Logistics runs on data. Real-time data visibility is essential to optimize operations, empower employees, communicate with customers and plan for peaks.
A smart data capture strategy is an integrated hardware, software and connectivity strategy that modernizes how employees, customers and IT systems interact with tangible assets and physical operations.
The 9 Principles of Smart Data Capture
For over 10 years we have been uncovering smarter ways to capture data. Through this we have developed 9 key principles of an effective smart data capture strategy.
Shift tedious work from people to technology
Use technology to restore bandwidth and rehumanize the employee experience.
Upskill frontline workers
Empower frontline workers with data-based insights that maximize the unique skills they have that machines can’t mimic – such as empathy, judgement and problem-solving.
Empower customers everywhere
Make interactive product information, stock levels, promotions and personalized offers as accessible in-store as they are online.
Design for humans
Be user-centered. Solve for the reality of people’s daily work and lives, particularly where this involves hybrid digital/physical workflows.
Give data instant purpose and value
Design solutions that deliver data and insights instantaneously rather than hours, days or weeks later.
Make data capture versatile and resilient
Design solutions that automatically adapt to different and challenging scenarios, instead of putting the burden on users to adapt.
Integrated, multimodal platforms
Develop or use platforms that analyze multiple data sources (e.g. barcodes, text, IDs, objects), integrate these with analytics and can evolve and scale.
Use any smart device, anywhere, any time
Be device-agnostic. Smart data capture software is powerful, and can utlilize any smart device with a camera as an advanced data capture tool.
Reach beyond human limitations
Go beyond what unaided humans are capable of.
A 4-Step Strategic Roadmap for Smart Data Capture
1. Identify a single use case
Smart data capture strategies are iterative and often start with a single use case. Even simple changes, rolled out in a matter of weeks, can result in dramatic productivity improvements.
Use best practices from other companies and authentic user insights to identify a high-value use case to begin with.
2. Evaluate solutions
Software: Evaluate core data capture performance, multi-modal and analytics capabilities and integration effort.
Hardware: You may not need to invest in hardware at all, or can use consumer devices.
Support: Smart data capture is specialized. Consider what expert support will be available to you.
3. Integrate and roll out
De-risk integration and rollout by paying attention to user experience and onboarding.
User experience: Plan user testing into your integration and explore pre-built user interface elements.
Onboarding: Get frontline workers to an “aha!” moment as quickly as possible.
4. Evaluate and expand
Once you’ve implemented your first solution and measured ROI, use what you’ve learned to expand to transformational impact. Build in additional modalities, expand to other business functions or incorporate additional analytics.
“Smart data capture seeks to balance the critical elements of people, process, and technology by maximizing support for existing technology investments, improving labor-intensive tasks, delivering data transparency and efficiency, and building repeatable, scalable solutions.”
Research Director, Computer Vision and AI, IDC
Strategy Insights and Resources
The Smart Data Capture Manifesto: 9 smart data capture principles, the 6 business impacts of data capture today, and a 4-step strategic roadmap for smart data capture.
One of the UK’s leading fashion retailers integrated Scandit Smart Data Capture into their employee-facing app on Samsung Galaxy XCover Pro rugged smartphones.