Now that we're all connected and responding 24x7 via any number of devices, of course there would be a loud corresponding call to have a "real-time supply chain," too.
A complex world, running on follow-the-sun supply chains, requires a hyper-connected and super responsive operation that goes beyond best-guess demand planning and forecasting, right?
Some industry experts claim that the day for real-time supply chain practices has come -- and is on the verge of being more mainstream, thanks to a multitude of cloud data management tools and increased corporate adoption of new supply chain software platforms coming to market. However, there's also acknowledgement that a necessary foundation for moving efficiently at real-time speed -- supply chain analytics -- is still very much at the beginning stages of development at many companies, and will take time to build out.
A real-time push
Some claim that the day for real-time supply chain practices has come -- and is on
the verge of being more mainstream thanks to a multitude of cloud data-management tools.
On one hand, there's evidence of increased interest in real-time supply chain support tools to address things like supply chain traceability, multi-level inventory optimization, demand signal repository, sales and operations planning, and leveraging point of sale data, officials from Bloomberg Businessweek Research Services and SAP said during an April webinar, "Supply Chain Innovation: The Quest Towards the Real-Time Supply Chain" (you can listen to the archive here
And, yes, webinar panelists highlighting recent survey results noted that, not surprisingly, forecasting improvement remains top of mind for a sweeping majority of the 318 executives polled. Seventy-seven percent of respondents said demand and supply forecasting and planning tools were very important in achieving their company's 2012 objectives; and 80 percent said forecasting will be important in 2014.
On the other hand, upgrades and new tool implementation take time; webinar panelists said they expect to see software tool upgrades and replacement cycles pick up steam in the next couple years. Larry Marion, a consultant for Bloomberg Businessweek Research, said:
One interesting observation in all this is the interest in real-time [supply chain management]. We hear this all the time and see this in many surveys we manage. It's clear that it's not going to be easy to move these batch systems into a real-time environment. But there is a real interest and momentum in this area.
Building the analytics base
What's more curious, though, as we peel back the layers of this survey, is how much attention supply chain analytics appears to be getting.
According to the survey, 73 percent of the executives indicated that supply chain analytics tools are important to meeting their company goals. And with 71 percent of respondents noting that current analytics tools need to be more predictive and go beyond providing information about prior performance, there's an equal amount of respondents -- 73 percent -- who are planning to upgrade or replace their analytics tools within two years to gain these more predictive features, Marion added. Much of the interest in using analytics stems from being able to better manage the supplier base, figure out where the best-practices are, and determine who's delivering material supplies in the shortest amount of time with the highest quality and reasonable prices, he said.
Maybe I'm making a leap here and connecting dots that aren't meant to be connected, but isn't it interesting that in a broad discussion about real-time supply chain management, survey executives appear to want more predictive analytics capabilities to help them make faster decisions and be more responsive to uncertain supply and demand needs?
Here's the rub. Analytics -- or more specifically, analytics software -- won't be a quick fix in closing existing supply chain gaps. To do this right, companies have to invest a considerable amount of money and resources in developing an analytics foundation before they can even run the nifty algorithms embedded in the software.
The underlying data that companies want analyzed actually has to be accurate first, and not many companies can say that's true about their existing data. And, with the volume of data that is consistently being generated everywhere, how do companies find and implement ways to manage and do something meaningful with all these inputs?
Bill Roberts, a consultant for Bloomberg Businessweek Research Services, Triangle Publishing Services, had this to say, adding insight from a survey-related interview he had with a semiconductor executive:
You need to get the underlining systems right before you can build analytics capabilities on top of them. I'm going to quote him [the semiconductor executive] at length here because it's interesting: 'Analytics is the culmination of years of investment in the basic tools. You need the underlying databases; they need to be maintained and structured in a methodical and rigorous way. You need technology that allows basic reporting. These are all key to get value from analytical tools.' He added that he and his staff for the last year, year and a half, have spent fully half of their time building analytics capabilities on top of their existing supply chain tools. I thought that was an interesting way of [noting] his priorities.
With that in mind, analytics (and, importantly, analytics done well) could be a big leap forward in terms of supply chain innovation. The question, then, is how much is that innovation worth to your company, and what kind of bet are you ponying up to make it reality?