Source: whichplm.com
After a momentous 2019, ending with unexpected international travel lasting up to two days before Christmas, we were thankful to finally use the holiday break to sink into our cozy family room couch with our dogs Lilly and Oliver, browse our OTT app of choice, and catch up with the latest entertainment. We stumbled onto the second season of Lost in Space, which we binge- for the next couple of days.
Without giving away any spoilers, the first episode, Shipwrecked, finds the Robinson family trying to leave a toxic planet to return to the mothership, the Resolute. Yes, you may say that we are suckers for a good sci-fi show, but what was so interesting in the plot was how Maureen Robinson used first-hand information generated by the systems installed in the Jupiter (their ship) to guide the family off the treacherous planet. While she did do some number crunching by hand, the data she relied on was misleading and incomplete, sending the journey off track, almost sinking the Jupiter in the acid sea hole and killing the entire family. Dr. Smith included.
Most certainly, your company is not the Jupiter and, hopefully, your team is not trying to get back to the Resolute. However, this opening episode made me think of the relevance of data and its pivotal role in transforming the operation management of any fashion company trying to, if not scale up, survive — certainly a goal for many out there.
When it comes to the way product data is assembled, collected, stored, and shared, how would you rate your company? While you may think of your PLM application as fundamental to all production and design efforts, just as Maureen Robinson was relying on the information of the Jupiter, you’d be shortchanged to think that you have all you need to make key decisions that may usher you into business success. The truth is that misinformation can make you or break you, and relying on unilateral data to set up important business governance would be a huge miscalculation. Don’t get me wrong, a PDM is a must-have for establishing a strong foundation for any business managing a sizeable style portfolio, but by no means is it the Holy Grail.
Maybe the writer behind Maureen Robinson didn’t have to enhance the story by correlating the information available to her with other variables to improve the quality of the data. That would have had a different outcome, for sure. We’ve seen myriad clients struggle with how to manage their sizeable internal data sets and make decisions based on the outputs of a siloed enterprise system to turn customer data into intelligent and actionable insights—insights that come available to be shared real-time with key stakeholders, enabling informed decision-making which impacts the course of their operations. When clusters of different pieces of information come together to conform data, it becomes very powerful in decision-making. This clustered information that is combined purposefully makes a difference between what is plain information and actionable data. This is what many have coined as big data, a term that is getting some attention in the fashion runways. Well, maybe not the runways, but the alleyways of the folks in charge of making it all come together seamlessly with systems that inform multiple workstreams that it takes to put a piece of clothing on the market.
And while imagination can fuel the way technology ecosystems come together, just as it created the complex systems of the Jupiter, the real concern is that if data doesn’t come together to inform decision-making, it will certainly sink your business. Once you have a system in place, like a PLM, it is relatively easy to manage data if the information is reliable, nomenclatures are consistent, and upkeep protocols are followed according to plan. But for instance, imagine for a moment if all other enterprise systems in place are able to comfortably “talk” to each other and “mingle” happily together in a normalized environment. Suddenly, you have opened the valuable data contained in your PLM that is arrested to some and generated clusters of information accessible to a bigger pool of employees whose own tasks and responsibilities depend on the foundation of product data contained in the PLM. As Mark Harrop would call it, a “data lake.” I like to think of it as the democratization of data. And it is a real thing, by the way.
Big data is a term used to describe a collection of data that is huge in size, often systematically conformed from multiple sources. It is the process of democratizing the data that makes it big data. A problem with big data is that it grows and changes constantly, and organizations struggle to leverage the opportunities to capture actionable insights by the aggregation of other variables supplied by siloed systems. Corporations already spend huge amounts of money furnishing capabilities that serve vertical teams: a PLM is a system used by production and design, an ERP is used by finance and merchandising, a DAM is used by creative teams, etc. One could argue that these are useful and considered staples in any company ecosystem, but what happens when a key executive would like to see a wider view of how a specific category of products has performed? For example, all the types of support that a skew had, what worked and what didn’t, and key metrics of all of the tactics in the market – not after the fact, but right now. It may also be relevant to examine specific efforts that went into support, from advertising all the way down to social, PR, CRM, and credit obtained from sending samples to specific outlets, including wholesale. This is the essence of a true 360-degree approach. Do you run your team down to the ground for days to get reports that are full of holes and errors and only provide insight into a static window of time? What if the meeting is postponed? Do you have to go back and recreate all that work for the next meeting to reflect updates? It happens more often than you think – and if it happens to you, well, you know how crippling it is.
But, “Danger, Will Robinson!” When senior leadership plays no role in enforcing this data aggregation nirvana, things can go wrong very quickly. The democratization of data is a companywide commitment, and while it resides with functional teams, with the support of information leadership, it really begins with strong support and vision from the top. This is a reality behind some of our most successful implementations. Governance is key here, and reports and planning flow generated with big data should be a requirement embedded in the exiting processes of the organization for reporting and planning. Teams should get hands-on and be comfortable with new capabilities while being encouraged to explore the possibilities that aggregated data provides. In our experience with data aggregation implementations, we’ve seen that after the initial shock is overcome, teams become very excited when they see their time cut in half to generate things that used to take days, if not weeks. Also, the visibility they now have, usually starting from the PLM, has been a game-changer, as they can now better realize the importance of their contribution and the value behind having real-time visibility in the variables that can turn things around in the performance of seasonal efforts. Lastly, teams also realize the importance of collaboration as a key factor for success. When interactions in the company are now fueled by information, more intelligent conversations will start to occur, and folks will come together with a different perspective of what their roles are to influence the bottom line.
If we live in an online world, it only makes sense that the systems that help us do our job are available to enable us to fish information from the data pond upon request and without a stumble. In a right-here, right-now economy, it is important that your systems are knit together to give you an edge with the consumer demand and the competition. Data aggregation is a must-have. Today’s society is on-demand, and it thrives on information. It is big data that will boost you forward, just as it helped the Robinsons get out of the acid planet at the end.