in India pays his or her taxes adequately. The IRS can safely start with the assumption that there is significant tax evasion in the country. In order to deal with widespread tax evasion, India’s tax agency is building a database of declared income and consumption patterns, such as travel, purchases of bigticket items such as cars, plasma TVs, deposits and withdrawals from banks, stock market activity, and the like, to spot patterns of tax evasion. The focus is on identifying individual taxpayers (N = 1) for further investigation. This project calls for deriving insights based on data from multiple sources.

A similar initiative is in place at the IRS in the United States as well. In the United States, the cost of tax avoidance is estimated at $350 billion. Tax evasion, around the world, is a moving target. In order to predict these behavior patterns, complex analytic models have to be developed. Data from a wide variety of sources must be pulled together to see the emerging patterns. Microsoft recently announced its purchase of a small start-up health search engine called Medstory, Inc., that applies advanced analytics to structured and unstructured medical and health information in journals, government documents, and the Internet to present an enhanced customer experience in access to health information. The desired result is a personalized information search based on one customer’s family history, prior medication, age, and gender.

Analytics must be driven by strategy. For example, in order to price health insurance for each diabetic consumer (patient), we need analytics, which in real time monitors behaviors (compliance on predetermined routines) but can also forecast likely behaviors. Analytics can also show where to allocate resources and how to optimize the “resource network.” Should a call from an irate and important customer in New Zealand be routed to India or Australia? This is a real-time decision, one of thousands, to which the firm must respond creatively. Insights also result from consumer concerns and comments. Understanding and researching blogs and chat rooms is another important source of insights. The capability to use analytical modeling tools is critical in every aspect of value creation, from understanding customer preferences and behaviors to supply chain management, global resource reconfiguration, skill management, and risk mitigation. We (i.e. CK Prahalad and MS Krishnan) will illustrate the power of analytical tools with applications focused on leveraging global resources to serve individual customers in global markets first (R = G), followed by illustration of such tools in moving toward N = 1.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

Competitiveness favors those who spot new trends and act on them expeditiously. Therefore, managers must develop insights about new opportunities by amplifying weak signals. These weak signals emerge from insights derived through a deep understanding and interpretation of a wide variety of information. For example, recognizing that SMS (text) messaging using a cell phone will be an important method for settling small payments is critical for the longterm success of Visa and MasterCard.

Spotting new trends requires comprehension of consumer expectations and behaviors and technological changes, as well as the nature of the supply chain and opportunities for its improvement. How does one spot trends early? Can a firm develop tools that aid in building insights? The new competitive landscape requires continuous analysis of data for insight. Analysis that is only episodic and ad hoc (as when a senior manager commissions a specific study, say, to assess the impact of oil prices on shopping patterns) or periodic (such as actual sales compared to forecasts) will not suffice. Traditional analytical approaches are often asynchronous with business changes. Hence, delays in recognizing, interpreting, and acting on the trends are emerging as critical impediments to competitiveness.

Every firm accumulates a voluminous amount of transaction data (for example, sales transactions) and equally large volumes of unstructured data (for example, video clips and advertisements). Managers need a mechanism to understand the accumulated information and extract valuable insights. Real-time analytics seize the opportunities and mitigate the risks in seeking to have global resources serving single customers.

The terms analytics and analytical models are used to describe a class of mathematical applications that permits businesses to crunch everything from picking stocks in trading rooms rapidly (in less than a millionth of a second) to identifying specific advertising messages based on your search at any time in Google. Some recent trends are helping firms build this capacity. Algorithms and quantitative methods used in analytics are evolving to help managers derive insights, often combining structured transaction data (numbers) and unstructured data as in documents, images, and video. Digitization of business processes, the Internet, and evolving ICT architecture enable real-time predictive modeling. These capabilities are at the heart of effective management in an N = 1 and R = G world In the subsequent entries, this will be demonstrated).

The link between data, analytics, and insights is shown in the figure above. As you can see, the quality of insight depends on both the quality of data and the quality of analytics. Models that are not built specifically to inform on strategic priorities are of little value of line managers. More important, insights that are not available when decisions have to be made are of little value. In this chapter, we will assume the availability of high-quality data that capture the millions of transactions in a company—be they sales, warranty claims, orders placed, or payments to suppliers. (The quality of data is a major concern in many firms. Data collection often is not standardized across the firm. Increasingly, data are also collected in a highly decentralized fashion, for example, by delivery agents with handheld devices. Rather than engage in a detailed technical discussion on how to “clean up databases,” therefore, it is assumed that the data quality is acceptable to perform analytics.)

