None of these supply chain software companies will solve your conflict minerals issue.
Before I get into the critical part of my rant, I first want to make sure that it is really clear that I applaud Intel for making a commitment to be “conflict free” by 2016. For those of you who don’t know what that means, read more here. But, basically it means that they will ensure that the elements and materials used in their products will not come from questionable sources that partake in or fund human rights abuses. This specifically targets minerals such as tin, tantalum, and gold, which primarily comes from regions in the DRC, where there are some organizations that use child labor, slave labor and other terrible means to run their business. Think blood diamonds, but for electronics components.
I think it is awesome that companies understand how important this is, and are setting goals to ensure they are not supporting these corrupt organizations with their business. It’s doubly impressive they are setting these goals because it is not easy. These companies are many tiers deep in their supply chain — meaning its a guy that buys from another guy that is buying from yet another guy (and then do that seven layers deep). So, even mapping out where all the materials are coming from at any given time is incredibly complicated given the global, disparate nature of supply chains — not to mention that it is constantly changing.
Now time for the rant. The second part of the announcement I saw talked about the “solution” companies like Intel are using. None of these supply chain software companies are really solving the problem here. They all do the same thing — doesn’t anyone else see that? I feel like I’m taking crazy pills.
These systems are nothing new — basically just online reporting platforms of some kind. So, yeah, it gets us away from managing it all on spreadsheets (which is what I was doing when I was a Sourcing Manager), but it still doesn’t solve the real problem. Sure, spreadsheets and email communication are frustrating because they lead to lots of bad data. And yes, collecting and analyzing data in this way is also really inefficient. But the elephant in the room is the fact that none of the data is any good.
Many companies have purchased enterprise software solutions that send out an email with a link that the supplier clicks on to fill out their data. That data is formatted and stored for that one company, which is only one of the suppliers' many customers. Many trade groups have tried to discourage that, because it leads to a lot of duplication for the suppliers - wasting time and money for everyone. These groups are creating standards that all companies can use, which moves us in the right direction, but doesn’t solve all of the problems.
So along come silicon valley software companies promising to solve all the traceability, transparency and data problems for supply chains. But they are all the same — a web-based platform where suppliers fill out a profile and let all their customers see it. These systems solve the duplication, scale and data management problem, sure, but they simply can’t deliver real traceability or transparency because they don’t understand how to get real data.
The reason this problem is so freaking hard is because any solution has to solve ALL of these problems:
value (how do we even use this data? reporting, decision making, goal setting, surface problems, take action, etc.)
Solving only a few of these problems doesn’t work. So, if you can make a scalable web service for suppliers that is full of bad data, it is useless. (little secret: it already exists, and in fact, was created decades ago... it is called Alibaba.com) Consulting companies and auditors love the fact that these software tools are full of bad data, and use it as great proof for their in-person data collection services. But we all know that those just don't work at scale, and that is why technology seems like the way forward. (Read more about the Chinese word for “audit” and how that’s not necessarily as reliable as we all might expect either.)
Let’s dig into the reasons we are getting bad data a little bit.
First, your users have to be able to give you the data. Have you ever sent out a survey where some of the responses were just nonsense? This is probably a good indication that the user didn’t understand the question and/or didn’t even know where to find the information you were asking for.
Some companies try filling this gap by sending their own people on site to collect data from the suppliers, and usually spend some time trying to train the suppliers while they are there.
Do you have any idea why you don’t get a 100% response rate on your surveys? Factories are busy places, and finding, preparing and inputting data takes time. And, like we mentioned, suppliers have lots of customers with many different requirements. How do we make it less time consuming and costly for suppliers to give us the data we need? Or, how do we make this process worth it for the supplier (see the Value section below).
Have you ever thought about why/if your suppliers even care about giving you this data?
I was at a conference a few months ago and was running a small group discussion on supply chain sustainability data. We had folks from Wal-mart, Levi’s, Kohls and others in the room. I started with a round of intros and asked everyone to tell us their name, title & company, their annual salary, and how many kids they have.
I started “Hi, I’m Taryn the CEO of EEx, and I make a million dollars a year, and I don’t have any kids, just two cats. OK, you’re next", I said to the woman next to me. People started shifting in their seats and eyes were darting around the room showing everyone’s discomfort with the idea of sharing that information with the group. It was a great way to get people to think about reliability of data. Why would they just voluntarily tell everyone their salary?
The woman next to me laughed nervously and said “OK, Taryn, I think we get your point.”
Another woman joked and said “Who will get access to this information, our kids?” insinuating that she didn’t want her kids to know how much money she made, because they might expect more from her. The group laughed, but I tried to bring us back to the lesson about supply chain data — "just because you ask someone to share information with you doesn’t mean that they will." Also, even if people do share, as I happily did — how do you know if it is accurate? Would I only give accurate information if I was worried the group would collectively audit me? How would things change if the person asking for your salary information was helping you set up a family financial plan because you were planning to buy a house and start a family. You expect to get real value from the financial planner, so I bet the data provided to them is a lot more accurate because it is in your interest for it to be accurate.
A strategy that expects suppliers to give data that is not actively in their own interest to provide, and that they get no direct value from providing is a bad way to get good data. Mandates & threats of audits will just add another layer of inefficiency, opaqueness and frustration for everyone involved.
If we want lots of really good data, we have to go beyond the basic motivations and fears, and realize that people’s willingness to provide accurate data skyrockets when they get direct value as a result of the data they share -- especially if people get more value from providing more data.
Now do you see why I’m so impressed that these companies are setting such aggressive goals — when they are faced with overcoming all of these barriers and finding or building solutions that solve all of these issues?
Imagine for a minute a web-based tool that is designed to help suppliers improve their own business, and in the meantime compiles the type of data required by their customers.
That’s what we’re building at EEx. We solve data quality problems in a scalable way by understanding and aligning the motivations between buyers and suppliers.
Rather than trying to collect every piece of supply chain data in a way that solves every problem but the one that matters the most (data quality), we started by focusing on compiling just one piece of real data (electricity), but doing it in a way that actually works well at scale. This works because we build tools to solve problems for the person who is actually using it first. Here's what that means to the users...
Getting started only takes a few minutes, and is as easy as signing up for a new gmail account.
Free trials with low cost make it affordable for even the smallest of the 6 million factories in China.
No prior expertise required, so there's no training or integration.
Actionable recommendations show factories how much money they can save and step-by-step instructions on how to solve the problem.
Additional information is built-in so they can learn more about the issue or problem when they need to (when they actually have it).
It takes subject matter expertise from hundreds of professionals with practical experience solving real problems and building it into the tool so the analytics are contextualized depending on individual circumstances.
Our first app, EEx Charge, is a great example, and is being used by hundreds of factories throughout China to understand, manage and lower their monthly electricity cost. Rather than listing features, I like to talk about how Charge helps these companies, as follows:
only pay for the power they use
use as little energy as possible
continuous tracking of electricity data
In the process of helping factories improve their own business, our app compiles data that their customers (retailers and brands) have been asking for through emails, surveys and audits. This is a more reliable way because it provides value to everyone involved.
We still have a long way to go, but I'm hard pressed to find other companies out there that are creating real value for suppliers with these solutions.
Rather than just asking suppliers to report information you want, figure out how to make that data valuable to the supplier you want it from.