In the early nineties, I was drafted by my peers to be the IT manager to stand-up in front of the President of our corporation to point out that our Return on Information was extremely poor. (We didn’t call it that, then, of course.) Not only we had thousands of users writing redundant reports, but the organization was churning a few basic business issues (orders) and creating, corporate wide, reporting systems with different rules for that data which then would not match. The subsequent tower of babble, the monthly management meetings ensued, where, rather than discussing key issues on how to grow the business, managers fought over data sources—‘where did you get your numbers from?’.”Call the guards, sound the alarm and form a committee”. I think when I went through the IT cost structures of writing thousands of conversion programs it struck a cord, though. This lead to the inevitable creation of a data management committee (good idea, poorly managed) and then the follow-on sledge hammer of ERP I. ERP would force all of us to agree, it was thought. We were to reduce the spend of IT, by spending hundreds of millions on consultants who came and went, as well. And the big bang ERP I project limped along for years. As most project people will tell you the huge issues in any IT implementations schedules becomes data, process and business complexity resolutions.But they missed the higher order lesson I talked about.We were churning the same old data and not looking out to our markets
- We had over 14 order data warehouses but not one competitive information warehouse
- We spent less than .05% of our IT budget on data subscriptions, data streams and research on markets, competitors, customer surveys, etc.
Our supply chain data was made up.That can’t be, you say! But think back. We were all operating the global chain of assumptions on derived data and belief data for things like: lead times; availability and capability of suppliers to meet our needs; the cost of transportation; and returns. Many firms are still making up these numbers.Poor understanding of expense variability. When it didn’t work as planned—why? We had little idea. We spent a lot of time on transaction systems—called execution systems—but very little real execution systems that understand and managing execution—i.e. business events.
And we had no visibility, once product left the dock, to its path forward. The inevitable returns followed back at the beginning of each quarter as a myriad of channel partners (who also like to play games with their accounting systems) returned unsold product.
Oh, there is more, but the basic elements of poor data management are here stated:Myopic focus on churned, stale, internal data.Using numbers to support personal objectives—I made my numbers, I get to go to club, get stock options, etc. (I think we send people to jail for that these days).Over investing in reporting systems where users applied their own rules to the numbers in order to approximate what they believed was the true state of the business (since they could not get the real-time data).Thus, decision making was a very dubious exercise.
Does any of this sound familiar?Like a Bridge Over Troubled Waters…IT & Data Services On DemandBy the late 1990s most of corporate America was right in the middle of ERP I, the consolidation and overhaul of the corporation financial structures, just as… along comes the virtual enterprise.
Of course, this is the conflicted story. While building the “ERP Moat” in headquarters, the supply chain was being outsourced, exposing the need to share data across many domains. But ERP Y2K fears were in full swing, so it was hard to bound ERP and begin the process of understanding the global supply chain information issues. Many of us were calling for a serious look at the architectural approaches used to resolve these issues, but too much money and too much was at stake—ERP had to get implemented—not matter what!Well, here we are in 2006, and new generations of business managers and models have arrived. It gives us a chance to rethink IT and our information strategies. Looking to services beyond the enterprise is now becoming the norm. This presents some real opportunities and real challenges when it comes to getting great data to create hands across the waters. As we move to On Demand—not just systems, but the data, too, the need remains. I need good information to make decisions! And On Demand, and service oriented approaches can help fill that need.I recently attended two conferences—GT-Nexus’s customer conference, aptly called Bridges and Viewlocity’s aptly called Vista—both with clients who are large, global enterprises, who rely extensively on their trading partners to provide operational backbone data for the business.Excellent presentations were given by their customers, who travel extensively and are highly seasoned Supply Chain Professionals. These gals and guys really knew their stuff!I walked away with two opposed perspectives.I was extraordinarily impressed by what these managers had achieved in terms of making progress in the creation of a network with their trading partners to create the ‘bridge’ across the waters—literally—to provide the real-time data they needed to run the business;
but…How far we have yet to go in terms of actually getting that data? (Though these firms were way ahead of anybody out there on information visibility).
It was getting interesting to listen to shippers, carriers, 3PL, freight forwarders, et al, smoothly as they could, debate the source of data discontinuity. The other guy was the problem when it came to the data. One brave carrier did clearly state in an open meeting, to put it in your contract (to the shippers). That is the only way you will get the attention required to get compliant data.So what is standing in the way of getting great supply chain data?I often hear this excuse—too often—that sharing data will lead to competitive destruction. That my supplier will some how give this data to my competitor. Hmmm. Now we are talking about ethics here? Or, more importantly, the concept of data ownership. Whose data is this, anyway? If I have a channel partner, is not the shelve inventory status of my product, my data? Or Point of Sales—my sales, too—my data?