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

1. As the number of customers and vendors increases, how can ICICI retain its N = 1 and R = G orientation? What analytic capabilities are needed to make this work?

2. Can the architecture of the ICT system automatically identify all the cross-impacts of any single change to a single subprocess such as minimum balance requirements? As the systems become complex because of the variety of products and services, as well as the choices that individuals can exercise, the architecture of the system must automatically sense and adjust itself. Can the system self-monitor? Will the ICICI face the same challenges that legacy systems face? How can the firm overcome this?

3. Can social infrastructure keep pace with the rate of change—new business models, scale, and scope with a large number of new employees? As the battle for talent in India intensifies, what is the quality control process for retaining the best talent and protecting the company’s culture?

ICICI has been used as an illustration because its strategy is still evolving and its competitive advantage both in India and increasingly in its global operations is based on its deep understanding of the business models and its links with business processes.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

The social infrastructure and culture fostered by the bank’s senior management since 1996 have been decisive factors behind its capacity to constantly experiment and seize new opportunities. The senior management recruited a young and dynamic management team. Team members were empowered to “kill” old legacy systems. These young managers turned themselves into change agents. In their new culture, managers were willing to share their best people for new initiatives that may not have been directly under the managers’ control. Winning as a corporation became a critical goal. One senior manager used the metaphor of “donating blood” to describe the sharing of the best people in her group for new corporate initiatives. It was not suicide, nor was it stealing. Few were likely to “hoard” key skills. The willingness to share skills reflected the bank’s confidence in its strategy and its willingness to experiment and grow rapidly.

The social architecture within ICICI depicts a sense of urgency and a need for real-time insights from transparent processes and data in all decisions. While hierarchy is used as a substitute for transparency in traditional firms, ICICI tries to use IT to cut as many unnecessary layers as possible from its decision chains. While the bank may not have a formal CIO, the head of IT has a visceral understanding of the bank’s business processes and needs and a similarly deep understanding of business processes and ICT capability as critical elements of senior management. For example, ICICI has aggressively adopted open-source software and has deployed open-office software across the organization, including the senior management staff (for internal communication), and the company is comfortable with it. In summary, the company has created a culture of boldness to constantly seize new opportunities and at the same time mitigate risk through transparency in processes and information.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

ICICI differs significantly from other banks in how it manages the synchronization between IT and business. First, it does not have a CIO. The bank’s head of IT has several years of experience in domestic and international banking, where he learned the strategic assets of ICT. Second, the entire senior management team, starting with the CEO, K. V. Kamath, has a deep understanding of the business implications of ICT. Synchronization between business needs and ICT investments is governed by a small group called the Technology Management Group that consists of both bankers and IT professionals.

The portfolio of ICT applications at ICICI contains only a few “packaged applications,” with the rest being customized applications to enable the dynamic business process capability that the strategy mandates. In reference to the building blocks shown in “Business Process and ICT Architecture“, ICICI has deployed standard pieces of hardware and software in the lower two blocks of the infrastructure while it has customized the ICT applications that support business processes. The application layer enables the business processes that help ICICI execute its business model and strategy. For example, the Technology Management Group at ICICI decided to abandon packaged software from a leading enterprise software vendor because the functionality in that product was restricting its capacity to change its business processes rapidly at low cost. The company opted to codevelop a customized system by partnering with one of the largest IT vendors in India. This codeveloped banking application is now offered in the international market.

Yet another distinction in the case of ICICI is the two-way flow of ideas and information between business units and IT. It is not just the traditional model of requirements emanating from business units that lead to demand for investments in IT. As noted earlier, the tech R&D lab and senior management constantly scan new technologies and developments in ICT for their business relevance. They engage commercial and academic partners to seed low-cost experiments.

For example, ICICI has partnered with the Indian Institute of Technology, Chennai, to develop a new electromechanical ATM machine customized to the rural Indian environment at a much lower price point. The climate in many parts of India makes the currency notes soggy with moisture and soiled with rough usage. Hence, the traditional ATM technology used in the West or in cities may not be suitable, since the makers of those ATMs expect cleaner currency notes. The new ATM from ICICI is being designed to deliver currency notes to consumers in collated bundles of cash similar to the way in which soda vending machines work.

