Start Your Big Data Journey with a Map

Justin Holman, the CEO of TerraSeer, recently wrote an interesting blog post suggesting that a great place to start a Big Data journey is to build a map.  He argued that most firms  and managers don’t have the resources or technical capability to do a full-blown analysis on all their data.  But, a map is a relatively simple place to start that will allow you to visualize a lot of data quickly and in a new way (most firms still don’t use enough maps to view data.)

For the supply chain manager, I would agree.  As we’ve discussed before, a map can be a great way to view your customers by different types and relative demand (as seen in the map above).  It can also be a great way to see how product is flowing through the supply chain.

We have seen many cases where a company finds savings opportunities by just looking at their data on a map.  It is often the first time the managers have seen the data presented in this way.  And, it allows the managers to quickly understand their business in ways that were not obvious before.

Even if you are not doing a full-blown network design study, I would still recommend mapping your customers and supply chain.  You may learn something new.

Importance of Single Sourcing Groups of Customers

In practice, you need flexibility to single source customers and groups of customers.  (By customers, I am referring to the final ship-to location.  This could be a retail store, your distributor’s warehouse, or even an end consumer)

For example, you many minimize your costs by shipping from multiple warehouses or plants to a customer.  But, this may annoy your customers.  Or, you may only be able to send full trucks once every two months.  To avoid these problems you can single source the customer and find the best single point of delivery to that customer.  That is, your products must all travel to single warehouse and then on to the customer.

It also becomes import to single source groups of customers.  For example, for simplicity, you may want to serve all the customers in Tennessee from a single warehouse to simplify your operations.  Or, you want to serve all your customers that are in the same Sunday Paper region so you can better manage promotions.  In the construction business, you want to make sure all the customers in a region receive product from the same manufacturing plant.  Boards and shingles coming from different plants can have slightly different colors.

Justin Holman, CEO of TerraSeer, is doing some interesting work for the automotive aftermarket.  He put together the map you see in this post to help determine the similar regions for auto parts.  He has a post that explains the map and the fact the state boundaries are not helpful for forecasting auto parts.

If you apply his concept to network design, you might want to single the customers in each of the regions that Mr. Holman has identified.  This would simplify your decisions about what products to stock in each warehouse and would allow you to better manage demand.

Besides aftermarket auto parts, you could imagine that this analysis would apply to a wide range of products– construction materials, swimming pool products, sun screen, lawn care products, beverages, and about any other product whose demand changes by season.

Dual Sourcing Strategies and Network Design

Recently, I wrote about dual sourcing strategies in my SupplyChainDigest column.  The idea is that when firms try to decide if they should make a product in China or the U.S, they should also consider a dual sourcing strategy.

Professors Allon and Van Mieghem from Northwestern’s Kellogg School of Management have formalized this strategy in several papers and projects.

With this strategy, you can get the low cost benefit of China and the safety stock benefit of reacting to variability in the U.S.

But, there can be more to this strategy.  This discussion assumes that demand for this product is mostly in the U.S.  If demand for the product is world-wide, you need to use network design software to help determine where to make product for each market.  That is, do you make a product in each region of the world to avoid transportation costs or do you centralize production to take advantage of economies of scale.

The lessons we learned from dual sourcing still apply.  If it is better to make a product centrally because of economies of scale, then you may want to consider some local capability to handle the variability and reduce safety stock requirements.

This analysis is certainly more complex, but the extra effort can reduces costs and risks.

Network Design within a City for Same-Day Delivery

We typically think of network design at the national level.  However, the same principles apply when doing a study at a very local level.  For example, we’ve talked about the pizza delivery model as a good example.

This topic is becoming more important as retailers try to figure out same-day delivery.  I talk about his issue in  blog post at SupplyChainDigest.


White Paper: Combining Network Design with Process Excellence and Strong IT

PRTM (now part of PwC) and LogicTools (now part of IBM) published a white paper showing how firms create efficient supply chains:

“…the integration of a few disciplines in supply
chain management—optimization of
network and inventory, process excellence,
and IT-enabled visibility and collaboration
has proved to generate breakthrough operational
improvements at reduced overall




Mars Wrigley Presentation On Use of Network Design

IBM posted a YouTube Video of Mars and Wrigley discussing, “how they used IBM ILOG’s supply chain applications; LogicNet Plus XE, Inventory Analyst, and Transportation Analyst to maximize the efficiency of their global network for huge savings in a presentation to IBM Smarter Supply Chains Regional Symposium and Users’ Conference in 2009.”

Lead Time and Inventory Buffers

A recent article on (a fast rising $140 million design retailer) reminds us that there are multiple lead times in a supply chain and that inventory plays a key role.  Here is  key question (from the WSJ) and the answer (from the CEO):

WSJ: Earlier this year, your average shipping time was 15 days. How have you improved fulfillment?


Mr. Goldberg: We’re living in an Amazon world—shipping should be fast and free. We’ve invested tens of millions of dollars this year on two efforts. One is to build warehouses so that we get things in and out very quickly. The other is purchasing inventory. Last year during the holidays about 10% of our product was in inventory. Seventy percent of the products that are currently on Fab right now are in inventory, which means they’ll ship within one day of purchase, which means they’ll get anywhere in the U.S. in one to four days.

This is very interesting on a few levels.

First, Amazon (and other retailers) started out just like this– with no inventory.  In fact, back in the late 90’s, there were articles saying that on-line retailers had a huge advantage because they didn’t need to hold any inventory.  They would take the order and then have the vendor ship to the customer.  It would have been a great business model if had worked.  But, like is finding out, customers don’t want to wait 15 days.  Like Amazon before them, is finding out that they need to hold inventory to reduce lead times to the customers and control their business better.

Second, this shows that there are multiple lead times in a supply chain.  Presumably,’s lead time is still 15 days.  However, because they have an inventory buffer at their warehouse, their customers now only see a 1 day lead time.  So, the inventory buffer changed the lead time buffer that the customer sees.  Inventory buffers are also very useful for buffering variability that the customer sees.

In general, a company should measure the overall lead time, but also the lead time seen by different parts of the supply chain (what does the customer see?  what does the warehouse see?  what do the plants see?).

Now, can work on reducing the 15-day lead time from vendors knowing that the customers see the 1-day lead time.  As they reduce the 15-day lead time, the benefit will be a smaller pile of inventory at the warehouse.