Deploying Lean Principles to ERP Implementation Projects

The competitive environment that both Manufacturers and Distributors alike have experienced in recent years in the era of Globalization, Currency Fluctuation, and Market Pressures has given rise to the business impetus to run a leaner operation to remain competitive. These issues have trickled down to the IT department. IT Professionals are at times facing an enormous obstacle. They are expected to align the organization’s IT infrastructure with the strategic and operational components of the Business to improve upon Service Delivery. The other part of the issue is to reach those goals with fewer resources. Many IT Managers have had to adopt techniques to run a lean IT shop and extend that to the principles of the IT projects that are under development.

An ERP project is an ideal area to utilize lean concepts to further understand how this can be achieved, but we must first understand the basic principles of lean and how they relate to an ERP project implementation.

Lean Definition
Lean Principles have evolved from the Lean Production Philosophy which has its origin in the set of business philosophies developed in post-war Japan known as T.P.S. (Toyota Production Systems)— which has as its core philosophy cost reduction through elimination of waste (muda Japanese).The principles deployed in Lean made Toyota the pre-eminent auto-manufacturer in the world and by extension helped shape Japan into an economic power.

The concepts outlined in Lean Manufacturing evolved into a series of principles which evolved into a business concept known simply as Lean which can be applied across several disciplines i.e. Project Management, IT Deployment, etc.

The Organization known as APICS (American Production Inventory Control Society) has defined Lean as “A Philosophy of Manufacturing based on planned elimination of waste and continuous improvement of productivity.”

How ERP & LEAN Work Together
One of the ways in which ERP & Lean complement one another is in areas such as: Machine Setup Time, labor costs, and materials handling.

During Machine setup, time is lost due to the time the machine operator must setup or take down and change tooling. At other times the employee must spend valuable time looking for tools or preparing for many delays related to machine setups as a result of constant changes to the production schedule at the same work station. One of the core values of Lean Manufacturing is known as the “5S Method.”

* Sort - Eliminate all unnecessary tools, parts, instructions
* Simplify - A place for everything and everything in its place
* Shine - Maintain a tidy and organized work environment
* Standardize - Document the rules for maintaining the first 3S instructions
* Sustain - Operations carried out in sequence, eliminating waste

Execution of the” 5S Principles” meant that resources were planned in ahead, tools were in place and readily accessible, and (where possible) production jobs were scheduled to run in a sequence that minimized machine set-up. When the “5 S Principles” were applied to an ERP environment they looked like this:

* Sort - Use only parts of the ERP system which benefit the company
* Simplify - Use ERP to enable integrated business processes i.e. inventory control
* Shine - Ensure that you work with accurate and timely data
* Standardize - Document and standardize, business processes
* Sustain - Business Processes executed by ERP executed on a consistent and timely basis

The results achieved by the ERP system deployment have resulted in cost reductions and improvements in efficiency meant that work in process has to be managed closely to ensure that no bottlenecks in production occur, The tools within ERP such as Capacity Planning and Costing Modules to define direct vs. indirect labor now mean that only the time the job runs in production are calculated as direct labor.

The efficiencies gained by the ERP implementation produced reduction in set-ups, and other shop floor time management processes, means direct labor costs are also maximized. Through the use of data collection devices, you can account for time spent “on the clock” and nonproductive time spent while a work-order is in queue. This way, non-productive time no longer figures as a basis for calculating direct labor. Finally, as ERP itself evolves with the use of BI tools, along with lean techniques and philosophies such as lean pull-production principles, you will achieve business gains as you introduce JIT (just-in-time), resulting in greater capacity to monitor inventories, manage more efficiently, and align your suppliers to lean-pull production techniques. In the lean ERP model, especially where cellular production techniques in manufacturing are introduced, there is going to be less handling of materials. Once a production job begins on the shop floor, production raw materials flow through the plant rather then sitting idle waiting to be used in Production.

As a result of lean ERP being used in the organization, inventory moves from work station to work station in a continuous flow through the plant—and as a result, return on investment is accomplished through the use of improvement in efficiencies and reduction in inventory investments.

Process ERP vs. Discrete ERP Differentiation

People often ask us “what’s the difference between process and discrete ERP?” We model both systems in such a way that they share many common components, nevertheless process manufacturing industries have unique requirements that differ from discrete manufacturing industries. Here’s a rough overview of the difference.

A quick definition from APICS (The Association for Operations Management) describes discrete manufacturing as “The production of distinct items such as automobiles, appliances, or computers.” Whereas process manufacturing covers “Production that adds value by mixing, separating, forming, and/or performing chemical reactions. It may be done in either batch or continuous mode.” Now let’s look at a few examples.

Think about what your company manufactures. Does it require mixing chemicals? If so, you may need an ERP system that does things like calculate ingredient quantities. If your industry produces the type of product that once made, doesn’t lend itself to being disassembled into its individual components, it’s likely you need to consider a process ERP system. On the other hand if your company assembles products from many component parts, you’ll require discrete manufacturing functionality. In his article, Process Manufacturing Software: a Primer, Joe Strub explains the difference with examples.

“Once you make a can of soda, you cannot return it back to its basic components such as carbonated water, citric acid, potassium benzoate, aspartame, and other ingredients. You cannot put the juice back into the orange. A car or computer, on the other hand, can be disassembled and the parts, to a large extent, can be returned to stock.”

In addition, P.J. Jakovljevic explains other characteristics in product development within a process manufacturing environment, such as the fact that the manufacturing materials may vary in quality or degrade over time, or that process manufacturing is scalable. He states

“… if the formula calls for 1,000 pounds of cake flour, but one only has 500 pounds, one can still bake cakes, just not as many. Conversely, in discrete manufacturing, one missing part means waiting for it before the finished assembly unit can start rolling off the production line.”