Customized ATMs for rural markets, biometric devices for rural markets, and corporate cash management applications are some of the examples resulting from this exercise. ICICI has always been on the forefront of adopting new technologies. While business groups pull ICT projects on a need basis, the ICT team and the tech lab push new technologies through low-cost experimentation. In a typical large firm in the United States, various industry reports suggest that discretionary spending on IT is in the range of 15 to 25 percent of the total IT budget, while the rest— 75 to 85 percent—is spent on the incremental maintenance of legacy applications to keep current business operations running with minor changes. However, in the case of ICICI, only 20 percent of the total IT budget is spent on maintenance, while nearly 80 percent is spent on new business applications. One of the reasons for this distinct difference is that unlike traditional international banks, ICICI has no legacy systems. The business implication of this difference is significant because it unleashes resources for experimentation with new business processes and technology solutions.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

Senior managers at ICICI consider their capability to enable flexible business processes that support organic growth coupled with a flexible social structure to execute their strategies as a major asset. This flexibility allows constant experimentation on new products and services. Resilience in their business processes is reflected in their capacity to adapt credit assessment systems in retail banking, to connect directly with thousands of dealers around the country, and to scale up with microfinancing to self-help groups in rural banking with adaptive pricing. More important, all these initiatives begin as low-cost and low-risk experiments that take only a three-to four-month period to prove viable. Scaling of such successful experiments is a continuous process at ICICI. This flexibility in business processes does not mean that there is a lack of process definition at any given time. All of the processes and their output metrics are well defined and monitored.

ICICI has balanced the tension between well-defined business processes and the capacity to alter business processes to seize new opportunities. In 2004, ICICI identified opportunities to compete with Internet-only banks such as ING Direct in some developed markets. Since this did not require opening branch offices and success was largely defined by the flow of information and improvements in business processes, it was a viable opportunity. For example, ICICI manages the entire operations of direct banking to its customers in Canada from India.

The bank adheres to all the regulatory norms as set by Canadian authorities, and it offers 1 to 2.5 percentage points more in interest than other Canadian banks. The efficiency of its business process and ICT backbone fused with its base in India allows it to create a surplus (compared to its Canadian competitors) and share it with its customers. It is not surprising that the bank has been adding 2,000 customers per week in Canada (as of June 2006) and has over 500,000 international customers (as of that time). A study by a major consulting firm revealed that the ratio of operational costs in salary terms between ICICI and other Internet banks in Canada was 1:7 while IT costs per customer was 1:15. One senior manager at ICICI argued, “While large MNC banks are trying to push their back-office operations to India to leverage resources here, our entire operation is in India, and hence, we are well positioned to offer competitive services in the international market.” They call this reverse business process outsourcing (or reverse BPO).

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

The government of India mandated that every bank open rural branches. For every two urban branches that were licensed, the bank had to open at least one rural branch. Most established banks saw this as a burden and as a cost of doing business. In contrast, ICICI recognized, fairly early, how to effectively leverage this requirement into a new business opportunity. The bank realized that in order to reach the rural poor, it needed a new distribution system.

ICICI acquired the Bank of Madura, a regional bank in South India that had pioneered the concept of rural lending through selfhelp groups (SHGs)—groups of 20 village women who are organized to provide support to each other. As the women become a tight-knit unit, the bank then lends to the SHG, which in turn  provides loans to its members based on locally developed criteria. The SHGs prioritize, monitor, and collect dues.

ICICI recognized that rural community organizations and village self-help groups have a deeper understanding of customers in this market. ICICI has developed processes to efficiently screen, borrow, and manage loans as little as $100 at sites located every 6 to 10 miles in rural India. These borrowings include loans for crops, buying a buffalo or tractor, irrigation, education, health care, and mortgages in rural India.

ICICI has also innovated services such as biometric cards and digital kiosks to improve personalization and access to services. ICICI’s rural lending doubled in 2006 to reach $3.6 billion with over 3.2 million clients. These loans are personalized based on the earning potential of the borrower. For example, the terms of payment for a “buffalo loan” may be adjusted based on the milk yield from the buffalo. Biometric devices were introduced to protect the identity of each member in these self-help groups.

ICICI has partnered with thousands of community-based organizations and cooperatives to tap the microfinance market and provide unique solutions to finance different types of rural consumers at their convenience. In designing these services, ICICI has pushed along the N = 1 and R = G axes (see the figure at post: ) through personalization and resource leverage in collaborations.

Personalized Insurance for Diabetes (2006)

This initiative from ICICI Prudential is another powerful example of the many serving the needs of the one. ICICI has built an ecosystem of partners that includes pharmaceutical companies, local gyms, doctors, and nutritionists to provide access to its consumers. The company adjusts premiums based on individual levels of conformance. ICICI is building analytical models to understand the unique behavior of each patient and at the same time gain deeper understanding of the disease to further improve the services that it offers to customers.

