Supply Chain Visibility Example #7: Competitive Market Visibility

The default view of supply chain visibility is that it is inward looking, meaning that the supply chain in question is our own. By this default view, we’re mostly concerned with knowing about ourselves, about our inventory and orders and capacity, etc. The other examples given on this site support the default view, and only consider our own supply chain as a source of data. But this doesn’t always need to be the case. In some situations, supply chain visibility is about seeing your competitor’s supply chain and making decisions based on that understanding of how they bring their products to market. This is what we call “competitive market” type supply chain visibility.

You can imagine, given the difficulty supply chain managers have in knowing their own supply chain, how transparency to a competitors supply chain would be difficult to achieve. The most challenging aspect of visibility to a competitors supply chain is data capture. Where a retailer may have trouble getting production plan data from their own suppliers, they have really no chance of getting such data interfaced to them from a competitor retailer’s supplier. So, if you can’t simply ask for the data about your competitor, how do you get it. This is, I believe, where things get interesting.

To construct an understanding of the competitor’s supply chain, using legally available methods, is something that often occurs during a hostile acquisition project. After all, the supply chain is a major determinate of a business’ success, so its therefore a determinate of the business’ valuation and how well it would fit with the acquiring company’s existing supply chain, IT systems, or management culture. In non-hostile acquisitions a lot of data is provided willingly by the target company, but this clearly wouldn’t be the case when trying to setup supply chain visibility on a competitor. Most of the processes done in evaluating a hostile takeover targets can be redeployed for competitive market type visibility. These processes include using publicly available data to estimate:

  • Organization charts for sourcing, product development, IT, logistics, and sales
  • IT landscape, including what ERP is in place, what systems are used for forecasting, order management, inventory management, etc
  • Channels to market: do they have retail stores, do they have a web store, etc
  • Fixed assets in machinery or buildings. Knowing a company owns its own distribution center may tell a lot about how they can manage their supply chain.
  • Timeline of major investments, entry into new markets, etc
  • Stated goals in new markets, with new products
  • Formal partnerships or sponsoring status of industry associations
  • Executive compensation schemes and backgrounds
  • Patents or ongoing legal disputes
  • Financial outlook: are they debt free, debt heavy, etc
  • Employee overview: how many, where at, etc
  • Ownership structure
  • Major suppliers and customers, with hopefully the same kind of analysis as described above being done on these supply chain partners.

For large public companies, virtually every point above can be discovered legally. In most cases, the data above form a kind of “master data” that allows us to understand the macro-level forces affecting the competitors supply chain. In some situations, keeping this updated in a CRM-type tool is enough. For example, its common practice for sales-staff to be required to keep ongoing notes about prospects or clients in a CRM tool. If the sales person sees someone at a conference and they mention that the vice-president of the prospect company has just been fired, the sales-person is supposed to go to the CRM tool and update it. This allows all sales staff, even in the future, to have a kind of collective memory about the client or prospect organization.

Just as the process of maintaining a collective memory about the prospect or client is very valuable, the same can be done with competitors. When the analysis shifts from the competitor as an individual, to the competitor and their supply chain partners as a competitor supply chain, then we are talking about competitive market supply chain visibility. Perhaps more important is to take the “master data” types of information about the competitor supply chain and connect it with more transactional, real time data. The best data sources for transactional-level data on competitors are government-mandated reporting.

Imagine, for example, that you are a specialty manufacturer in the US and you sell industrial electrical fittings for public electric grid operators. Your competitor is also based in the US, since transporting the finished fittings is extremely expensive. Both you and the competitor import raw materials from overseas. Having done the analysis described earlier and keeping it maintained, you have a good overview of the competitor and their supply chain. Going into a request for quotes (RFQ), you want to leverage that visibility to improve the price quote decision. How would this be done? The answer lies with publicly available data from the US government.

Governments are interesting as a data source. They are able to dictate the content, format, and quality of the data. Generally, the data they obtain becomes publicly available. In some situations, there is a delay, which renders the data less useful. And all that public data may come in truly awful formats, like as a printed report which must then be re-keyed into a database to be useful. But, all of those issues aside, government data can help with the question above. In the US, all imports and exports are recorded at a fairly transactional level and are released to the public. With the right process or system, we can know the following about the competitor:

      • Who the suppliers of the competitor are
      • What exact materials or parts they have been buying
      • The quantity of materials or parts
      • The price paid for the materials or parts
      • In what rhythm the transactions take place between the supplier and the competitor: daily, weekly, monthly, etc
      • Among US importers, what proportion of the supplier’s business goes from to your competitor

With the “master data” information, and with transactional data about all the exchanges between the competitor and their suppliers, it should be possible to answer these questions:

  • Does the competitor have materials on hand to handle this order, or would they issue a PO to their supplier (i.e. am I pricing against a make-to-stock or a make-to-order offer)?
  • Given the expense of final-SKU transportation, what would be the expected transport cost from the competitor’s facility vs. my own facility?
  • Does the competitor use the same supplier as us?
    • Who buys more volume?
    • Who pays higher prices?
    • Who orders regularly vs irregularly?
    • Is there an opportunity to lock-up capacity with the supplier by using the competitive market visibility information during negotiations?

These questions can help determine where the competitor will respond to the RFQ. Perhaps the competitor runs very lean and has no inventory of raw materials to fulfill an immediate order, but can sell for a lower price point than us if the order is delayed. Now we know where to compete, i.e. based on speed to deliver rather than price.

The transactional data you have access to greatly depends on industry and locality. Every country has its own government initiatives to collect data, and each industry has specific reporting requirements and data which are considered valuable. But in almost all situations there is some kind of supply chain transactional data leaking out which can be integrated into a competitive market supply chain visibility system.