We model functionality for manufacturing in discrete or process industries under the following categories.
Discrete Manufacturing Process Manufacturing
Product Costing Formulas/Recipes
Shop Floor Control Process Model (Formulas and Routings)
Field Service and Repairs Process Batch Control and Reporting
Production Planning Conformance Reporting
Project Management Process Manufacturing Costing
Product Data Management (PDM) Material Management
Product/Item Configurator Product Costing
Shop Floor Control
Production Planning

If you’re talking about requirements involving bills of material (BOM), listing the component parts for assembly you’d find those covered through the discrete manufacturing categories, whereas if you’re talking about functionality for formulas, recipes, or ingredients, those would tend toward the process manufacturing categories.

To better understand which type of system would fit your environment, you can consider target industries addressed by different process ERP vendors such as Deacom, CDC Ross, and 3i Infotech. Or review some discrete ERP vendors such as Epicor, SAP, and 3i Infotech. That is by no means an exhaustive list, rather it’s only a few example products, certified in TEC’s knowledge bases.

Notice that 3i is listed in each, in fact other products are also available for both industries. The articles that I mentioned above (and below) mention some of the things to take into consideration from vendors with products that will support either industry. It’s important to consider how these vendors adapt their products to the industry’s needs.

Process ERP vs. Discrete ERP Differentiation

People often ask us “what’s the difference between process and discrete ERP?” We model both systems in such a way that they share many common components, nevertheless process manufacturing industries have unique requirements that differ from discrete manufacturing industries. Here’s a rough overview of the difference.

A quick definition from APICS (The Association for Operations Management) describes discrete manufacturing as “The production of distinct items such as automobiles, appliances, or computers.” Whereas process manufacturing covers “Production that adds value by mixing, separating, forming, and/or performing chemical reactions. It may be done in either batch or continuous mode.” Now let’s look at a few examples.

Think about what your company manufactures. Does it require mixing chemicals? If so, you may need an ERP system that does things like calculate ingredient quantities. If your industry produces the type of product that once made, doesn’t lend itself to being disassembled into its individual components, it’s likely you need to consider a process ERP system. On the other hand if your company assembles products from many component parts, you’ll require discrete manufacturing functionality. In his article, Process Manufacturing Software: a Primer, Joe Strub explains the difference with examples.

“Once you make a can of soda, you cannot return it back to its basic components such as carbonated water, citric acid, potassium benzoate, aspartame, and other ingredients. You cannot put the juice back into the orange. A car or computer, on the other hand, can be disassembled and the parts, to a large extent, can be returned to stock.”

In addition, P.J. Jakovljevic explains other characteristics in product development within a process manufacturing environment, such as the fact that the manufacturing materials may vary in quality or degrade over time, or that process manufacturing is scalable. He states

“… if the formula calls for 1,000 pounds of cake flour, but one only has 500 pounds, one can still bake cakes, just not as many. Conversely, in discrete manufacturing, one missing part means waiting for it before the finished assembly unit can start rolling off the production line.”

We model functionality for manufacturing in discrete or process industries under the following categories.
Discrete Manufacturing Process Manufacturing
Product Costing Formulas/Recipes
Shop Floor Control Process Model (Formulas and Routings)
Field Service and Repairs Process Batch Control and Reporting
Production Planning Conformance Reporting
Project Management Process Manufacturing Costing
Product Data Management (PDM) Material Management
Product/Item Configurator Product Costing
Shop Floor Control
Production Planning

If you’re talking about requirements involving bills of material (BOM), listing the component parts for assembly you’d find those covered through the discrete manufacturing categories, whereas if you’re talking about functionality for formulas, recipes, or ingredients, those would tend toward the process manufacturing categories.

To better understand which type of system would fit your environment, you can consider target industries addressed by different process ERP vendors such as Deacom, CDC Ross, and 3i Infotech. Or review some discrete ERP vendors such as Epicor, SAP, and 3i Infotech. That is by no means an exhaustive list, rather it’s only a few example products, certified in TEC’s knowledge bases.

Notice that 3i is listed in each, in fact other products are also available for both industries. The articles that I mentioned above (and below) mention some of the things to take into consideration from vendors with products that will support either industry. It’s important to consider how these vendors adapt their products to the industry’s needs.

Deploying Lean Principles to ERP Implementation Projects

The competitive environment that both Manufacturers and Distributors alike have experienced in recent years in the era of Globalization, Currency Fluctuation, and Market Pressures has given rise to the business impetus to run a leaner operation to remain competitive. These issues have trickled down to the IT department. IT Professionals are at times facing an enormous obstacle. They are expected to align the organization’s IT infrastructure with the strategic and operational components of the Business to improve upon Service Delivery. The other part of the issue is to reach those goals with fewer resources. Many IT Managers have had to adopt techniques to run a lean IT shop and extend that to the principles of the IT projects that are under development.

An ERP project is an ideal area to utilize lean concepts to further understand how this can be achieved, but we must first understand the basic principles of lean and how they relate to an ERP project implementation.

Lean Definition
Lean Principles have evolved from the Lean Production Philosophy which has its origin in the set of business philosophies developed in post-war Japan known as T.P.S. (Toyota Production Systems)— which has as its core philosophy cost reduction through elimination of waste (muda Japanese).The principles deployed in Lean made Toyota the pre-eminent auto-manufacturer in the world and by extension helped shape Japan into an economic power.

The concepts outlined in Lean Manufacturing evolved into a series of principles which evolved into a business concept known simply as Lean which can be applied across several disciplines i.e. Project Management, IT Deployment, etc.

