Operations Articles

Article / Updated 07-25-2022

In this article, we look at some business types in more detail to see how traditional financial firms are being shaken up — and improved — by FinTech disruptions. What is FinTech? FinTech is an overarching term for the combination of finance and technology. However, within FinTech, many subcategories apply to specific sectors of the financial world. Here’s a quick summary of them: Capital Markets Tech, in which companies leverage newer technology such as artificial intelligence, machine learning, and blockchain, is led by seasoned capital markets veterans and is both collaborating with and disrupting the financial services incumbents. WealthTech unites wealth and technology to provide digital tools for personal and professional wealth management and investing. This sector includes brokerage platforms, automated/semiautomated robo-advisors, and self-directed investment tools for individual investors and advisors to navigate the changing landscape in wealth management. For more information, check out The WealthTech Book, edited by Susanne Chishti and Thomas Puschmann (published by Wiley). InsurTech is a combination of insurance and technology. It refers to innovations that generate efficiency and cost savings from the existing insurance industry model. For more information, see The InsurTech Book, edited by Sabine L. B. VanderLinden, Shân M. Millie, Nicole Anderson, and Susanne Chishti (published by Wiley). RegTech is a community of technology companies that solve regulatory challenges through automation. The increase in major regulatory policy and the rise in digital products have made it imperative for companies to check for and implement compliance issues, and this can be difficult with old, manual processes. For more information, refer to The RegTech Book, edited by Janos Barberis, Douglas W. Arner, and Ross P. Buckley (published by Wiley). PayTech refers to the combination of payments and technology. Innovative payment services now form part of the PayTech ecosystem and have dominated the early days of the FinTech revolution through mobile, cross-border, peer-to-peer, and cryptocurrency payments. Financial institutions have had to digitize their current offerings to create new channels linked to a digital platform. For more information, see The PayTech Book, edited by Susanne Chishti, Tony Craddock, Robert Courtneidge, and Markos Zachariadis (published by Wiley). AI in Finance refers to how artificial intelligence, machine learning, and deep learning are applied across financial services companies today and how they could be used in the future. For more information, see The AI Book, edited by Ivana Bartoletti, Susanne Chishti, Anne Leslie, and Shân M. Millie (published by Wiley). LegalTech combines the nature of legal technologies and their relationship with data, the Internet of Things (IOT), cybersecurity, and distributed ledger technologies as well as ethical considerations of the technological advancement. For more information, refer to The LegalTech Book, edited by Sophia Adams Bhatti, Susanne Chishti, Akber Datoo, and Drago Indjic (published by Wiley). Banks Some larger financial institutions have adopted the phrase “We’re just a technology company that happens to have a banking license.” This is mostly a marketing gimmick, although it’s perhaps partially true for some of the new challenger banks that are attempting to disrupt the incumbent banks. However, with customer acquisition costs high and increasing regulatory hurdles to surmount, new challenger banks need to decide whether they will build their technology stack themselves or work with FinTech partners to develop the innovation required to topple the incumbents. The financial institutions that are effectively managing this move to become FinTech companies are those that understand how to move quickly to deliver what the consumer needs in an industry on the verge of further change. Most of those who succeed have taken a hybrid approach, focusing on partnerships, acquisitions, and internal initiatives. Several incumbent banks are known to be developing new digital-first products in a bid to keep the new wave of challenger banks and providers in the background; an example is Bo from the Royal Bank of Scotland. They are also gradually adopting much more ambitious cloud-based platforms (despite their paranoia about their data being hacked) on which they can offer or launch numerous products. These initiatives are being supported by the likes of Amazon, Google, and Microsoft, which provide cloud hosting services and enable banks to develop core banking Software-as-a-Service (SaaS) platforms with the required encryption security. Asset management Traditionally, serious investors have valued personal investment advice from human experts, and they haven’t minded paying for it. However, the asset management industry has been attacked from two different angles: One of these is the march toward passive investments (such as exchange traded funds, or ETFs) over active asset management. ETFs are traded like stocks where the holdings track to some well-known index, such as the Standard & Poor’s (S&P) 500. The other is the rise in popularity of robo-advisors, which use ETFs as a strong part of their strategy. A robo-advisor is an investment selection tool that uses algorithms and machine learning to offer investment advice and management to users. The trend toward passive asset management has been apparent for some time in the retail/business-to-consumer (B2C) space, but we’re lately also seeing it with the larger business-to-business (B2B) investors as the stock market