Data processing, 1959. Image by James Vaughan, CC license

If you search “technologies for supply chain evolution” you will get 17.8 million results, many of which will mention IoT, robots, driverless vehicles, mobile technology, predictive analytics, network optimization software, and 3-D printing.

The presumption is that industry will want these solutions because of the coming added complexity and demands of the modern supply chain in the digital age.

But most supply chains still confront very basic problems and inefficiencies; they haven’t in many cases even fully deployed yesterday’s technology, so delivering product with drones doesn’t make the priority list.

So which technologies are key to the supply chain of the future? The same ones that were introduced 15 years ago that companies still haven’t adopted! This is unfortunate, because many of these technologies were designed to automate the supply chain office, and without automating the supply chain office, all of that promising talent you are committed to developing is typing away at tedium.

Just visit your customer service department, where very smart and capable humans – some with $120,000 college degrees — are reading data from pieces of paper and entering them into systems, an act which, according to supply chain technology gurus, should have disappeared years ago with the introduction of EDI, integrated systems, and OCR.

Supply chain managers are managing minutiae, not the supply chain.

Where does the minutiae come from? From the 18,000 to 30,000 phone calls or emails and the 120,000 to 350,000 manual interventions a typical ($2 billion +) company must make just to ensure proper system processing of its order-to-cash flow. And this is with all the normal ERP and associated technologies, such as EDI, that a company of that size normally uses.

Companies still have teams of people shuttling information and data all over the supply chain office, and because they are busy shuttling information they don’t have time to look at it to make sense of it and use it to improve your business.

Automating the supply chain office is one of the cheaper technology moves you could make. The EDI and OCR of the 1980s has gotten better and easier to deploy, and when strung together with complimenting technologies, can automate nearly all of your order processing, exceptions management, invoice discrepancies and customer claims work.

Automation also has the enormous benefit of – by definition – digitizing every piece of data from every transaction. If all of your shipping and invoice claims are scanned, stored, and sent to transactional systems for disposition, all that data is available to study for patterns, relationships, and other insights that can mean immediate savings. Like getting a view of the forest.

Want to evolve? Make the supply chain office run itself. For a $2 billion company selling to major retail outlets in the US, this means zero human intervention for every one of 60,000 deliveries a company of that size is likely to make. Most business rules are simple to automate: if X order received, send to Y location and reply Z back to customer.

A truly evolved supply chain office is one where all human assets are users of data, not movers of data, creators of opportunity based on a view of the forest, and customer relationship builders.

Image: Loaded container ship in the Houston Ship Channel, by Louis Vest, CC license

There’s a debate going on in B2B commerce about “touchless” sales order processing. Touchless just means you don’t need a human to watch, review, check, or do anything else to an order when it’s received from the customer, like making sure product codes and pricing are correct.

On the one side are touchless believers and on the other, advocates of automated checks plus a quick review by human eyes, called “click and go.”

Many companies have already achieved touchless order processing on a very high percentage of their order volume, and you need to look no further than Amazon for a very simple example of completely automated order processing. On any given Saturday morning, you, along with thousands of others, made a one-click purchase on Amazon. That order made its way to a fulfilment center uninterrupted by human scanning because of software.

Getting there is not hard.

Touchless order processing in a B2B environment is best achieved with the right combination of order capture method and algorithmic checks based on your company’s business rules.

The key aspect of order capture is simple readability – a structured, typed form or an electronic form filled out via an internet portal, or the standard EDI purchase order.

Algorithmic checks can be written for just about anything – if customer order date is X, then send order to Y. Many companies, realizing they need these kinds of checks, start building them in their ERP systems using custom code.

But before long the DIY route can mean expensive software modifications as companies seek to automate more and more of their inbound order processing steps. I know of one company whose order checks are so complex that some of their large customer orders can take up to several hours to process.

It is much better, in my view, to outsource the order check process by streaming your orders through a 3^rd party-hosted application. This allows almost unlimited creativity in order check logic because you don’t have to wrestle with your ERP code.

You can also buy packaged software to do order checks, but why would you want to license more expensive software, hire and train people to maintain it, buy a server for it to run on, and manage all the future modifications, upgrades, and integrations with your ERP system? If you’re thinking about using EDI services companies for this function, don’t. Outsourced EDI wasn’t built for this type of work.