The Organization known as APICS (American Production Inventory Control Society) has defined Lean as “A Philosophy of Manufacturing based on planned elimination of waste and continuous improvement of productivity.”

How ERP & LEAN Work Together
One of the ways in which ERP & Lean complement one another is in areas such as: Machine Setup Time, labor costs, and materials handling.

During Machine setup, time is lost due to the time the machine operator must setup or take down and change tooling. At other times the employee must spend valuable time looking for tools or preparing for many delays related to machine setups as a result of constant changes to the production schedule at the same work station. One of the core values of Lean Manufacturing is known as the “5S Method.”

* Sort - Eliminate all unnecessary tools, parts, instructions
* Simplify - A place for everything and everything in its place
* Shine - Maintain a tidy and organized work environment
* Standardize - Document the rules for maintaining the first 3S instructions
* Sustain - Operations carried out in sequence, eliminating waste

Execution of the” 5S Principles” meant that resources were planned in ahead, tools were in place and readily accessible, and (where possible) production jobs were scheduled to run in a sequence that minimized machine set-up. When the “5 S Principles” were applied to an ERP environment they looked like this:

* Sort - Use only parts of the ERP system which benefit the company
* Simplify - Use ERP to enable integrated business processes i.e. inventory control
* Shine - Ensure that you work with accurate and timely data
* Standardize - Document and standardize, business processes
* Sustain - Business Processes executed by ERP executed on a consistent and timely basis

The results achieved by the ERP system deployment have resulted in cost reductions and improvements in efficiency meant that work in process has to be managed closely to ensure that no bottlenecks in production occur, The tools within ERP such as Capacity Planning and Costing Modules to define direct vs. indirect labor now mean that only the time the job runs in production are calculated as direct labor.

The efficiencies gained by the ERP implementation produced reduction in set-ups, and other shop floor time management processes, means direct labor costs are also maximized. Through the use of data collection devices, you can account for time spent “on the clock” and nonproductive time spent while a work-order is in queue. This way, non-productive time no longer figures as a basis for calculating direct labor. Finally, as ERP itself evolves with the use of BI tools, along with lean techniques and philosophies such as lean pull-production principles, you will achieve business gains as you introduce JIT (just-in-time), resulting in greater capacity to monitor inventories, manage more efficiently, and align your suppliers to lean-pull production techniques. In the lean ERP model, especially where cellular production techniques in manufacturing are introduced, there is going to be less handling of materials. Once a production job begins on the shop floor, production raw materials flow through the plant rather then sitting idle waiting to be used in Production.

As a result of lean ERP being used in the organization, inventory moves from work station to work station in a continuous flow through the plant—and as a result, return on investment is accomplished through the use of improvement in efficiencies and reduction in inventory investments.

Preparing for Product Development in Process Manufacturing

As seen in such articles as Product Life Cycle Management in Process or Process Manufacturing Software: A Primer, what the process manufacturing industry lacks in glamour, it certainly makes up for in complexity. Traditionally, manufacturing is divided into two categories: process and discrete (if one is not counting hybrid, mixed-mode environments). Many differences exist between the two environments, but most differences can be grouped into one of two areas: 1) those differences derived from material issues, and 2) those differences derived from production issues.

Process manufacturing materials (ingredients and finished products) are different from their discrete counterparts. Process materials are customarily powders, liquids, or gases, which must be confined and which are more difficult to measure accurately. Process manufacturing materials are typically also processed close to their natural sources (e.g., farms, mines, oil wells, etc.). In addition, the materials are of inconsistent quality, which means extensive quality procedures, segregation (lot control), restriction of use (i.e., "this lot is OK for one customer but not for another"), and, usually, the inclusion of quality attributes as part of their inventory definition needs to be implemented.

Process materials can also vary over time. They can get better, they can get worse, and they can even completely change their identity down the track (e.g., owing to the aging process or a limited shelf life). In addition, ingredients often come in a variety of grades and specifications, which can impact the properties of the produced goods. This additional inherent variability leads to both product lifecycle management (PLM) and production or supply chain operations challenges.

It is the differences in production issues between process and discrete environments, however, that reveal the simplest definition of process manufacturing: once one produces the finished product, one cannot distill it back to its basic ingredients. Process materials often involve irreversible mixing, blending, heating, melting, and other operations, while the duration, operating conditions, and sequence of production steps can have a dramatic impact on the yielded material. Has anyone ever attempted to turn orange juice back into its original water, sugar, sodium, and, of course, unpeeled oranges; extract crude oil from derivatives; or extract the pigments out of paint? Conversely, one can disassemble a finished car into its original components, such as tires, spark plugs, axes, chassis, carburetor, and engine block. Thus, where with discrete manufacturing one talks of parts or components, with process manufacturing one speaks of ingredients. Similarly, formulas take the place of bills of materials (BOMs), and convertible units of measure (i.e., pounds, bags, boxes, ounces, and liters) can be related to units.

Thus, food, beverages, chemicals, paints, drugs, and many consumer packaged goods (CPG) are produced quite differently than their discrete counterparts. This is because process manufacturing typically produces products (including coproducts, byproducts, and recurring materials) based on formulas or recipes that detail the ingredients, production steps, and processing parameters, as opposed to on precise BOMs and routing operations, which is typical when making and assembling discrete items.
There are also more subtle differences between the two types of manufacturing. One of these differences is the fact that process manufacturing is scalable. For example, if the formula calls for 1,000 pounds of cake flour, but one only has 500 pounds, one can still bake cakes, just not as many. Conversely, in discrete manufacturing, one missing part means waiting for it to arrive before the finished assembly unit can start rolling off the production line. With process manufacturing, one also tends to make products in bulk or batches, as in a vat of coke or a 500 gallon tank of solvent, and then pack it off to fulfill customer orders. On the other hand, in discrete manufacturing one would expect to see one appliance or car at a time coming down the production line.