index returns continue to rise and they are looking to cut costs to further enhance returns for their clients. WealthTech firms are enabling investors to self-manage their portfolios by offering users technology-enabled tools to help make investing decisions. These tools can include full-service brokerage alternatives, automated and semiautomated robo-advisors, self-service investment platforms, asset class specific marketplaces, and portfolio management tools for both individual investors and advisors. They consider not only investment opportunities but also factors such as a user’s goals, income, marital status, and risk aversion to differentiate on their offering. They enable those who can’t afford a traditional financial advisor to have similar — if not more informed — advice at a lower cost. Insurance If the banking and asset management firms think they have it tough with the rise of FinTech firms, there are many that believe that the insurance industry is even more prone to disruption — and innovation. InsurTech firms initially started to explore offerings that large insurance firms had little incentive to pursue. For example, they offered customers the ability to customize their policies, and they used internet-enabled devices to collect information about behavior (such as driving habits) that could be used to dynamically price insurance premiums. Traditionally, the insurance market has worked with relatively basic levels of data to group respective policyholders together to generate a diversified portfolio of people. However, InsurTech firms are tackling their data and analysis issues by taking inputs from various devices, including GPS tracking of cars and activity trackers on wearables so that they can monitor more defined risk grouping and therefore allow certain products to be more competitively priced. In addition to better pricing models, InsurTech firms are using highly trained artificial intelligence (AI) to help brokers find the right mix of policies to complete an individual’s insurance coverage and credit score. In some cases, they can replace brokers entirely, further disintermediating the process (and saving costs). Apps are also being developed that can combine contrasting policies into one platform for management and monitoring. Some of the benefits of that might include enabling customers to purchase on-demand policies for micro-events and enabling groups of individual policyholders to become part of a customized group that is eligible for rebates or discounts. Insurance is also a highly regulated industry. Major brokers and underwriters have survived by being both prudent and risk averse. They are therefore suspicious of working with InsurTech start-ups, particularly those that want to disrupt their stable industry. Many InsurTech start-ups require the help of traditional insurers to handle underwriting issues, so the incumbent players here are likely to collaborate with and invest in their junior partners. Regulation and legal work RegTech is the management of and compliance with regulatory processes within the financial industry, using technology to address regulatory monitoring, reporting, and ongoing compliance. The predominantly cloud-based, SaaS offerings to help businesses comply with regulations efficiently and more cheaply act as the glue between the various sectors of the financial services industry described earlier. LegalTech describes technological innovation to enhance or replace traditional methods for delivering legal services across financial services and beyond. This innovation includes document automation, predictive artificial intelligence, advanced chat bots, knowledge management, research systems, and smart legal contracts to increase efficiency and productivity and reduce costs. With the use of big data and machine-learning technology, RegTech and LegalTech firms reduce the risk to a financial institution’s compliance and legal departments by identifying potential threats earlier to minimize the risks and costs associated with regulatory breaches and any legal work. RegTech firms can combine information from a financial institution with precedent data extracted from prior regulatory events to forecast probable risk areas that the institution should focus on. LegalTech firms can help financial institutions draft documents, undertake legal research, disclose documents in litigation, perform due diligence, and provide legal guidance. These analytical tools can save institutions significant time and money, including saving them from having to pay fines levied for misconduct. The institutions also have an effective tool to comply with ongoing rules and regulations specified by financial authorities, which are constantly prone to amendments. Payments From banknotes to coins to plastic cards and mobile devices, payments have evolved over the centuries to include a number of ways to help financial transactions take place between individuals, institutions, and governments. Payment technologies and global infrastructures that facilitate payments around the world also are changing. Over the last few years, mobile money has helped millions of people in developing countries get access to the financial system and tackle the goal of financial inclusion. Digital and cryptocurrencies such as Bitcoin, Ripple, and Ether have also entered the payments sector, which is innovating more rapidly than ever with the goal to move value cost-efficiently in real time and at near zero cost. As a result, the PayTech sector is booming; established players closely work with newcomers as there is no end to the creativity of the PayTech and payment industry.

