Our retail team sees patterns every day — whether it's a macro-summary of a metroplex transportation plan relative to new housing starts or a planogram showing how a retailer will reset their store for the coming fall season. Patterns of consumer behavior take shape in a physical form: the shopping center. “When I see a piece of property now, I see a pattern of anchors and outparcels; locals and nationals — but primarily influenced by location determinants that relate to maximizing a developer's return, rather than just ‘what will look nice,’” says my colleague Tim O'Brien, one of Little's retail design directors. “On a different scale, those same patterns become a merchandising plan — a ‘lease document’ for the sale of shelf space, with varying degrees of maximum margin opportunities,” adds Nicole Vachow, a senior visual strategist I work with at Little. It's interesting that consumer patterns are at once somewhat nebulous and then so clear and concrete. For example, you may never be able to predict when the next “Hot Topic” will manifest, but you'd hesitate in a heartbeat about locating an Anthropologie adjacent to a Dollar Tree. Perhaps more provocative is that there exists perfectly clear data that suggests a similar outcome — if only it could be harvested sensibly. Although isolated, the merchant and the developer both have analytical software that provides predictive analytics: one for identifying the demographic content of a region or precinct that suggests optimizing a developer's return on investment; the other for improving a retailer's sales and gross margin.
Why Link GIS Data and POS Data?
This hyperbole begs the question: is it possible to link these separate pools of data? Better yet, if gaining insight from the data assists both retailer and developer in making accurate decisions faster, then great. Why not integrate software that is data driven and flexible through parametrics (meaning that you input the data that defines a design component's attributes). The approach is called a “building information model,” or BIM.
Through our direct contact with AutoDesk, the maker of Revit (a leading BIM software developer), we are constantly evaluating the platform's ability to be a central repository for all kinds of data — not just things that architects and contractors need to know about. As our CIO Chris France puts it, “there is little difference between the concept of linking data related to many aspects of the retailer and the concept of Enterprise Resource Planning (ERP), which is a mainstay for corporations globally.” While ERP systems and processes took nearly a decade to integrate, conventional wisdom suggests that tying merchant and developer specific data to a BIM is entirely possible and relatively expedient to implement. It is my opinion that the most effective “place” to link data related to merchandising (micro-scale) and development attributes (macro-scale) is within the construct of the actual plan — therefore creating a “virtual shopping environment” that has multiple value-laden uses.
While I believe the integration of data into a “building information model” is a work in progress, my purpose in providing the following application examples is to reinforce with the developer and retailer that progressive design professionals are focused on what we call “technologies & processes that provide results beyond.”
Shopping center developers need to consistently focus on the goal of maximum return on investment. Using a building information modeling platform to design a shopping center will start with the land plan itself, while the designer focuses on populating data fields that relate to tenant type, rental rate and rate of return, tenant adjacency criteria, cost ofand service requirements. When laying out the property, instead of only “thinking” about the physical constraints and opportunities on the land, the designer will be automatically generating table information that gives the developer insight into how well the center will perform financially. The developer, of course, will add value to the equation by providing additional data criteria specific to the goals of the project. So, imagine your designer at the earliest phase of the project, giving you an accurate read on the pro forma aspects of the project. Could you imagine the increased speed and accuracy of your project's initial direction?
For the retailer, similarly imagine your store planner/designer populating data fields related to merchandise specific fixtures. When the designer draws “lines on the page” and arranges fixtures around the store, there's an immediate response in table data, which indicates the volume of merchandise, category balance, and even gross margin/return on investment data. While there are numerous planograming software platforms that do similar things, there is a huge gap — these tools are not used until after the design is cooked. In fact, planogram software is currently reaching its peak utility when analyzing on-going store sets, but not necessarily for initial design. Could you imagine the result of your creative, brand-enhancement focused designer being able to simultaneously address the practical, performance-based objectives of the store design at the earliest stages of putting pen to paper?
A Rally Cry
It is time to close the gap between these disconnected data streams. The technology is available for those who have the insight to practically integrate data into the designer's bag of tricks. I am convinced that there is direct, business-oriented value for both the developer and the retailer. If only I could get the industry at large to remember one thing: Good things are coming and you need to expect the most from your design professional.
BY BRUCE A. BARTELDT JR., AIA
National Retail Studio Principal, Little Diversified Architectural Consulting.