What Does Social Media Mean to Your Supply Chain?
If social media is powerful enough to tighten the bonds between brands and consumers, is it powerful enough to tighten each link in your supply chain?
By now, most of us are familiar with the retail notion of the “Connected Experience,” or, the personalized relationship that develops between customer and retailer. In one way or another, most of us are connected customers, having forged deep relationships with the brands of our choice.
From the perspective of the supply chain professional, the Connected Experience puts us one step closer to answering the most ubiquitous question of all: what do my customers want to buy?
The Power of Enterprise Resource Planning
The absolute real-time nature that is inherent in social media can act as a blessing and a curse for professionals overseeing a supply chain. In one sense, access to real-time data can help supply chains run ultra lean – as proper analysis can lead to producing just enough product to meet consumer demand.
For example, imagine you could predict the percentage of customers that were interested in purchasing black sneakers versus brown sneakers. This would empower you to stock your shelves with only the most necessary quantity of each style.
With the real-time capabilities built into Enterprise Resource Planning (ERP) software – especially ERP software outfitted with Customer Relationship Management (CRM) features – retailers are able to make these types of strategic predictions. Working together with social media, these systems provide instant analysis of customer data and interaction that can be used to make real-time supply chain adjustments. In fact, it was not uncommon over this past holiday season to see retailers analyzing customer data pulled from social media.
While ERP/CRM integration coupled with social media analysis means a leaner supply chain for retailers, it ultimately translates into a closer connection with the consumer. Even a global retailer can take on the persona of the mom and pop shop down the street.
Of course, as perfect as this all sounds, there exists two giant paradoxes built into two assumptions:
- Real-time data is always an accurate indicator
- A large percentage of your customers are actively interacting with your brand in social media
The Real-Time Paradox
Think for a moment about the notion of “real-time.” How often are the real-time decisions in sync with final purchasing choices?
For instance, imagine a customer expressed interest in the aforementioned pair of black sneakers through online activity (e.g., either by “liking” or Tweeting about them). If you aggregate this data quickly and combine it with similar insights from other social media channels, it would make sense to predict an increased demand in black sneakers.
But imagine that this interest in black sneakers is based on little more than the excitement of the new product. In other words, there is a strong correlation in social interest for a new product, but not a shared correlation in buying behavior. Acting too quickly on real-time interest produced in social channels can reverse the benefit of running a lean supply chain, and instead leave local shops fat with unwanted inventory.
Now, shift this example away from sneakers and into more complex goods, such as automobiles or major appliances. The risks of more expensive stops along the supply chain quickly grow.
The China Paradox
Earlier this year, analytics firm ForeSee Results found that social media is driving just 5% of visitors to retail websites. But across the world in China – recently named by CNBC as the world's hottest emerging retail market – an Internet population of 404 million trusts brand information from social media three times more than from an acquaintance’s recommendation (per 2010 Global Web Index data, cited by Ogilvy's Andrea Fenn).
In Fenn's article, “Social Media & China: Why & How,” Fenn cites China as a fertile social ground that is already being capitalized on by brands. To succeed in this social landscape, brands must adapt to certain peculiarities of the Chinese Internet culture. Not only does this include heavy use of “Made In China” social destinations, but also western social networks such as Twitter and Facebook.
This helps to sum up what I refer to as the China Paradox. While named for this market, it is defined more by questions that can affect us as we seek to operate a lean supply chain:
- Is our customer data segmented appropriately across all markets to ensure one large faction is not skewing our data?
- Have the peculiarities of any given culture been taken into account prior to any decisions being made?
Is Software Our Solution?
Is ERP software a solution to these paradoxes? The answer, of course, can be both “yes,” and “no.”
ERP systems are perhaps the most powerful tools we have at our disposal in analyzing customer data. But the recommendations made from this data are only going to be as strong as the data quality and how well that data is interpreted.
When you integrate social media analytics into your supply chain strategy, think of the data as an accumulation of individuals instead of a singular group. Consider the demographics of your social media data, and think about how you will monetize your inferences. In doing so, you will be in a better position to see the benchmarks being established, especially as they relate to correlations between social activity and your bottom-line.
For example, by spending time investigating your data, you may find that an increase in social activity pertaining to black sneakers only results in increased buying activity during fall, and primarily on the East Coast.
Even more interestingly, some research has found an increase in social activity is followed by sudden spikes in buying activity three months down the line. This may indicate that a small, yet influential, group of followers buy early, and then encourage the purchasing decisions of their social networks. Analyzing data through this type of lens can help encourage a new level of strategy in our supply chain decisions.
Understand, too, the cultural peculiarities of any group and the risk of looking at all social data in aggregation. Social media data, like the traditional data used to make supply chain decisions, ebbs and flows, from one extreme to the next. This is where behavioral analysis – especially from those embedded within your markets – can be invaluable in humanizing the ERP intelligence data.
Ultimately, software will never be the stand-alone savior that helps us capture the power of social media, any more than social media itself is the stand-alone savior for operating a lean supply chain.
Rather, using cultural, historical, and sales data, along with social media, holds the potential to connect brands and consumers more tightly than before. And of course, inherent in this tighter connection, will be a leaner and more profitable supply chain.