The Challenges of Process Manufacturing

For decades, enterprise applications vendors have used technology to automate the business processes that are found in the more straightforward discrete manufacturing setup, where much of the complexity lies in coordinating the great number of widgets that are assembled into computers, minivans, and television sets. The capacity needed to assemble the multitude of intermediate parts and subcomponents into finished goods is a simple function of the number of assemblers brought to the task, which can be increased or decreased according to demand.

Conversely, it is not easy to make changes in process manufacturing. For example, the amounts of chemicals that a plant can produce are fixed by the design characteristics of the tanks and reaction vessels it uses to make them. Adding capacity is a costly endeavor involving months of design work, followed by multimillion dollar construction projects. Disposal of off-spec material is another costly operation, even in cases where the material can be sold to another plant. Rework of unused material is preferable, but requires careful planning so that production of premium-grade products is not adversely affected.

Additionally, unlike with discrete manufacturing, switching from one product to another in a process plant involves significant downtime during which maintenance is performed and vessels and piping are cleansed to prevent product contamination. A classic example is a brewery, which has to mix and brew a variety of product flavors, handling hundreds or thousands of actions involving the complexities of pipes, tanks, and supplies. When one type of beer is being made, the tank being used to produce it is no longer available for other operations. Effective process enterprise resource planning (ERP) software needs to be able to control how long it takes to fill the tank, determine what ingredients will be used, and determine how long the beer needs to brew. Once the brewing is completed, the software must schedule when the beer will be pumped out to be bottled, and arrange for the tank to be cleaned. When one extrapolates from this simple one-product example, one can see that scheduling an entire plant to meet customer demand for a variety of products is too complex a process for ordinary mortals. It requires specialized software with high-level mathematical capabilities.

Product Development for Process-oriented Industries

Product development can also be a challenge for process manufacturers, as product development requirements differ widely between the two styles of manufacturing. Because process PLM systems revolve around recipes and formulas (for more information on what constitutes a full-fledged PLM system, see Critical Components of an E-PLM System and The Many Faces of PLM), and because of the aforementioned variability in ingredient quality, product designers often must experiment with multiple formulations before they achieve the desired result.
Defining and formulating recipe-based, industry-tailored products can be a complex process, involving developing, perfecting, and protecting franchise products, their potential successors, and even the failed prototypes that preceded them. Often, as part of the development process, materials have to be provided to customers free of charge so that the customers can evaluate the product's performance in their process. This back-and-forth between customers and developers may be reiterated multiple times. Thus, many producers are still struggling to balance development and production costs (while factoring in the impact of manufacturing capacity and supply chain speed) against the potential value of a new product.

Furthermore, product development is steadily becoming more about customer service than about mere product and process innovation, involving, for instance, developing unique products for preferred customers. Customers are increasingly demanding services that go far beyond mere delivery and replenishment. This is particularly true when it comes to specialty chemicals, where product development is often more about a one-to-one relationship with the customer and understanding its needs than it is about building a better molecule, since in this industry brands matter much less than in, for example, the retail or automotive sector.

Nevertheless, by combining process industry—oriented PLM capabilities with process manufacturing—oriented ERP ones, it may be possible to produce a unified sample management solution that would allow product samples for evaluation purposes to be delivered in the same manner that commercialized products are delivered. Further combining these PLM systems with process manufacturing—oriented supply chain management (SCM) solutions could provide additional recipe optimization capabilities, such as the evaluation of current inventory to develop least-cost or best-fit product formulations or recipes. Such evaluation would accelerate the new product development and introduction (NPDI) or new product development and launch (NPDL) process, help lower development costs, and shorten time to market for globally compliant products.

This would be particularly helpful in the specialty chemicals sector, where the NPDI process wins more business by recognizing and exploiting customers' needs (e.g., for adhesives, flavoring or scenting agents, polymers, etc.) than by trailblazing a new market with a purely technological innovation. In many chemical companies, but particularly in specialty chemical companies, every order might represent a new product, since it is often sufficient to tweak an existing formula or replace this chemical ingredient with that chemical ingredient. Thus, the faster the time to market and time to volume, the greater advantage these companies have over their peers, and the greater chance of gaining market share.

Regulatory Requirements for Process Manufacturing

Process-oriented industries may also benefit from the recent focus on regulatory management within the product development context, which parallels a general industrial trend toward better management of global regulatory requirements and environmental impact (see Atrion User Conference Highlights Need for Regulatory Compliance in PLM). This is because process manufacturers face different regulatory requirements than their discrete counterparts, which places additional demands on their software. The problem is in addressing compliance in a cost-effective manner. All of the benefits of PLM (including faster introduction of products to markets; reduced product cost; increased product sales; higher product quality; reduced waste; and more valuable product portfolios) can be quickly erased by significant, noncompliance events that impact the company through fines, penalties, negative publicity, or a prohibition on selling a new product in key markets.
In fact, regulatory management is only becoming more important as many regulatory bodies have renewed their focus on product compliance. Because these regulatory requirements vary from industry to industry, as do many other PLM requirements (see PLM Is an Industry Affair—Or Is It?), and because PLM functionality is becoming an essential element of an enterprise application portfolio, industry-specific functionality is increasingly critical to buyers of enterprise applications.

For instance, certain discrete manufacturing sectors are facing new regulatory requirements. Automotive companies, for example, must address the new requirements of the Transportation Recall Enhancement Accountability and Documentation Act (TREAD) in the United States, while electronics and high technology companies in the European Union (EU) must meet the demands of the Waste of Electronic and Electrical Equipment (WEEE) legislation.