Article / Updated 07-15-2022

The process of making anything starts when you decide what to make, how much to make, and when to make it. In a manufacturing company, this process is (conveniently) called production planning and scheduling. Service companies often make life more complicated by finding creative names for this process, but most of them sound a lot like “service planning and scheduling.” If you’re working in a services supply chain, try not to get hung up on the word make. Just remember that the point of any make process is to transform inputs such as raw materials and technical skills into outputs for a customer. For a doctor, the make process would be performing a surgical procedure. For an artist, it would be creating a painting. Planning production Before you can create a good production plan, you need to take a lot of factors into account. Here are 10 examples of the kinds of information that you really, truly need to consider before you can tell whether a production plan will work: Determine when customers need the product and whether they’re waiting for it now. Determine how long it’ll take you to make the product. Determine the capacity of your manufacturing process. Determine the setup time required to make the product and whether that time will affect the setup time for other products. Determine how to prioritize the order in which you’ll make products. Determine what parts, components, or supplies you need to have on hand so that you can make a particular product. Determine whether you already have the parts you need or have to order them. If you must order parts, determine the supplier’s lead time and the shelf life of the products. Identify risks that could disrupt production. Determine whether you need to schedule time for breaks, holidays, changeovers, and equipment maintenance. This list isn’t complete, but it’s enough to make the point: You have so many factors to consider that production planning can quickly become overwhelming. The only way to make it work is to develop a production planning process and set some rules. You also need to ensure that the rules give you enough flexibility to change the plan when necessary. The following figure is a high-level view of the steps involved in creating a production schedule. Setting a demand goal Production planning starts with a high-level goal: how much you want to sell. You can think of this goal as the “in a perfect world” scenario. If you think you’ll have 1 million customers next month in your fast-food restaurant, you’d start with a demand goal of 1 million hamburgers. This high-level demand goal is called the master demand schedule (MDS). It’s okay if your MDS is optimistic, but try to keep it reasonable. There’s no point in building a production plan for a sales target that you’d never be able to meet. Creating a production schedule After determining your demand goal, you break that sales goal down into a master production schedule (MPS). In other words, building the MPS is how you to decide what you’ll need to make each day to meet the MDS goal. Creating an MPS forces you to look more closely at the materials you need and when you need them. It also drives you to look at the people and equipment you have available to make your products. As you build your MPS, you begin to uncover production constraints, which are bottlenecks or problems that may interfere with production. You may not be able to order as much of the raw materials as you want because your suppliers don’t have enough capacity, for example. Or perhaps your manufacturing equipment can’t produce the materials quickly enough. In the example of a fast-food restaurant, two obvious constraints that the MPS will need to address are space and time. You have a limited amount of room to store buns, meat patties, and lettuce, and these ingredients are perishable, so you need to use them before they spoil. Each constraint that you find requires you to make some decisions. You need to consider whether you can do something to resolve or eliminate the constraint, such as find a new supplier or rent extra storage space. Or you may need to change your production schedule. It’s common to repeat this constraint resolution process several times, because each time you change the MPS to resolve a constraint, you need to check whether that change affects other constraints. In other words, production scheduling is an iterative process. Finalizing the production schedule When you know what materials you need to order, and you’re confident that they can be delivered on time, you can finalize, publish, and execute your production schedule. The final production schedule gives your team its actual production targets: how much you expect to make and when you expect to make it. Your production schedule also drives purchase orders to authorize buying the components you need from your suppliers. The schedule may be broken into jobs or batches of products that are similar or that are being made for the same customer. When the jobs are scheduled, you can sequence the delivery of parts so that they show up just in time (JIT) for you to use them. Lean Manufacturing often combines parts sequencing and JIT deliveries. In an automotive assembly plant, for example, many kinds of upholstery are used for car seats, so the seats are sequenced to show up in a particular order and are delivered to the assembly line JIT. If everything works properly, your production schedule won’t change and should be stable. But things don’t always work that way. Even after the production schedule is published, there’s a good chance that you may end up making changes if things don’t go as you expect — if a shipment of supplies gets delayed or a machine breaks down, for example. When you revise the schedule, you may have to change the order of production jobs or adjust your production targets. This replanning also affects both your suppliers and your inventory levels, because it changes the order in which you use each component. Because so many activities are driven by the production schedule, frequent replanning can cause confusion and frustration. A production schedule that changes too often is called a nervous schedule. Nervous production schedules create waste in a supply chain, such as unnecessary work and excess inventory. Most companies make a choice about how far in advance they can realistically change the production schedule without creating chaos for their supply chain. This threshold, usually measured in days or weeks, is called a time fence. A company might decide that it’s okay to make a change to the production schedule with at least one week’s notice. In this case, it would be possible (but not desirable) to make changes to the production schedule outside the one-week time fence. But when the company crosses that time fence — is less than one week out from a production run — the schedule is frozen, and no more changes will be allowed. The