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Mapping Product Genomes: The Life Blood of Supply Chains


One major technological development is being able to map genomes for products. A genome is all of a living thing’s genetic material. It is the entire set of hereditary instructions for building, running, and maintaining an organism, and passing life on to the next generation.[1] In most living things, the genome is made of a chemical called DNA. The genome contains genes, which are packaged in chromosomes and affect specific characteristics of the organism. A genome map helps scientists navigate around the genome. Like road maps and other familiar maps, a genome map is a set of landmarks that tells people where they are, and helps them get where they want to go. The landmarks on a genome map might include short DNA sequences, regulatory sites that turn genes on and off, and genes themselves. Often, genome maps are used to help scientists find new genes.

Genome mapping is a capability that grew out of the biotech industry, and which is proliferating, largely due to the dropping cost of genome sequencing. The cost of genome sequencing in 2001 was $100M per sequence. By 2007 it was $10M, and it has now dropped to $1000, and is expected to drop to a penny by 2020!  Less than the cost of flushing a toilet!  A picture of a genome mapping pulled from a website is shown.
In a similar fashion, the digitization of things will allow us to be able to better map product genomes. The ability to track products and be able to pinpoint not only where they are today, but to track the entire history and ancestry of a product through the chain, is emerging as a key enabler of transparency and visibility in the supply chain.

Consider this:  Are you able to connect the essential leverage points in your network through cloud, mobile, and other mediums that provides a platform for analytics? Can you track the DNA of your supply chain at a part number level, globally? Today, the answer to both these questions is no, but very soon, we will see technology that will permit anyone, whether a consumer, a manager, or a suppliers, to be able to do this.  This is one of the big questions to consider when we think about how supply chains evolve. We need as structure to map the genome of our supply chains – and this means having an ability to establish part number tracking and coding in the end to end supply chain. One of the biggest opportunities here is to think about a vehicle for encoding the genome, to enable understanding of where products go and come from, which is one of the most important elements in combating counterfeit and fraud. This element of waste is rarely discussed in supply chain scholars, but remains one of the biggest and overlooked areas of lost profits and revenues in the world. The importance of tracking and measuring all goods, including the possibility of counterfeit goods, must be estimated using data tracking.   But unlike the calls for “Big Data”, we must “de-mystify” the view that Big Data is the answer for supply chain improvements. Big Data is static and useless;  it’s the questions you ask of the data that change supply chain outcomes.

The digitization of products and things is a key technology development that will drive the ability of individuals in supply chains to be able to track what is happening in their living supply chain. In effect, these digital signals are like the nerves in our body, that transmit to our brain, that drives us to act when our hand is close to a stove burner, or we taste something pleasurable, or any other sensation that is driven by nerve endings.

But we can’t process everything at once in a supply chain. There is just too much data, and this can lead to sensory overload, where data is flying at us, and we can’t process it all. We have to sleep sometime also! And maybe play golf without having to look at your mobile phone all the time. So how is the digital living supply chain going to work?

The key here is to think about what data you NEED at any given time, and what data is considered CRITICAL at any given time. As humans, we can only focus on a limited number of inputs, so we need to define ahead of time what we view as critical. If we need information on something that doesn’t fall in that category, we also need to be able to know where to look for it, and if we have to do a “deep dive”, have a system that allows us to do that in more detail to the right level of granularity. But more than that, you need to think about getting data that is useful, and for it to be useful, it needs to be current – ideally, it needs to be in real time! And to be able to process it quickly, data should be in a “visual” form. That is, people understand pictures a whole lot better than tables and tables of figures. So taking data and visualizing it, and putting it together in such a way that you can easily process it is key. That is what Steve Jobs understood immediately when he designed the Apple as an interactive, visual device, with a human interface.  How we interact with the data will determine how useful it is.  Automation can help us focus on the right information, but ultimately, humans must make the decisions based on that information.