This is truly one of the most bizarre situations across the chain. I know I shipped you the product to your DC, I just want to know that you actually sold it, so I can accurately replenish so you and I can make more money! Now Wal-Mart, the most competitive company in the world, doesn’t seem to worry about this. Retail Link provides lots of data. (Still many suppliers are yet to take full advantage of this). People, lets get with the 20th Century here!Lack of shared data platforms. Old methods that weave in and out of dozens of systems and create disjointed data, different format and out of sync (late data) are the norm. On a shared platform, organizations can subscribe to the same source of data, keeping in sync the information. (There are several technical approaches to doing this, which we have discussed in other articles).Disjointed processes. The reality is that disjointed processes lead to disjointed information. A new generation of readers, I guess, need to be introduced to the Bullwhip Effect. They need to play Dice and Chips or the Beer Game. ( Join us to play Supply Chain Games.) They need to look at the real data vs. hypothetical models.
The concept of the Bullwhip Effect is that as the demand signal is propagated (late) through the supply chain, the signal is distorted. Signal distortion increases, resulting in late and inaccurate responses to demand. Notice the consumer sales (figure 2), the blue line. Notice that by the time the signal gets back to the manufacturer and they place the order, the signal distortion is huge. This is not unusual, and though many firms have made great strides in this area (we will show you how below) most firms still suffer from this effect.Return on InformationOne thing is clear—organizations who have good data are way ahead of the competitive curve—whether Harry and David—it’s more than the Pears; Apple Computer (how come they keep coming up with cooler products); American Eagle Outfitters (how come they keep growing in that highly competitive teen market?); and do we say Wal-Mart, yes. They started their data journey when they were a small firm. Mr. Sam knew he needed good information to run the business—the rest is history!Watching track races, it is always exciting to watch a runner pull ahead in the race. And as their lead gets stronger the psychological impact for the leader increases and the back of the pack decreases. You see this in the winning companies too! They are always asking what else can I do to create a greater distance between me and the back of the pack? The losers are saying, we tried this before; or after IT gets done with ERP than we will begin a program. Please!At the above mentioned conferences, I quietly noted that the presenters were leaders in their sectors—not necessarily the Fortune 50, but in their sector—they had more market share, were more progressive and had a winning attitude. They did not blame technology, supplier, or other factors for obstacles. They took a continuous improvement attitude and learned and progressed. They see the need to focus on information (timelines and accuracy) as a key management issue.This positive mind set also was reflected in how they worked with their trading partners. Stated one player “gone are the days when you can fire your carrier.” Educating your partner on the mutual benefits was the way (carrot AND stick—not just stick).We have done several research projects on data sharing requirements and needs of the business community.
Figure 3
We have several versions of this chart, by sectors, company sizes, etc. But what was clear is that though responses varied by industry, the response was overwhelming in the importance of information sharing across the supply chain.And what do they get for making the effort for great data?Improved detailed customer preference dataIncreased salesMore cross sale/upsellReduced customer annoyanceHigh Inventory TurnsImproved product transitions—significantly!Shorter cycle timesLower operating costsNot losing luggage!
The challenge becomes, of course, how do I get that data? How can I rely on that data?How can I bridge across the supply chain to have a vista?
Here is a path forward:
- Industry member organizations have been working on these types of problems, i.e., data naming standards for a long time. But there is more work to be done. With RFID, we now have yet another set of activities on data. Get involved.Trading partner working groups for Transportation industry—or more importantly, driven by the shippers. The Byzantine approaches to paper and layers of organizations who touch shipments have got to be addressed. There are many industry organizations in Auto, Retail, Healthcare, Food, etc. that are focusing on data standards and quality—but Maritime seems to be left rudderless on this at the moment.Simplify the distribution network. Simplify the process.Focus on the problem. Just like any Six Sigma program. What are the key data elements (not all) that we need to drive the process forward? Part of the problem that firms have is when they make their laundry list it is too long. Too much data, too many reports vs. knowing what core information it really takes to get the job done. It is not that additional data is not important, but you have to start with the essentials.Evaluate auto-id/data collection techniques to reduce data entry burdens and improve accuracy.Evaluate shared architecture, On-Demand with the partners you share key processes with. Your trading network lives in the market place, not in corporate, behind your firewalls and you have got to find ways to synchronize your information with these players.And most importantly, evaluate the impact of poor data and make a business case to get the resources and technology to focus on it.
Figure 4
- Continued purchasing of raw materials when product is already marked for End of Life.
- Inventory held in the wrong location to support markets and customer service levels.
- Making buys or placing positions on wrong or out of date technology.
- Missing competitive or market shifts.
- Missing demographics of your market.
- Wrong merchandize mix.
- Inaccurate costs of data used to determine sourcing models.
- Poor or no data on business transition costs (aka, closing a plant, moving to the 3rd party manufacturing, start-up costs in new market, etc.)
- Poor contracts.
- Poor project planning estimates.
Figure 5
Your future is in your markets. That is where the sources of information that can drive improved business can come from.And, with the advent of On Demand, we have an opportunity to rethink what we are doing here—to move to IM rather than IT. That is Information Management rather than Information Technology.