On the process manufacturing side, food industry regulations range from developing nutritional and allergen information for product labeling, to the definition of control points to prevent contamination through a hazard analysis and critical control point (HACCP) process. Rising fears over bioterrorism and concerns with product safety and integrity are generating new government regulations that require food and beverage companies to track products throughout their life cycle. This means technology that tracks the original genesis of the food supply is of paramount importance. Thus, government regulations are driving the sector to invest in technologies that synchronize product labeling with formulation systems. For more information, see Process Manufacturing: Industry Specific Requirements Part One: Introduction and Food and Beverage.

The manufacture and use of hazardous chemicals are also governed by strict regulations, especially in North America and the EU. Thus, the chemical industry and companies that rely on chemicals within their plants must address a myriad of regulations, including Restrictions on Hazardous Substance (ROHS) and other regulations that require compositional analysis, the development of material safety data sheets (MSDS), environmental analysis, and hazards identification. The chemical industry must also deal with the impact of European Classification and Labeling Inspections of Preparations, including Safety Data Sheets (ECLIPS); Registration, Evaluation and Authorization of Chemicals (REACH); Science, Children, Awareness, Legislation, and Evaluation (SCALE); and Global Harmonized System for the Classification and Labeling of Chemicals (GHS). For more information, see Process Manufacturing: Industry Specific Requirements; Part Two: Chemical.

But it is the life science and pharmaceutical manufacturers that face possibly the toughest restrictions of all, requiring strict adherence to good manufacturing practices as well as to comprehensive and highly enforced Food and Drug Administration (FDA) regulations. Implementing and ensuring compliance with employee safety guidelines, possible food contact rules, monitoring emissions (which are often delineated by regulatory permits), and even validating the origin and composition of products are all mission-critical processes that contribute to the cost of doing business.

For such manufacturers, a further layer of complexity is added by the introduction of hazardous materials and dangerous goods that are closely regulated and must be reported. Software can greatly simplify this in two ways. First, when creating a new formula or modifying an existing one, that formula must be analyzed for the presence of hazardous materials. Performing this check requires a continuously updated and current list of regulated materials that are considered hazardous. It also requires knowledge of the percentage of these materials relative to the other ingredients.

Secondly, the reporting of hazardous materials must comply with a specific format, namely MSDS. These MSDS will usually accompany the customer's bill of lading (BOL), and therefore must be integrated with the billing process. While copies of MSDS can be kept on file and manually matched with the BOL, most companies will not want to risk noncompliance and would rather seek an automated remedy. Likewise, most companies will not want to rely on manual procedures to determine when a formula or product requires an updated MSDS. Instead, these companies will seek to have update notification incorporated into their enterprise-wide software, in order to automatically generate new MSDSs when needed. Thus, it is apparent that programming hazardous material compliance is not a trivial matter, particularly when one considers that it involves list processing and matching, percent of total analysis, scheduling, and formatting.

Why Managing BOM Is Such a Big Task

In the discrete manufacturing sector, the bill of materials (BOM) is a fundamental piece of product data that exists throughout the major stages of a product’s life cycle. According to Wikipedia, BOM is the term used to describe the raw materials, parts, subcomponents, and components needed to manufacture a finished product. Simply speaking, BOM is just a list of all materials needed to be assembled together into a product. The concept is clear and simple, and it doesn’t seem to be a difficult task to manage BOM, especially when we have a powerful tool—software—in hand. However, this is true only when the product structure is so simple that not much collaboration is needed to develop the product, when consumers are delighted to have the same products that everyone else has, and when design, engineering, and production are performed under the same roof. The truth is, during the past few decades, the landscape of the manufacturing sector has changed dramatically, and it is still changing at a rapid pace.

Collaborative Product Development

As time moves on, products become not only more complicated in structure, but also impossible to develop exclusively by a single department. In fact, developing a product is now a corporate-wide activity that involves almost every function of a company, from strategic planning, to sales and marketing, to after-sales services.

To see how things get more complicated, we don’t even need to look at all the participants. Let’s stay with three functions—product design, engineering design, and production—for a while. At the time when the product design department finishes its work, a design BOM will be generated. Ideally, this BOM will be carried throughout subsequent processes. However, this is not very likely to happen. For example, a single part created by product design team might be modified into two parts by the engineering design team for the feasibility of production; when the production team receives the production order, it might decide to use another material (which also meets the requirements) to produce the parts, since there is a large amount of this material in the stock due to a cancelled order.

The differences among the design BOM, engineering BOM, and production BOM create inconsistency of product data along the product’s life cycle, and sometimes increase product cost and time-to-market. Besides these three types of BOM, there are also customer BOM, sales BOM, maintenance BOM, cost BOM, etc., all used for different purposes, making things even more complicated. One way to resolve this problem is to bridge the information gaps on a constant basis under the change management mechanism, which is a fundamental functionality within the product lifecycle management (PLM) solution.

Mass Customization

To meet the increasing demands of consumers that want more personalized products without significant increases in price, many manufacturers now practice mass customization of products ranging from automobiles to computers—even apparel. Modular BOM is one of the enablers for mass customization. It defines the components needed to produce a subassembly, and provides cost information for each component and “rolled-up” cost for the overall subassembly. Nowadays, one product may many configurations. If computer systems store each possible configuration as an independent BOM, BOM maintenance becomes almost impossible.

Configurable BOM is another enabler for mass customization. By using this BOM, buyers and manufacturers can create “end-items” dynamically. Based on this configurability, Quote-to-order (Q2O) solutions (sometimes known as configure, price, and quote, or CPQ) enable manufacturers to mobilize their mass customization initiatives. These systems can reduce time-consuming quoting and ordering processes, decrease unit costs, and lower sales costs.