earlier in the process you can identify a constraint and replan the production schedule, the better off you’ll be. In most cases, changing the production schedule after you’ve already issued purchase orders for the supplies means that you’ll end up with extra inventory, which increases your costs. You can think about the challenge of production scheduling for a fast-food restaurant. Suppose that something unexpected happens: You sell fewer burgers than you expected, everyone asks for extra pickles, or there’s a recall on lettuce. In each case, you need to see whether these differences change your goals or create constraints; if they do, you’d need to replan your production schedule. Your production targets should always be aligned with your sales goals to ensure that you aren’t making too much or too little to satisfy your customers. This process is called sales and operations planning. In the old days, people prepared and updated production schedules manually, which was a complex, time-consuming process. Today, most companies update schedules automatically by using material requirements planning software. Capacity Every person, every group of people, and every machine in the world has a limit to how much it can process or produce in a particular amount of time. Whether you’re in the business of manufacturing bottles or delivering babies, you refer to this limit as your capacity. There are lots of ways to measure and define capacity, but when you strip away the fluff, every supply chain manager needs to understand three concepts because they factor into your production plan: design capacity, operating capacity, and capacity utilization. Design capacity Design capacity (or theoretical capacity) is the maximum that a machine (or person) can possibly produce. The design capacity of your imaginary fast-food restaurant is the amount you could make if every person and every machine were running continuously, every minute of every day. That capacity might mean a whole lot of hamburgers and French fries but still isn’t infinite. Operating capacity Let’s be real: Most processes don’t run at their design capacity (at least not for very long!). People need to take breaks. Facilities shut down for shift changes. It takes time to perform equipment maintenance and software upgrades. When you take all these constraints into account, you end up with a new limit on how much you can make, which is much lower than your design capacity. This limit is called your operating capacity (or effective capacity). Unless you’re making only one product over and over, you probably need to shut down some machines and make changes between jobs, such as switching tools or bringing in different components. This setup time affects how much operating capacity is available for making products. And, of course, things can go wrong: A machine could break down, you could run out of inventory, or someone could be late for a shift. Any of these issues — and many others — can slow a manufacturing process, and all of them eat away at your efficiency. Because you could never possibly make more of a product than your design capacity would allow, the design capacity is technically one of your production constraints. Because operating capacity is almost always lower than design capacity, however, it’s rare for a process to be constrained by the design capacity. Operating capacity is one of the main constraints on production. In many cases, you can do things to increase operating capacity, such as running extra shifts or changing your maintenance procedures. Therefore, you may have some flexibility when managing the operating capacity for your production plan. A common goal for supply chain managers is to increase operating capacity and get it as close as possible to the design capacity. Capacity utilization With all the factors that can constrain production, the actual output of a manufacturing process is often a fraction of how much you think it could make. A common way to measure production output, or yield, is the percentage of operating capacity that you actually use. This percentage is called capacity utilization. If your process is running at full speed, making as many widgets as it possibly can, your capacity utilization is 100 percent. The U.S. Federal Reserve tracks industrial production and capacity utilization across various business sectors as a way to measure how well the economy is doing. Find the latest capacity utilization rates. A common goal of supply chain management is to increase capacity utilization. The more capacity you use, the more products you’re producing and the more money you’re able to make with the assets you have. You can see how these concepts are related by looking at the fast-food restaurant example. The number of burgers that you make is your production output, which is a smaller quantity than your operating capacity, which in turn is smaller than your design capacity. This figure illustrates the relationship of production output (capacity utilization) to operating capacity and design capacity. Increasing capacity utilization always sounds like a good idea at first. But when you look at it more closely, sometimes it can increase your costs and decrease your efficiency. Your car, for example, probably has the capacity to drive at 100 miles per hour, but it gets much better gas mileage at closer to 50 miles per hour. (Let’s ignore traffic laws for a second and focus on the mechanical issues.) In addition to burning more gas, driving your car at 100 miles per hour is going to cause many of the parts to wear out more quickly, and it gives you less time to react to a pothole in the road. So, even though the car has the capacity to go faster if you need it to, you’ll probably choose a slower pace for day-to-day commuting. In other words, you’ll decide that it’s better, overall, to operate your car well below its design capacity. In the same way, manufacturing processes often become less efficient when they get close to their capacity limits. One obvious reason is that equipment may wear out faster, which causes breakdowns. Also, increasing capacity utilization (in other words, making more products) can create an inventory problem if the rest of your supply chain can’t keep up. Your real goal as a supply chain manager is to make only as many products as your customers will buy — to provide enough supply to meet demand. If your output is high, but your sales are low, increasing manufacturing capacity utilization means that you’ll build up unneeded inventory and tie up your company’s cash, which is bad for the supply chain. The goal of production planning and scheduling is to make as many products as your customers will buy at the precise time that they need them. Building your production schedule around customer demand and your supply chain’s constraints ensures that you use your capacity efficiently while keeping your inventory as low as possible.