While “click and go” may be suitable for a small universe of customers, adopting this method for all orders defeats the purpose of automation, which is in the end freeing up supply chain talent for more valuable work.

Maybe software should be packaged like this?  Photo: Tetra Pak Package Portfolio, by Tetra Pak, CC license

A “packaged application” is software already built, coded, tested, used by other enterprises in your industry, and hopefully a solution that will meet most of your needs.  In general I recommend using packaged applications (why re-invent something?)

But a packaged application is not ready-to-use, in any sense of the word. The word “packaged” is kind of a misnomer. You won’t find a warehouse management system in a shrink-wrapped box on the shelf at Best Buy. A packaged application is simply one whose features and functions match in general terms what you want the software to do, but which still needs to be configured for your business. Configuration (also called setup) involves a lot of work and expense.

Much of the time involved in configuration is not in setting up all the data and parameters, but in deciding what data and parameters to set up. What data do you want to/have to set up for each customer? Should employees be “suppliers,” so that you can reimburse them for travel expenses? Do you want to manage your inventory levels according to min/max parameters or days on hand, or some other way? In most enterprises, decisions like these aren’t made by one person – groups of people get involved, and all those meetings and explanations have to be scheduled, and someone has to herd everyone into a decision. Not a quick process.

Packaged software is an annuity business. A software company survives in the long run because it is able to collect annual maintenance and support fees from its customers while providing custom development services and a stream of version upgrades. The support fees can be 20% to 25% of the original cost of the software license, so to the software firm, it’s like selling a new system to the same customer every four or five years. In exchange for the fees, the customer gets access to support desks, can have the software firm make modifications to the system usually on a time-and-materials basis, and automatically gets some upgrades and patches (or fixes) as well as user guides and maybe some technical documentation.

Recurring support revenue is highly profitable for vendors selling packaged applications. It is not unusual for big packaged software vendors like SAP, Oracle, and JDA to have this type of revenue represent 60+% of its sales while incurring only 5% or 10% of its operating expenses.

If you are selecting a packaged application, understand that your vendor will try to sell you the traditional on-premise solution, in which you will own and host the software while paying the vendor for additional licenses, upgrades and custom developments, plus the annual maintenance fees of 20% to 25% of the original license cost, which, on a license costing $500,000, for example, would be $100,000 to $125,000 per year.

And therein lies one of the most debated and disruptive topics in the software market today: the move away from the traditional on-premise (also referred to as perpetual license) model to a service or subscription-based model.  It is not exaggerating to say that the perpetual license model has in a way been the drug, the stream of highly profitable revenue, sustaining the software industry the past two decades.  Stay tuned.

All your apps are in the cloud(s) now.  It’s OK.  Photo: Paul VanDerWerf, Potts Harbour, Hartswell, ME.  CC license. 

Hyperscale computing (HC) may sound like something only NASA and Google need.  But any business doing any kind of commerce with web sites can potentially benefit, as can brick and mortar companies who are highly dependent on 24 x 7 x 365 operations and no longer want to buy and maintain servers.

Hyperscale computing is computer processing power and storage that can be scaled up or down instantly, in large amounts.  Hyperscale computing relies on distributing computer tasks to multiple servers (distributed computing). You could do this on your own, duplicating your server environment and buying extra servers and the software needed to distribute tasks, but all of this is already available in the cloud, by many reputable firms, at costs that are not only low but predicted to go lower.

Why should you care?  Here are two scenarios where you might benefit:

1. Your product is sold at brick and mortar stores as well as your own web site.  Your retail customers (stores) use your primary site to place orders and as a selling tool in their stores.  You frequently promote your products to generate sales, so traffic and transactions on your site fluctuate a lot.  In this case you have to manage high traffic in a high- responsive way, and you need alternatives for backup if your primary servers fail.  Again, you can manage the hardware physically, but the most efficient way will be to virtualize your servers with scaleability built in, which is the whole purpose of hyperscale computing.
2. You don’t sell a thing online but your 24 x 7 x 365 operation is highly dependent on e-commerce with other companies and your own ERP system, the hardware for which is hosted by you or by an external company. Most companies have redundancy backup internally, or they make sure that apps or services they use are hosted by firms that also have redundancy backup.  But what if your vendor has the traditional one or two server backup, and one or both of those fail?  As companies more and more adopt SaaS for applications solutions, they can’t just assume that their SaaS vendor has adequate backup/scale-up capability.