In summary, this type of visibility is an inversion of our default belief that visibility is about knowing ourselves better. Instead of trying to get more information on our own inventory, or own order statuses, the competitive market type supply chain visibility tries to get this information about the direct competition. As with most articles on this site I’ll wrap up with some high level points about how this can be used immediately in your work:

  • Supply chain visibility is indeed about the supply chain, but not always your own supply chain. In some situations its more valuable to know about the competitor’s supply chain than to improve transparency to your own.
  • It is legal and possible to form a macro-scale view of a competitor’s supply chain using publicly available data and processes common to hostile takeovers. The bullet points discussed above should be answerable for any large public company, and mostly available for smaller public companies.
  • After setting up a macro-view of the competitor’s supply chain, fill it in with transacational data retrieved from public sources. Often the best data sources fro this are government mandated reporting schemes.
  • Ensure that competitive decisions tie to the new visibility, since many decisions which could use this data are not made in a strictly supply chain context or by supply chain departments.
  • For an example of how this might be put in practice, see the technology review of Panjiva, who provide visibility software for competitive market visibility based on US government import data. Here is the link.

 


Learning by Playing: More Supply Chain Games

In January 2011 I published an article called “Playing for Real: Supply Chain Games”. As I said in the original article, supply chain games are a great way to develop new staff’s instincts about coordination, competition, and the cause-effects of rule mechanisms on behavior. I’m publishing below two additional games for training supply chain instincts. One looks how strong supply chain governance is different from reputational and transactional relationships. The other game simulates a price war, which is always fun.


Visibility Scorecard

When it comes time to make a decision between the different paths to visibility, your life will be much easier if the options can be compared across common metrics. This should make intuitive sense for those who have been on project steering committees in the past. Comparing apples to oranges is frustrating and makes important decisions open to personal interpretation. By scorecarding the fundamental effectiveness of the visibility provided by each option, we help avoid this pitfall.


Visibility Example #6: The World as a Warehouse

Imagine a large supply chain, covering 15,000 workers operating in 12 languages and 24 countries. Every day, inventory in various stages of completeness and transit could be valued at over one billion US dollars. Losing even a fraction of those materials would represent enormous wastage. Even without outright loss, a delay or misdirection could cost valuable time during which customer demand slacks and may eventually disappear altogether. How can we control such diverse, decentralized, and partially synchronized operations? One approach is to use a visibility layer to approximate a planet-wide warehouse: Total control and traceability of materials at any physical point on the earth, using common language and processes.


Risk Management via Supply Chain Visibility

Supply chain visibility is often included in the risk management toolkit. By coupling process changes with the improved intelligence from supply chain visibility with fast decision cycles, organizations hope to out-maneuver interruptions in the flow of material, capital, or information. In this article we’ll address visibility for risk management at three levels: what makes risk worth watching for (the business problem), how supply chain visibility can reduce risk (the mechanics), and finally how all this is often leading to more risky behavior on the part of the organization (the unwanted outcome).


The Supply Chain of Digital Content

Standing in an elevator in Changi International Airport early on a Monday morning, you’re likely to see business travelers reading the newspaper. But how did those newspapers get in their hands? As it happens, many of the newspapers may not be “paper” at all. They are digital content, served up to dedicated or general viewing devices. And since that form of newspaper was unavailable just a few years ago, let’s consider the supply chain behind these forms of digital content. Inevitable questions arise when we think about a digital content supply chain: is there a supply chain for digital content at all? If so, is it managed using the same principles and strategies as the more common physical version? Does the same staff run both supply chains? If not, what skills are appropriate to digital vs. material supply chains? Those are the questions behind today’s article. And to start off the discussion, let’s look at the “digitization” phenomenon from the viewpoint of a supply chain.


Watson and the Case for AI Staffing

Today’s article builds on earlier posts which dived into the likely prominence of artificial intelligence in supply chain management (and visibility) in the future. Specifically, we’ll look at the recent performance of the IBM question-answering AI system called “Watson” and discuss what it portents for supply chain careers.


Supply Chain Visibility & Artificial Intelligence

As some of the other articles on the site have discussed, there is a coming dominance of information over the purely material-management aspects of supply chains. And, at other times, I’ve mentioned my belief that artificial intelligence will play a major role in the shift. In today’s article I’m highlighting specifics behind that belief. The distinguishing line between tasks which must be completed by humans vs. machines is dynamic, changing more based on machines’ increasing capabilities than on changes in human ability. At a point in the near future, much of what is now “human-only” will become “human optional”, and finally “human impossible”. Data or calculation intensive tasks are an example of work that has recently shifted over these lines. For those who are having trouble imaging robots doing supply chain analytics, I promise to start slow…


Visibility Example #5: Benefiting from GPS

The web 2.0 catchphrase “mashup” refers to the ability to integrate heterogeneous data sources into a single, consistent, view for greater total value to the user. Mashups, both useful and dubious, are making their way into supply chain visibility toolsets. Today’s visibility example looks at a very simple and productive mashup between order data and GPS location devices riding with delivery drivers. In the article, we look at the situation and then decompose where its value-add comes from. The example below is fairly short and simple, but very effective. This is an example of “simple solutions to complex problems”.


Playing for Real: Supply Chain Games

Supply chain games are a great way to develop new staff’s instincts about coordination, competition, and the cause-effects of rule mechanisms on behavior. The infamous Beer game and Procurement Game were some of my first introductions to multi-party coordination through rules. Recently, I was looking for more games and ended up creating or modifying some