Global Manufacturing and Consumption

Another significant shift in the manufacturing industry is that product development and production have been widely distributed. It’s not a surprise to find “Designed by Apple in California. Assembled in China” on the back of an iPod owned by a 16-year-old boy in Spain. Production offshoring and global marketing give companies opportunities to cut costs and to reach more consumers, but these activities also require more collaboration with up- and down-stream partners. Product data transparency between a manufacturer and its suppliers (or in other words, consistent BOM information throughout its supply chain) becomes an important issue when companies want less expensive production resources but still need to keep up with the pace of shortening time-to-market. In an old-fashioned way, an engineering change that reflects material changes may reach suppliers in days. Not to say that suppliers may also have a few layers of suppliers.

Consistent BOM throughout the whole supply chain relies on integration. First of all, internal integration ties all the information systems running within an organization (PDM/PLM, ERP, SCM, etc.) that rely on accurate BOM data. This integration allows companies to have effective and consistent product information any time it is needed. Secondly, external integration connects all parties on the value chain. Based on electronic data interchange (EDI) or other means of data exchange, external integration allows enterprises to have a common view of the product structure and other critical data, so companies can collaborate across organizational borders.

As many managers have reported, BOM management has become a sometimes cumbersome task for organizations, and inaccuracy or inconsistency of BOM has cost companies a lot. In fact, BOM management is one of the critical factors that lead to the adoption of PLM systems. PLM is the best solution so far to bridge different stages of a product’s life cycle. With appropriate integration, PLM captures and records any changes that impact BOM and other important product information, and provides up-to-date product data whenever needed.

Lawson Standing Vertically in a Flat Economy

Lawson Software has hardly ever been associated with flamboyance and ostentatious behavior, let alone in these murky economic times. Still, its chief executive officer’s (CEO’s) recent dismissal of the software as a service (SaaS) market’s prospects will have drawn some consternation in the vendors’ and analysts’ community. However, a somewhat amended and clarified stance on SaaS recently came from Lawson’s senior vice president (SVP) of product development and strategy, Dean Hager.

Like the vast majority of enterprise applications vendors, Lawson concedes the tough economic milieu, which was recognized in its sloppy fiscal Q109 performance. Prospective customers are simply slowing down the “looking and decision-making” process, and also the negotiations are admittedly much more involved. The enterprise resource planning (ERP) vendors’ competition is getting dirtier, with everyone fighting very hard over what looks like fewer deals.

Still (at least not yet), Lawson has not given the impression of despair or panic, despite recent cost-cutting (read: layoffs) measures. Such measures appear to be in line with the economic climate and the measures of other peer companies.

In fact, every now and then I will still see some PR announcement about Lawson’s latest win of a new customer. The vendor dedicates about 80 percent of its efforts and resources to the following strategic verticals: apparel/fashion, food & beverage (F&B), multi-channel distribution (those with retail elements like building materials), ESM or equipment service management (e.g., Caterpillar dealers), healthcare, and the public sector. The relatively recession-proof sectors that are doing well even in this climate are ESM, fashion, and healthcare.

What About Food and Beverage?

As someone smart once said, “People have to eat and drink in both good and bad times”, so the F&B sector should not be that badly affected by the downturn. Sure, the premium brand manufacturers will likely suffer, but the low-price and private label items might even flourish.

In late October, Lawson made two announcements at the InterBev 2008 Conference and Exhibition in Las Vegas, Nevada (NV), United States (US). This was the validation of Lawson’s vertical strategy that was professed at its CUE 2008 user conference, and was soon delivered with the Lawson Tracer product. These industry-specific modules all have features that are unique to the F&B industry or are solving that industry’s specific business requirements.

Industry-specific Analytics

The Lawson M3 Analytics for Food & Beverage module helps F&B companies access meaningful business intelligence (BI) to improve decision-making without having to painstakingly develop analytics tools in-house. In fact, industry-specific BI solutions that can be up and running to provide value within days and weeks are Lawson’s attempt to mitigate the current economic crisis for its customers.

Thus the Lawson M3 Analytics for Food & Beverage application includes 70 pre-configured key performance indicators (KPIs) and 50 pre-built scorecard reports commonly used by F&B companies. Sample KPIs include day sales outstanding (DSO), inventory turnover, delivery performance, and gross margin percentage. Sample scorecards highlight critical data such as sales vs. budget, supplier performance, production variances, and customer debt.

This selection of metrics is engineered to meet the specific needs of an F&B company management. It includes what the executives and middle managers need, and does not include KPIs that are meaningless (which is of course the case with a more generic, “one size fits all” approach). The analytics set also includes KPIs not seen in other industries, like yield. Such a comprehensive approach to business evaluation has been essentially beyond the reach of all but the largest F&B companies until now.

Lawson Analytics for Food & Beverage helps F&B companies benchmark, measure, and improve performance in the following five key areas: sales, finance, procurement, production and the warehouse. With virtually all manufacturers currently concerned with burning cash, they need their existing systems to deliver more value faster, specifically in terms of improving cash flow and slashing costs. Lawson’s industry-specific analytics should help provide answers to those critical questions such as “what and where are our inefficiencies?”, “where are we losing cash?”, or “which processes are slow?”

The application enables tracking of multiple performance metrics by individual products, customers, and account managers to help decision-makers identify underperforming operational areas in time to take appropriate action. It also helps F&B companies eliminate unnecessary reports so decision-makers receive only the right information at the right time.