Think of it this way, in simple terms: what you used to think of as big computers in some refrigerated room running all your stuff is now available online, not only in the quantity that you want, but with much more capacity and speed and at much lower cost; but more importantly agile enough to expand instantly as needed, or failover automatically — both data and software — to a redundant environment in cases of disaster, virus, or overload.

Image: Nash assembly line, 1951, by Alden Jewell, CC license

Maintenance and maintenance parts are two other manufacturing sub-categories where the software market offers several competitive alternatives. This category is referred to as CMMS, or Computerized Maintenance Management Systems. These systems keep track of maintenance schedules for equipment, tell you when parts have to be ordered, manage vendor contacts and accounts, manage your parts inventory, and integrate to your financial systems to record parts expense and value of the parts on the balance sheet.

Like many software categories, parts and maintenance management has vendors that range from the big players to firms that offer free downloads and desktop versions. SAP, Oracle, and JD Edwards all have established offerings in this category.

Here, my advice is to select something close to home; meaning a vendor who is either your ERP vendor or a well-known and established software company. The reason is that maintenance is usually a non-critical function, and doesn’t warrant a lot of integration and customization work. It’s possible to get by for years using spreadsheets or vendor catalogs or other tools.

The ROI for this type of application usually comes from saving administrative time in keeping track of maintenance schedules and keying purchase orders and receipts for parts into your financial or ERP system. Manufacturing applications are no different from other software in that they need data to deliver the benefits they offer. That means someone has to key this data in, unless the software is getting data from a connection to another application.

Purchase orders, part numbers, receipts, parts usage, and lots of other data have to be entered or uploaded into a maintenance management application. This is one of the downfalls of software, not unique to manufacturing applications but maybe more prevalent in that category because the manufacturing floor is not the place you normally have the people who enter data: the quality, accuracy, and timeliness of the software’s output is directly correlated to the quality, accuracy, and timeliness of the data going into the application.

A maintenance management or parts management application will also change your internal ways of working. The software can’t read your mind; it only knows what you tell it. If your work force is sloppy about entering data or about workflow procedures like scanning parts into and out of the system, you won’t get much but headaches from the application.

Photo: Ministry of Information, Singapore; William Cho

The term “enterprise information management” seems to capture the whole world, right? But this term applies to the indexing, searching and compilation of information (not necessarily data) from all of the places in your enterprise where documents might reside.

Gartner defines EIM as “an integrative discipline for structuring, describing and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insight.”

It’s hard to tell where document/information management leaves off and (data or information) analytics begins. This is part of the mashing up of software functionality that is going on in the market today.

Information is everywhere – in emails, presentations, documents stored on a company’s server, individual user hard drives, servers in the cloud, etc. So traditional search software is somewhat ineffective, because it expects data or documents to be neatly organized inside a box where it can simply sort through data and return matches to your query.

Modern enterprise information management (EIM) software is different because it can search multiple and geographically and systematically separate sources according to terms defined by the user. It does this usually through a web browser.

The market for these tools arose because companies generated tons of documents without any “filing” standards, other than placing them on a corporate shared drive or on people’s PC hard drives. As a result, it was almost impossible to assemble all documents within a company’s four walls related to a particular customer, vendor, product, project, formula or activity. The ability to perform this type of search is especially important to legal professionals, who must respond to government inquiries or parties involved in litigation. This type of search is referred to as e-discovery.

Just a few years ago, I worked on a project like this, except it was referred to at that time as a records retention project, and we installed software from vendor L. The software was basically a search tool for the company’s numerous internal file directories, and required the indexing of every file according to pre-established criteria, and the establishment of a document hierarchy and permission levels. It also assumed that all of the company’s 1,200 employees would store all of their documents on the company’s shared drives, and no longer use their PC hard drives to store files (this was not realistic).

Today, the company that used vendor L is implementing a different system that is capable of locating files anywhere within the company’s network – shared drives, hard drives, emails. In less than 24 months, software that cost over $1 million to implement was rendered obsolete.

EIM usually includes e-discovery tools, and tools for managing content or knowledge, such as user guides, formulas, troubleshooting guides, business process steps or standard operating procedures, system diagrams, and documents critical to retaining official records.