These examples provide a remarkable range of business models at ICICI—many reaching “scale” in a short period of time. These initiatives combine access to resources from JPMorgan, analytics firms, self-help groups, and community banks (beginning of R = G) with portfolios of customizable products and services for the individual (N = 1). ICICI also allows rural self-help groups to decide their own priorities. Often, most of these initiatives have moved from conception to reality in one year. ICICI is still primarily an Indian bank with a growing appetite for global growth, and it is mastering the business of serving customers at every level of the economic pyramid.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)

Credit scoring based on the behavior of individual customers helps ICICI to understand customers and enables it to cocreate strategies for value creation across its customer lifecycle. ICICI, in this effort to understand its evolving consumer base, works with multiple partners with specialization in analytics to derive contextual insights and enhance consumer experiences. For example, this initiative maps a 360-degree view of its customers in terms of their engagement with the bank and searches for oppportunities to better inform customers and cocreate value.

Overseas Remittances: Money to India (2002)

Money2India is a remittance service offered by ICICI to capture the market of funds transferred to India by Indian nationals residing across the globe. Remittances from Indian expatriates back to India, through formal channels, were not a significant business till 2002. However, given the growing number of affluent Indian expatriates in the United States, Europe, and the Middle East and the restrictions on money transfers through unorganized sectors after 9/11, managers at ICICI saw a huge opportunity. Public sector banks from India such as the State Bank of India had a remittance business. They followed the traditional banking business processes and operated on a paper-based system for remittances from expatriates. It was a very slow process with no transparency, and obviously the consumer experience was not good. For example, on average it took around 10 days for the money sent by an expatriate in the United States to reach its final recipient in India. If the recipient was in a small town or village, the transfer could take even longer. ICICI created a digital bridge to integrate the U.S. and Indian markets through transactions between an ICICI account with JPMorgan in the United States and an ICICI bank account in India. ICICI leveraged the electronic transfer through JPMorgan and its electronic network of various branches across India to increase transparency to the expatriates and cut the cycle time from 10 days to less than 48 hours. ICICI currently enjoys over 30 percent market share of the $25 billion plus remittance market to India. ICICI has, more recently, introduced Indian rupee–denominated remittance cards usable in any ATM or over 100,000 merchant establishments in India.

Customized Corporate Banking Solutions (2003)

As noted earlier, the ICICI Bank has placed its ICT capabilities at the center of its value creation process, and it has an R&D lab with a small team of 40 people drawn from business and technology groups to experiment with new ideas. This combination of business and technology expertise enables the company to understand customer concerns and deliver unique solutions. These teams are provided incentives to identify unique solutions that enhance value to consumers. We illustrate with a few examples of how they have adapted products and processes to create unique value for customers.

ICICI was the first bank in India to introduce a check-scanning machine with its ATMs. All customer acknowledgment receipts for regular transactions include a small scanned image of the check, making it easier for consumers to track their transactions. Most banks in the United States still provide receipts with unique identification numbers, but consumers seldom use them due to the additional work needed to reconcile these receipts with their statements. The ICICI Bank integrated its magnetic ink character recognition (MICR) and image-scanning applications to provide this service. Similarly, for corporate banking, the bank has developed unique customized software applications to connect directly with enterprise systems of some of its large clients. ICICI has also developed unique solutions for its corporate customers. For example, large two-wheeler manufacturers in India, such as Bajaj Auto and TVS Motors, who sell over a million vehicles annually, face the challenge of reducing the float in clearing checks from their dealers countrywide. ICICI has delivered a cash management feature connecting dealers of these firms with their corporate offices so that information from a dealer’s check is itself treated as collection and directly linked to the financial systems of these manufacturers. This has reduced the collection time from weeks to a few hours.

This approach is closer to N = 1 and R = G, since the bank’s corporate customers in the past have had their own unique financial systems in different software platforms. ICICI has had to work with multiple global partners to customize this service and enhance its unique value to its customers. In another example, ICICI has partnered with the Austrian multinational firm Efkon, which specializes in electronic payment systems, to provide collection and cash management at over 2,500 retail outlets of Hindustan Petroleum Corporation Limited (HPCL), the second-largest oil marketing firm in India. In the first three years of its operation, the retail customer base for this payment solution has grown from a few thousand to over a million.

by C.K. Prahalad and M.S. Krishnan, Via The New Age of Innovation: Driving Cocreated Value Through Global Networks (2008)