The approach we take to accelerated implementation is one of flexibility, risk mitigation, and continuous improvement. With this approach, we can begin the work of building the PIM while we still have unknowns around the end product. We have built an internal tool that automates the tedious work involved in configuring a PIM.
- Automated model design: Given a product data spreadsheet, json file, or xml file we have tools that can generate a base data model automatically
- Iterative approach to model refinement: We have tools and procedures that allow the fast iteration of model enhancements. Allowing the customer to see their data in the model and provide quick feedback
- Many common feature requests (workflow, approval processes, taxonomy visualization, etc.) have been genericized and componentized for re-use across clients
- 20+ componentized features around workflow, image manipulation, usability, time to value, and other
- MVP Approach: No “big bang” go-lives. Start using the PIM as soon as it’s better than the current processes
- Inbound and outbound connectors are modularized and built from reusable components. Allowing us to focus our resources on the business logic
- We can ingest data in the format our customers can supply it – Reduces effort on the customer side
- Continuous Improvement: Project doesn’t stop at go-live, continue to refine the solution to provide even more value over time
Some highlights of an accelerated PIM implementation are:
- Shortened discovery time: Just a single 3-day workshop
- Data-driven model development: We use our client’s existing data sources as the basis for developing the core model
- Leveraging existing integrations: Where possible we create connectors to external systems in a way that simulates existing integrations. This allows us to insert the PIM into the sourcing or publishing workflow with minimal development effort from the client or external partners.
While our accelerator program is very flexible and can be molded to suit a variety of customer needs there are some criteria that make a client particularly well suited for the accelerator program.
- Good understanding of their own data
- Well organized product data
- Not a huge initial reliance on print
- Limited set of well-defined data sources and output channels
Pre-configured base models and feature add-ons
- Product Configuration
For us at Aperture Labs, all of our implementations are delivered remotely, with the occasion of having one or two onsite meetings if requested by the client, so we are able to not only continue business as usual, but able to still take on work and new clients with minimal downtime, even with unexpected curveballs.
With the use of cloud-based applications, these are some of the tools we rely on that allow us to effectively collaborate whether in the office or working remotely. Applications such as:
- Trello – allows us to seamlessly collaborate with clients on tasks, work streams, and show high-level progress to both our clients and internally within Aperture.
- GotoMeetings – we use as a means for formal meetings with our clients. Allowing conference calls, videos, and screen sharing to facilitate deep, organized collaboration as well as give demonstrations, training, and knowledge sharing.
- Google Documents – we are able to share documents around projects and also work together to build the models with the clients.
- Sococo – we use this tool internally to work as a team while working remotely to simulate an office environment. Allowing our team members to “stop by” each other’s offices for ad-hoc chats, meetings, and whiteboarding sessions.
- inRiver PIM – as a cloud-based SaaS platform, inRiver lends itself very well to remote working as it is accessible anywhere there is an internet connection.