Clearwell Systems, acquired in 2011 by Symantec, is a leader in the e-discovery field. Symantec also offers other EIM solutions. The Symantec web site says this about the Clearwell e-discovery application: “The Clearwell eDiscovery Platform, nominated as a Leader in Gartner’s 2012 Magic Quadrant for eDiscovery, provides users with one seamless application to automate the legal hold process, collect data in a forensically sound manner, cull-down down data by up to 90%, and reduce review costs by up to 98% through the use of Transparent Predictive Coding.”

My advice with this type of software is 1) like any software, garbage in = garbage out, so make it easy for users to do what they need to do for compliance; otherwise users will invent ways to work around your application, not use it; 2) whatever you are archiving must be important so put it in a secure environment with a redundant backup; and 3) as soon as you index, categorize, and digitize your enterprise information you will think of new ways of using it so pick a vendor with a wide range of services and solutions.

Photo by Meredith Cook at Breckenridge, CO on a “blue bird” day, a clear day following a fresh snowfall.  It’s unrelated to SaaS or Cloud (or is it?); just nice to look at.

SaaS and cloud are starting to be used interchangeably (“we’re looking for a cloud solution”) but they really are not the same thing.

Software-as-a-Service (SaaS) is: software that is made available for use based on access to features, time, number of transactions, number of users, or a combination of variables.  A ‘cloud’ is simply a server – a computer you don’t own or maintain – that sits somewhere other than in your building, that you access to run applications or store data.

SaaS describes a type of software, cloud describes a type of platform.

So you can see it’s possible to take applications that you own, and put them in ‘the cloud,’ and also possible to use software you don’t own, but pay for based on usage, that is sitting in your data center with all your other applications.

But there are more important distinctions.

Type of Software-as-a-Service: Is it software that only you access (single tenant), or is it an application that many other people or companies use (multi-tenant)?  Multi-tenant is generally lower cost, but with less specialized functions for your particular enterprise.  Is it truly SaaS, or just a full cost, configured-for-you application hosted by someone else whose costs have been spread out monthly over 5 years to look like a SaaS solution?  True SaaS works like a subscription: sign up, pay by month and use it; when you no longer need it, you cancel.

Type of Cloud: Is it a private or public cloud, or a hybrid?  A private cloud is a single tenant environment (your enterprise) where you control access and have firewalls for security and where you can define the hardware.  A public cloud is where you are paying for a part of an existing cloud server environment; here, you “rent” space and the advantage is flexibility, low cost, and the ability to scale capacity up or down based on your needs.  Hybrid clouds offer both private and public spaces for you to use.

Let’s look at examples; in both cases we will use the scenario of a manufacturing company selling to major retailers in the U.S. and Canada.

True SaaS:  You contract with a company that offers tools for analytics (software) together with point-of-sale (POS) data for your products for your largest retail customers.  You pay by month to access and analyze POS data. The costs vary depending on how many report levels you want to see.  You access the application via internet, anyone in your company can use the service, and you can cancel at any time.

True Cloud: For purposes of experimenting with business intelligence applications, you purchase database space from a vendor, at a cost that varies depending on how much space you use.  You can scale up or down in terms of the storage you need.  You can connect to this space with a variety of tools for transporting  data and you can install and remove applications easily.  For running your business day to day, you can host your most critical applications in this cloud, and have in reserve an identical cloud with servers ready to take over in cases of disaster or over-capacity of your main servers.

Before you accept at face value the terms ‘cloud’ or ‘SaaS,’ make sure you understand what the vendor is telling you. Ask for details and explanations.  What the vendor thinks is cloud or SaaS can certainly be different from what you expect.

Image: Coors Brewery, Golden Colorado, by David Fulmer, CC license

The job of manufacturing software in the modern economy is to keep track of production formulas, in terms of quantities and cost, enable production scheduling, calculate and report on efficiency measurements like machine utilization and percentage of wasted materials, and in some cases measure cost of goods sold.

These systems are usually linked to the core financial system. Subcategories include software to manage preventive maintenance schedules, spare parts inventory and ordering, and to manage and report on product defects and percentage compliance to quality standards, and labor management systems that track worker output and productivity.

