A conversation with Jason Purviance, Chief Information Officer, ModeOne
Q: At what point does mobile data collection become a systems-level risk?
Jason Purviance: Mobile data collection becomes a systems-level risk the moment it’s not governed like a system. If collections are handled as one-off activities instead of standardized, repeatable workflows, risk grows fast. At enterprise scale, the problem isn’t just potential data exposure it’s loss of consistency, auditability, and control across matters, devices, and teams. If you can’t demonstrate process discipline and repeatability, you have operational risk.
Q: How should enterprise IT teams support legal teams during time-sensitive matters?
Jason Purviance: Speed is important, but speed without guardrails creates downstream problems. IT should enable legal teams with pre-approved tooling, defined workflows, and clear escalation paths. The structure needs to exist before the urgent matter shows up. When the controls are already built into the process, legal can move quickly without improvising or introducing unnecessary risk.
Q: What operational weaknesses tend to surface first as collection volume increases?
Jason Purviance: Inconsistency shows up first. When the tooling or workflow doesn’t scale, people start compensating manually. That leads to uneven chain-of-custody records, handling variability, and increased error rates. What works at small volume often breaks under sustained demand. Scale exposes process weaknesses very quickly.
Q: How do you assess whether a mobile data workflow is truly enterprise-ready?
Jason Purviance: It has to be repeatable, observable, and controlled. You should get consistent results regardless of volume, geography, or operator. If success depends on a specific expert or special-case handling, it’s not enterprise-ready. Enterprise workflows shouldn’t rely on heroics they should run predictably.
Q: Where should CIOs look for hidden costs in mobile data collection?
Jason Purviance: Most hidden cost is downstream. Over-collection that drives review cost, storage costs and manual handling that slows timelines, or poor documentation that forces rework later. You have to evaluate the full lifecycle, collection through processing and review not just the initial acquisition step. That’s where the real cost profile can show up.
Q: What operational signals suggest a solution won’t scale long term?
Jason Purviance: Heavy manual steps, weak automation, limited audit visibility, and inconsistent outputs are all red flags. Another signal is when operational effort increases faster than volume. A scalable platform should reduce friction as usage grows, not add more operational burden.
Q: How does system design influence privacy and custodian confidence?
Jason Purviance: Privacy controls should be enforced technically, not just procedurally. When scope limitation and data targeting are built directly into the workflow, custodians understand what is and is not being collected. That builds trust, reduces resistance, and lowers exposure risk. Architecture matters more than policy language here.
Q: What role does automation play in maintaining defensibility?
Jason Purviance: Automation removes variability. Standardized logging, automated audit trails, and enforced scope controls ensure every collection follows the same pattern. From a defensibility standpoint, fewer manual touchpoints mean fewer opportunities for mistakes or challenges to the process.
Q: How should CIOs evaluate vendors from an operational scalability standpoint?
Jason Purviance: Look past feature lists and demos. Ask how they operate at scale. Can they show consistent execution across large volumes and different environments? How do they handle platform changes and edge cases? Scalability is demonstrated through operational maturity and repeatable outcomes not marketing claims.
Q: Why is treating mobile data collection as an enterprise system so important?
Jason Purviance: Because ad hoc approaches fail under load. Once volume increases, informal processes break down. Treating mobile data collection as an enterprise system gives you control, repeatability, and resilience. Systems built with discipline perform under pressure.
Closing Perspective
Jason Purviance: When mobile data collection is governed and engineered like any other enterprise system, it becomes manageable and defensible instead of risky. CIOs who focus on process discipline, repeatability, and lifecycle oversight can support legal and compliance needs without sacrificing control as demand grows.
Enjoy our FAQ’s? Check out our FAQ with Ryan Frye, covering mobile data collection, scale, and innovation, or our FAQ with Matthew Rasmussen, covering iOS updates, iPhone 17, and mobile data security.