Industry-specific Planning Tools

In a related announcement, Lawson also announced the availability of Lawson Stock Build Optimizer and Lawson Planning Workbench for Food and Beverage. These new applications aim to help F&B manufacturers improve long- and mid-range production planning to ensure that the right amount of the right products are available at the right time to meet seasonal and promotional peaks in demand. F&B companies traditionally have to choose the lesser of two evils:

1. Losing sales if they don’t produce enough products to meet demand spikes, or
2. Writing off perishable products if they produce too much.

Lawson Stock Build Optimizer helps companies visualize their overall plan for building and maintaining an inventory of finished products. The F&B industry has two relatively unique requirements: it is deal- or promotion-driven with both customers and F&B manufacturers having a history of impacting the timing of transactions based upon promotions. This module allows the supply chain to be leveled to eliminate problems in timing. Stocks need to be built up in advance of the promotion period, stock-outs need to be eliminated, and inventory investments minimized.

Lawson Stock Build Optimizer then offers tools that allow manufacturers to perform multiple “what if” scenarios to simulate the consequences of different long-range planning decisions. These models, which can account for a wide range of variables from production capacity to ingredient costs, help planners refine master production schedules (MPS) across multiple manufacturing sites. For example, planners can use these models to evaluate the benefits of building stock in advance to support demand spikes, versus using overtime or subcontractors to meet seasonal demand for products such as holiday chocolate assortments.

For its part, Lawson Planning Workbench for Food and Beverage should help F&B manufacturers improve mid-range planning decisions as they balance changes in demand and supply availability during production. Companies can visualize their total coverage days for each product to guide production planning decisions for the next few weeks or months.

The application then captures and provides a full view of production variables, such as changes in customer orders, delivery schedules, employee shifts, and aging inventory. This allows planners to conduct “what if” modeling before deciding how to prioritize production for specific products and orders to help avoid stock-outs, inventory write-offs, or the need to temporarily open additional production lines.

Both Lawson Stock Build Optimizer and Lawson Planning Workbench for Food and Beverage are configurable to users’ specific needs. Both applications also offer simplified installation and support through integration with the Lawson M3 Enterprise Management System [evaluate this product].

Dear readers, what do you think? Is this a well thought-out value proposition from a vendor to help its F&B customers during bleak times or merely a vendor’s repackaging exercise to cash in on the current economic crisis? Should virtually all vendors try to come up with similar industry-specific initiatives and thus justify their existence and customers’ investment and trust?

What are your opinions about whether these new products will help F&B manufacturers analyze an increasingly complex set of supply chain variables to help them optimize production plans, lower inventory costs, and enhance customer service? What steps are you taking in these regards?

For an exhaustive analysis if the needs of F&B companies see TEC’s earlier series of articles entitled “Food and Beverage “Delights.”

Processing Complex Events (During These, oh well, Complex Times) – Part II

Part I of this blog series introduced the concept of complex event processing (CEP) and possible needs for CEP software applications. One such broad CEP platform, Progress Apama, has been offered by Progress Software Coporation after acquiring the formerly independent Apama LTD in 2005. It is worth analyzing what has happened with the Apama product since being acquired by Progress Software.

Progress Apama’s Current State of Affairs

For one, Apama revenues have increased multiple times (e.g., 70 percent growth in fiscal 2008). This growth probably makes Progress the market share leader in the CEP market, together with the fact that Progress Apama currently has approximately 110 customer deployments.

A sampling of Apama customers, those that Progress has publicly announced, can be found at the company’s website here. The product’s “sweet spot” and leading presence to date has been in the Capital Markets and Financial Services segments for high frequency trading applications. Apama’s customer profiles range from the largest sell-side firms in the world to smaller, boutique buy-side firms.

Furthermore, Progress Apama now has a worldwide footprint, with deployments in North and South America, throughout Europe, the Middle East, Australia, Japan, and Korea. The product now logically supports some internationalization capabilities. Last but not least (and to be detailed later) Apama has expanded in capability with more CEP functionality, sophisticated development tools, flexible event capture and replay, visual dashboards, and open integration framework, while emphasizing less on just promoting the product’s high performance and scalability (e.g., sub-millisecond latency for thousands of scenarios) traits.

Progress Apama customers are generally distinguished by a desire to leverage the product’s rapid application development (RAD) tools to build unique trading or trading-related applications that allow them to incorporate their own business logic, rather than packaged, off-the-shelf applications. While the company’s early market adoption has been in capital markets, Progress Apama has also established penetration outside financial sectors in other event-driven environments.

Other sectors are telecommunications, supply chain/logistics, energy grid monitoring, manufacturing process monitoring, retail banking fraud detection, entertainment (i.e., gaming surveillance), and other areas. For example, when it comes to telecommunication providers’ revenue assurance, a CEP platform could monitor the billing of several million subscribers across multimedia channels (i.e., voice/video, data, content, and unlimited multimedia messaging service [UMMS]), to prevent revenue loss in real-time.

Real-life and Prospective CEP Deployments Outside Capital Markets

At Progress Software’s Analyst Summit 2009, there was a case study presentation about Apama empowering advanced international logistics in terms of shipping and ports management. The customer is Royal Dirkzwager, which since its founding in 1872 has developed into the maritime information and service provider for Northwest Europe, with a strong focus on the Port of Rotterdam.

Dirkzwager deals with vast information on vessels’ characteristics, ship’s position reports, and ever-varying estimated times of arrival (ETAs) and actual times of arrival (ATAs). From about 200 position reports per second 10 years ago or so, today the company has to deal with over 1,000 position reports per second. Dirkzwager’s public sector customers are the related port authorities, port state control, customs, seaport police, and coast guard. Private sector customers are ship owners and agents, terminals, and service providers (pilots, tugs, maintenance crews, etc.).