One solution in this category is Oracle’s JD Edwards Enterprise One Manufacturing Management. The company’s web site claims the application “manages all manufacturing modes with a single enterprise-wide system where all manufacturing processes share common inventory, material, planning, purchasing, and financial databases.”

Manufacturing execution systems (MES), a subset of applications in the manufacturing sector, are applications that directly monitor and control the manufacturing process; for example, managing the dosing of different materials into a vat of formula, opening valves, operating PLCs (programmable logic controllers), and displaying real-time graphics of the different stages of production. These systems usually also calculate and display management-related indicators, such as cycles per second, minute, hour or day, pieces produced per man-hour, and percentage of material losses in the production process.

Wonderware is an MES software brand with a long history in real-time monitoring and control of manufacturing processes. The company is owned by UK firm Invensys, and claims more than 500,000 licenses sold in over 100,000 manufacturing plants around the world.

The company’s web site claims: “Wonderware is the market leader in real-time operations management software. Wonderware software delivers significant cost reductions associated with designing, building, deploying and maintaining secure and standardized applications for manufacturing and infrastructure operations. Our solutions enable companies to synchronize their production and industrial operations with business objectives, obtaining the speed and flexibility to attain sustained profitability.”

Wonderware’s customers include Chevron, Norfolk Railway, Nucor Steel, New Belgium Brewing Company, and Magna Automotive.

Another subset in manufacturing applications is shop floor management. These systems are used by contract manufacturers and companies that make to order specialty products. The software helps with estimating time and costs, managing schedules and resources, and coordinating material receipts and shipments.

E2 is a private company that claims to be “the authority on manufacturing software.” The firm’s web site states: “The E2 Shop System is comprehensive manufacturing software that puts total shop floor control at your fingertips. Designed just for job shops and make-to-order or contract manufacturers, E2 equips you to see your business like never before, and get the big picture on the best way to manage it.”

The ROI for these apps comes usually from basic cost control. Especially in complex manufacturing environments where many inputs and processes are involved, precisely recording machine time and materials consumed is essential to cost control. Small percentage reductions in losses or just knowing your true costs can more than pay back the investment in shop floor, MES, or other manufacturing software.

Image by David Bleasdale, CC license

Analytics is one of the top buzzwords in business software today. Analytics software is often marketed as a tool for business intelligence, data mining or insights. It’s the crystal ball software: tell me things I don’t already know, and show me ah-hahs or other exciting revelations that, if acted on, will increase sales, cut costs or produce some other benefit.

The essential elements for analytics are:

1) A design for your ‘stack’ which is just a term for layers: usually at the bottom you have a data layer, then a translation layer, then on top of that some kind of user interface layer. The translation and user interface layers are usually provided by the analytics vendor; you provide a place for data storage.

2) A way to send the data to your data storage, automatically, which is usually referred to as “ETL” or extract, transform, and load. SnapLogic and Informatica are two vendors who offer these tools.

3) Some way to “harmonize” the data, which means define each data element and how it will be used in analytics. “Sales” will mean such and such, “Gross Margin” will be defined as ……

These three components can be on-premise in your building or in a cloud hosted by a vendor.

SAS, based in North Carolina, has long pioneered this space, and now many business software firms claim to provide “robust analytics.” The problem: what constitutes “analytics”? Canned reports are not analytics. So you’ll need to shop this category knowing that probably the most serious applications will come from firms that are dedicated to analytics.

International Data Corporation (IDC) reports that the business analytics software market is projected to grow at a 9.8% annual rate through 2016. IDC describes the market as dominated by giants Oracle, SAP and IBM, with SAS, Teradata, Informatica and Microstrategy rounding out the top 10 in terms of sales revenue. Although the top 10 account for 70% of the market, IDC reports that “there is a large and competitive market that represents the remaining 30%…hundreds of ISVs (Independent Software Vendors) worldwide operate in the 12 segments of the business analytics market…some provide a single tool or application, others offer software that spans multiple market segments.”

Here are some other interesting analytics or business intelligence (BI) products: Qliktech provides easy-to-develop dashboards with graphical representations as well as tabular and exportable reports. Its Qlikview software is an “in-memory” application, which means that it stores data from multiple sources in RAM, allowing the user to see multiple views of the data, filtered and sorted according to different criteria.

