Customer Success Story

Polaris Looks to Dakota Systems for Master Data Expertise

Polaris Inc. is a $5B manufacturer of ATVs, motorcycles, snowmobiles, electric vehicles, and watercraft. From the outside-in, Polaris looks like a customer experience rock star with state-of-the-art digital capabilities. Recreational vehicle shoppers can configure their dream ride online using 3D imagery and email their design to nearby dealerships to check available inventory. Customers use smartphone apps like RideCommand™ to map their trail routes and track friends they’re riding with, in real-time.

Under the surface lay a sobering reality. Since being founded in 1954, Polaris grew rapidly through acquisition, so its information systems were siloed, poorly integrated, and needed updating. Data didn’t flow seamlessly across the company. The engineering Product Lifecycle Management system (PLM – including 3D CAD tools) had been upgraded to a best-in-class system, but many critical downstream processes relied on spreadsheets to relay master product data from one department to the next – including getting 3D data to the digital team for online product configurators. 

Accessories and products were managed in different ERP systems. Fitment of accessories to vehicles was maintained manually. Even when new vehicle releases were minor variations from last year’s model, all of last year’s accessories needed to be manually assigned to the new models, taking days of work to map thousands of relationships. The result was a significant degree of manual effort and rework to manage product data for every product launch. 

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Dakota compiled the first high-level view of the end-to-end flow of critical product data through Polaris and all its business processes, from product concept through dealer delivery.

Polaris IT leaders recognized the need for master data governance and management, so they engaged Dakota Systems for help. The Polaris team had prepared a set of questions for Dakota. What should be managed as Master Data? Do we need Master Data Management (“MDM”), Product Information Management (“PIM”), or both? How do we organize master data governance? Who should be the data quality stewards?

To answer those questions and others, the Dakota team designed and facilitated a series of design-thinking working sessions for each of the major functional areas – manufacturing, engineering, product management, marketing, sales and dealer operations, digital, and support. Business process owners, data stewards, and IT leads attended each session. Dakota led the Polaris team through a series of interactive exercises to document the current state of product data including critical business process inputs, outputs, and systems. For each function, participants documented what was working, what wasn’t working, and emerging ideas for the future that held promise. 

When we were done, Dakota compiled the first high-level view of the end-to-end flow of critical product data through Polaris and all its business processes, from product concept through launch, from supply chain to dealer acceptance, from order to delivery. Dakota defined 18 desired-state future capabilities for master data and their gaps versus the current state. We road mapped 20 gap-closing actions so Polaris had a path to resolution with timelines and cost estimates. This gap analysis gave Polaris perspective on the magnitude of the business impact, the scope of the master data requirements, the systems involved, the impacted business processes, and the potential solutions including technology, master data architecture, governance, and change management. On reviewing the output from this first phase, one executive exclaimed, “Dakota knows more about Polaris than we do!”

Given a shared understanding of the current state and the opportunities for improvement, the next step was to lay the foundations of master data management. This included the development of a product master data model, a governance process, and PIM/MDM system requirements.

The product Logical Data Model spanned vehicles, options, packages, and aftermarket accessories. Dakota developed a conceptual data model that aligned the commercial view of the products (how product managers, customers, and dealers view the products and options, including pricing, base models, trim levels, and bundles) with the engineering and manufacturing view (vehicles as Bills of Materials (BOMs) with subsystems, modules, and parts). This hierarchical product model had to allow for “fitment” information (which accessories fit which models) and enabling reuse of fitment across model years and product lines. It also had to allow for creating and managing rules that constrain what could be bundled and sold together (even though an accessory or an option package fits a model it might not be offered for purchase).

Rather than invent new business and work processes for managing product master data, the Dakota team looked for existing compliance processes that could be expanding to include master data. Polaris had recently updated its Product Delivery Process (PDP) – the phase-gate process used to manage new product introductions. Dakota conducted “conference room simulations” of a product launch with Polaris product teams to validate the product data model.  The simulation helped determine which master data objects were needed at each phase gate, when they were created, by whom, and in which system. Dakota created value stream maps for the product master data flows and added the master data elements to a swimlane diagram of the PDP. This process not only validated the product data model, but also created validated documentation of the master data governance process, and gained alignment between IT, business leads, and product lines. Future updates to the product delivery process will inspect for master data at each formal phase gate review.

“You helped us have this conversation, which we needed to have for a long time.”

Alex Mireau, Polaris Program Manager

Finally, the Dakota team developed detailed functional requirements for a PIM/MDM platform, which the Polaris team used for vendor selection. At Polaris’s request, Dakota recommended a shortlist of vendors whom we were confident satisfied the requirements.

At the end of our collaboration with Polaris, they were ready to drive change. They had a roadmap for master data management for products, understood the costs and benefits of PIM and MDM, had alignment between IT and the business, and were able to clearly communicate the need for change to senior leadership as well as to individuals in the work process. As the manager of a strategic program remarked, “You helped us have this conversation, which we needed to have for a long time.” With help from Dakota, Polaris had a solid foundation of business and technology readiness for PIM and MDM. 

Dakota has helped companies like Agilent Technologies, Polaris, CommScope, Kohler, and TE Connectivity develop product information strategies that work.

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