One of the business issues for the company has been to integrate berth planning for terminals and employee planning for authorities and service providers into its customers’ business processes. Another issue for Dirkzwager has been the globalization of customers and its geographical coverage expansion.

Namely, from customarily focusing on Rotterdam, the company intends to focus on northwest Europe and, albeit to a much lesser extent, on a worldwide coverage. Last but not least, harnessing electronic position information tools such as AIS (Automatic Identification System) and LRIT (Long Range Identification & Tracking) has become much more important.

Dirkzwager reportedly implemented Apama due to its capability to handle different position report types and to handle large amounts of position reports (i.e., scalability). Also, the company’s employees can now create and modify business rules for the port’s operation. As for future directions, the port operator company expects to enable customers to create own business rules, and to also be able to process port related messages such as route advice and monitoring. The latter capability should result in a reduced overall fuel consumption and improved port arrival planning.

Monitoring Manufacturing Processes, Catching Crooks and Other Bad Guys…

Given Progress’ traditional approach to leverage partners to embed and sell its products, we should note that to this point Apama sales have been based mostly on a direct sales model. To date, sales have been primarily to banks and other larger companies in financial services, where CEP is deemed as a “bet the farm” solution. Sales into governments, telecommunications, utilities, transportation enterprises and so on will also likely target major enterprises. These operations will require a continued expansion of a direct sales channel as well as partner-based channels for smaller organizations.

One good example of a partner embedding Apama would be Manuvis within its FactoryMRI manufacturing execution system (MES). Manuvis’ system continuously monitors production equipment and other key production statistics in a discrete manufacturing environment (e.g., production of auto parts). Should the software detect a continuing anomaly in a machine, it will notify workers to tend to the machine. The software will also dynamically re-direct production and re-optimize the production schedule.

Generally speaking, CEP tools can link directly into data collection and automation systems sending signals from the production floor, as well as into packaging, warehousing management systems (WMS), and other related business systems to guide problem resolution and improvement. Another example of Apama’s use in the production environment is to detect bottle-filling trending low or high in a large high-speed bottling plant.

By defining threshold and time window limits, the system provides alarms and dashboard visibility on the fly, as well as comparisons over any period in history. Data input can be sensor outputs, control instructions, transactions and so forth, while connection taps can be made into programmable logic controller (PLC) and control system data streams, as necessary.

Progress has been working with several international regulators, including the UK’s Financial Services Authority (FSA, which is the counterpart of the US Securities & Exchange Commission [SEC]), to incorporate real-time fraud detection technologies into its market monitoring endeavors to help detect fraud. One of the drivers for FSA’s SABRE II (Surveillance and Automated Business Reporting Engine) fraud-detecting initiative was for the regulatory authority to become more dynamic and proactive in detecting market abuse. This proactive approach would be achieved by investigating potential offenders more quickly with relevant evidence, and by identifying trading rings and links between individuals generating illicit market impressions.

The idea was to also instantly detect and prosecute “extremely lucky” individuals (e.g., traders who constantly take a best offer in a market to drive up a share price) and monitor for price/volume movements where companies may need to make a disclosure of price sensitive information. The other drive was to implement all requirements for the Markets in Financial Instruments Directive (MiFID) in terms of transactions reports, policy calculations, and inter-regulatory reporting.

There are hundreds of known and possible illegal trading patterns (tricks), but traditional algorithmic techniques have not been able to detect their use in real time. Thus, Progress Apama is used to promptly detect insider trading, breaches of short-selling rules, wash trading, the spreading of illegal rumors followed by suspicious buying patterns, “painting the tape” to drive a stock’s price up, front-running of orders, and trader collusion (with insider knowledge and “agendas” to buy across different trading venues), as well as many other common market abuses.

The point here is to detect fraud while it is occurring (not after the fact), so that regulators can detect market manipulation that is in breach of regulations in a timely manner. Hence, before a trade is placed, real-time rules should detect both illicit doings and honest mistakes (like so-called “fat-finger” errors or decimal points in the wrong places), apply real-time compliance rules, or make sure the firm is not over a certain percentile of an actively traded market.

Given the need for in-depth know-how and domain expertise, Progress has teamed up with specialist consultancy Detica Group PLC (now part of BAE Systems) to encode market knowledge into algorithms that detect illegal trading patterns. Other possible examples of Apama deployments could be: the detection and prevention of credit card fraud (e.g., detecting several same-number credit card transactions at physically distant retail stores in an atypical time bracket); analyzing patterns in passenger movements (e.g., to detect potential terrorists); aviation control; and predicting the best route for vehicles such as tanks and long-haul transport.

More on Apama’s Life Under Progress Software

Beyond the original acquisition of Apama by Progress Software, there have been no further CEP products acquisitions. As part of Progress Software, however, Apama has expanded its product capabilities with enhanced visual dashboard technology, which involves the RTView technology that is provided via an original equipment manufacturer (OEM) relationship with SL.

Apama has also meanwhile gained backtesting analysis capabilities, by leveraging integration of other technology from Progress–ObjectStore. This object-oriented database is used in the Apama product as Apama EventStore, a time series database that can capture event streams (such as market data and trade execution calculations/decisions), making that data available for replay. This “TIVo”-like effect of a sort uses an application within Apama called Research Studio.

For example, as the radio frequency identification (RFID) system continuously reads each tag, Boekhandels Groep Nederland’s (BGN) Selexyz retail bookstores use Progress Apama to filter out duplicate reads from incoming streams and ensure that every book is counted just once. Duplication is also prevented by reconciling the advanced shipping notice (ASN) data streams coming from the distributor.

The third and final part of this blog series will conclude with Progress Apama’s differentiating traits, future roadmap, and competitive landscape. The post will also discuss what more CEP is capable of and what it is not capable of.