Information Builders (IB) is a software company classified by advisory firm Gartner as a leader in BI applications. IB’s main application, WebFocus, is a flexible, user-friendly tool that is popular with sales teams because salespeople use it while visiting customers to enhance their selling messages with facts and visual interpretations of data.

WebFocus has a “natural language” search capability, making it useful to monitor and analyze social media.
Birst, named by Gartner as a challenger in the BI space, is a cloud-based (SaaS) application that offers “self-service BI,” deployment to mobile devices, adaptive connectors to many different types of data sources, in-memory analytics, drill-down capabilities, and data visualization. The Birst tool also has a data management layer, allowing users to link data, create relationships and indexes, and load data into a data store.  Tableau is another similar vendor.

It’s useful to start small and experiment with analytics.  People in your organization with good quantitative skills and imagination can experiment with tools, usually at very low cost.  Soon you will see some interesting results and will want to do more…but make sure to put in place some rules about what constitutes sanctioned and official “analytics” in your organization, to prevent uncontrolled proliferation of un-validated information.

Image by reynermedia, CC license

Finance and accounting functions were among the first to be automated through software. The sheer volume of numbers and calculations, reporting requirements, tax filings and payroll mechanics, plus the fact that nearly every business has to engage in these activities, made the area perfect for software.

When just these basic functions are needed, not much distinguishes one finance application from another. They all post transactions to a cost center and sub ledger account, they all capture sales and costs and calculate required P&L and balance sheet data, and they all provide reports. They might distinguish themselves in terms of ease of use or report writing, or banking account integration, or cash management, or some other aspect.

Many finance applications are simply bookkeeping systems; if you want real analysis you’ll need to extract data to Excel, Business Objects, or another analysis and reporting tool. My own experience with both Oracle and SAP bears this out: even these leading finance packages are mostly concerned with accounting and financial, not management reporting.

Oracle and SAP both have what they call “business intelligence” capabilities, but they are contained in separate modules that must be purchased and integrated with the core software. So companies can easily spend millions implementing SAP or Oracle, and still find themselves extracting data into Excel spreadsheets for basic business analysis.

My experience is that most finance applications lack budgeting and financial modeling capabilities. It is one thing to know that your prior month results were over budget because of rising fuel prices, and quite another to project the future profit impact of different oil price scenarios. At what point would it make sense to switch to alternative fuels, to pass on some of these increased costs, or to buy oil futures as a hedge? A typical finance application won’t help you to answer these questions because they mostly record and categorize costs based on what already happened, not what might happen in the future.

Yes, there are “what if” modeling applications available on the market, but as a stand-alone application they aren’t very useful, since you have to enter all of your data, as if you’re using an Excel spreadsheet. The modeling application needs integration with your ERP to be most effective. Your ERP is the source of all kinds of data needed for financial modeling: production costs, formulas, material costs, transportation costs, revenue by product, as well as cost standards and budget information. This data changes frequently based on business conditions, competition, labor costs, and many other factors.

Microstrategy, Oracle Hyperion and Cognos are leading names in the financial modeling and analytics areas, but other, smaller firms are emerging. Netsuite, the ERP-in-the-cloud vendor, offers an add-on financial modeling application. Netsuite’s web site states that the modeling application features these capabilities:
• Dynamic formulas and assumptions
• “Actuals” data incorporated into new forecasts
• Workflow management
• Planning of full financial statements
• Unlimited versions for “what-if” analysis
• Multi-dimensional models for complex sales and product planning
• Multiple currency budgeting
• Graphic drag-and-drop report builder
• Multi-version variance reporting (vs. budget, vs. plan, vs. forecast)

A3 Solutions is another, smaller firm offering financial modeling applications, either on-premise or as Software-as-a-Service. A3 uses the Excel spreadsheet as the user interface, claiming it is the friendliest environment for creating what-if scenarios, and provides tools to link multiple sources of corporate data and manage modeling versions dynamically and virtually through its Spreadsheet Automation Server. A3 claims McDonalds, Honda, Toyota, T. Rowe Price, and American Airlines as clients. Simplicity, speed of implementation, and low cost are A3’s main selling points.

Once you have the “system of record” stabilized in a strong finance application, as well as good controls over product, customer, and sales data, you can start to think about these higher-level analytical tools. Define a standard model for delivering analytics, put someone in charge of the data, and tightly control the “official” analyses that are produced.