Cheat Sheet / Updated 04-18-2022

Turning your successful domestic business into a successful global one requires a considerable amount of thought and planning. All the economic advantages you imagine (new markets, manufacturing cost savings, labor cost savings, and so on) can quickly be outweighed by physical and cultural challenges. If you've done your homework and are one of the companies out there who have made a successful go of global logistics, you are likely to be asked at some point to provide support services to humanitarian and disaster relief efforts. If so, it's important to know what you'll be getting into.

Cheat Sheet / Updated 04-12-2022

Without quality control, your organization can't survive for long. Successfully implementing, maintaining, and evaluating quality control standards is critical whether you're seeking ISO certification or just keeping up with customer needs. When implementing a quality control process, you'll likely face resistance from people within the organization. By staying vigilant and addressing potential problems early, however, your organization can function at a high level.

Cheat Sheet / Updated 04-11-2022

Although the term supplier diversity has been around for half a century, aspects of it still mystify organizations and rout the best intentions. Being expected to know everything can be daunting. This Cheat Sheet provides a quick reference to help you understand some key supplier diversity considerations.

Cheat Sheet / Updated 03-01-2022

If you're thinking about starting an import/export business, do some research and ask yourself some key questions to see if a career in international trade is right for you. Make sure you're in agreement with the buyer or seller of goods about basic issues regarding your import/export business and stay current on trade rules and regulations in the countries that you're importing from or exporting to.

Cheat Sheet / Updated 02-22-2022

What is Fintech? A FinTech company is any company that provides financial services, software, or technology to individuals, companies, governments, or financial institutions. If you’re interested in finding out more about FinTech, it helps to know a few basic definitions, understand the benefits of working with a FinTech provider, and get a handle on core technologies.

Cheat Sheet / Updated 02-18-2022

A supply chain is a complex system made up of people, processes, and technologies that deliver value to a customer. Supply chains connect the functional departments within a company, and they connect every company to its customers and suppliers. Supply chain management involves coordinating all the work that is required to profitably deliver a product or service to your customer.

Cheat Sheet / Updated 02-17-2022

In business, operations management is the development, execution, and maintenance of effective processes — whether used continuously for the production and delivery of goods or services or for the one-time execution of a major project. Some mathematical formulas come in handy to keep business operations running as smoothly as possible, from managing inventory to estimating the time and cost of a special project.

Article / Updated 09-27-2021

Managing inventory is an important way for a business to manage variations in demand. Inventory can provide a means to manage demand fluctuation so that process capacity and resource utilization are kept steady and used most efficiently. Of course, maintaining an inventory isn't cost-free or risk-free, because inventory represents tied-up cash and storage costs and comes with the risk that the inventory will spoil or become obsolete. In the case of bank or restaurant customers, if they have to wait in a line too long, the risk is a lost customer. Following are some formulas for the three most common inventory policies that companies use to try to minimize their risk: Newsvendor inventory policy Continuous review inventory policy Periodic review inventory policy Newsvendor inventory policy The newsvendor policy is often also called single period inventory management. As the name implies, the business has one shot to purchase the inventory that it believes it will need to meet customer demand. This policy is typically used for seasonal items, such as swimsuits and snowblowers. Let μ = expected demand, σ = standard deviation of demand, Q = an order quantity, ES = expected sales, ELS = expected lost sales, ELI = expected leftover inventory, = the cost of understocking one item, and = the cost of overstocking one item. Newsvendor optimal order quantity is Q such that: Continuous review inventory policy In a continuous review inventory policy, you continually monitor your inventory and order a fixed quantity every time your inventory level reaches a preset quantity. The fixed quantity is often called the economic order quantity (EOQ) because it's the quantity that minimizes your total inventory costs. You place an order for the EOQ whenever your inventory level reaches the set reorder point (ROP). To calculate the EOQ and ROP, use the following equations. Let D = annual demand for the product, S = setup cost to place one order, H = holding cost to keep one item in inventory for a year, SS = safety stock, and z = the z value for the desired service level. ROP = (Average Demand * Average Delivery Lead Time) + Safety Stock Periodic review inventory policy In some cases, it's impractical to continuously monitor inventory levels, and a business may choose to periodically monitor. In this policy, the firm sets a certain time (T) to check inventory levels. At this time, the company orders inventory to bring levels up to a target inventory (TI). The company typically sets the T based on its operations and calculates the TI based on this T using the following equation: TI = Average Demand * (Average Lead Time + T) + SS Where SS is calculated as: