In our personal lives, we’re empowered with data at our fingertips on one device all day, every day. So why hasn’t the same access to actionable, real-time information spilled over into all areas of the business world?
The data experience gap
We believe data capture is a significant and overlooked cause of this data experience gap.
Most data in our personal lives is fully digital. Almost all companies, however, need to collect, analyze and act on data relating not only to digital assets, but also tangible assets and physical operations (such as inventory, equipment, warehouse and store operations, patient care or last mile delivery).
And unfortunately, data capture – the process of collecting and digitizing information from the physical world – is much harder than harvesting data from digital assets. A clothing retailer can collect and analyze e-commerce data almost instantly. The same process in their brick-and-mortar stores, however, still relies on frontline workers scanning millions of individual barcodes.
This problem of data capture holds back improvements to how employees, customers and businesses can collect, access, interpret and utilize data to make timely and informed decisions.
The state of data capture today
The state of data capture today can be summarized by two key elements:
1. Processes to capture data are outdated and inefficient: Capturing data from tangible assets and physical operations still relies heavily on manual processes. Even where technology (such as hand-held scanners) has been introduced, it is generally confined to capturing one item at a time and embedded in repetitive manual workflows.
2. Frontline tools do not deliver instant, easy-to-use data insights. Analytics tools are designed for desk-based workers. Mobile employees or customers in-store lack easy-to-use, mobile tools that can identify real-world objects and connect them with real-time system data.
Enterprises have accelerated their digital transformation efforts over the last few years, but one key area is lagging, namely the capture of data in the physical world. Smart data capture is a compelling solution to overcome this challenge at scale while leveraging the devices we all carry in our pockets.
These two factors impact not only efficiency but also customer experience, employee experience, business resilience, flexibility and speed of decision making. Logistics errors, for example, cost the pharma sector alone a staggering $35 billion every year.
- Frontline workers: Store associates, pharmacists, delivery drivers, field service engineers and many more are not empowered with tools enabling data-informed decisions. Data democratization initiatives have not reached the frontline.
- Customers: The interactive, personalized experience consumers are used to in e-commerce is not replicated in brick-and-mortar stores.
- Businesses: Desk-based decision makers often work with data from the frontline that is incomplete, inaccurate or outdated. On average, 60% of SKUs are affected by inventory record inaccuracies.
We believe data capture can be smarter
We believe the technology is available to transform data capture. And we believe implementing a smart data capture strategy is the key to unlocking the next level of business efficiency and customer and employee experience.
Whether in our personal or professional lives, our use of data has become ubiquitous and essential to every task we do. However, PAC recognises that so many interactions with the physical world continue to increase complexity and friction leading to a data experience gap. The key to addressing this is transforming how people interact with tangible assets to collect actionable data. Smart data capture can enrich existing experiences across complex workflows, like supply chains, in a seamless and digitally led manner.
The goal of smart data capture is to efficiently capture, combine and analyze multiple data sources (barcodes, text, IDs, objects) and instantly surface rich, actionable insights.
Smart data capture enables real-time decision making, employee and customer engagement and workflow automation at scale. Unlike the old way of data capture, it isn’t quantified by a simplistic measure of items counted over time but by exponential productivity gains, richer business insights, increased employee satisfaction and enhanced customer loyalty.
The 9 principles of a smart data capture strategy
For over 10 years we have been uncovering smarter ways to capture data. Through this we have developed 9 principles of an effective smart data capture strategy.
1. Shift tedious work from people to technology
Use technology to restore bandwidth and rehumanize the employee experience.
Smart data capture does not seek to replace jobs, but to improve them. It reduces the amount of time employees have to spend on tedious, error-prone manual data capture processes.
2. 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, judgment and problem-solving. Mobile computing, machine learning and augmented reality (AR) all create new opportunities to connect the frontline.
3. Empower customers everywhere
Make interactive product information, stock levels, promotions and personalized offers as accessible in store as they are online.
While they started off as a way to streamline checkout, smart retailers are now building AR overlays into self-scanning smartphone apps to help consumers locate and compare products and promotions. Rounding out the customer experience in this way increases engagement, conversion rate and basket size.
The ability to accurately capture real-time product information is a transformative force for both customers and organizations. This capability revolutionizes customer-facing applications and enables flawless accuracy in self-scanning functionality, with augmented reality offering enhanced insights such as product reviews or allergen information. Additionally, supply chain applications will greatly benefit from enhanced insights into trailer, cube, and weight utilization rates, leading to optimized trailer loads and improved delivery efficiency. Smart data capture is a technology whose time has arrived.
4. Design for humans
Be user-centered. Smart data capture solves for the reality of people’s daily work and lives, particularly where this involves hybrid digital/physical workflows.
When developing e-commerce, social or chat apps, you don’t need to worry too much about what else the user is doing. But designing for target users such as warehouse workers, store associates, delivery drivers or in-store shoppers requires observational research to understand how humans interact with physical packages, parcels, palettes and products.
5. Give data instant purpose and value
Design solutions that deliver accurate, comprehensive data and insights instantaneously – rather than hours, days or weeks later.
Smart data capture delivers accessible, actionable insights to frontline workers at the moment of data collection. It also enables instant, reliable and more complete reporting back to head office.
In order for REI’s store employees to deliver best-in-class expertise and service with ease and confidence, our tools must give them the data and insights they need, in the moments they need them.
6. 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.
An example is the common situation where multiple different barcodes are printed on a single sheet, label or price tag. Smart data capture uses contextual, visual cues to identify the right code to scan, rather than the user having to do this.
7. Integrated, multi-modal 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.
The real world is unstructured and variable. There’s no single “magic bullet” data capture technology that can solve for every scenario and use case. Flexible, multi-modal approaches are key to capturing data in a more accurate, precise and useful way.
8. 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. This includes smartphones, tablets, drones, fixed cameras, robots and wearables as well as dedicated data capture devices such as barcode scanners.
9. Reach beyond human limitations
Go beyond what unaided humans are capable of, even in optimum conditions and with all the time in the world.
For example, it’s not always possible for a driver delivering age-restricted goods to identify a fake ID just by examining it. However, if you scan the ID and apply machine learning algorithms, this can detect anomalies invisible to the naked eye and highlight a likely fake. It prevents fraud, bakes regulatory compliance into workflows and creates a clear audit trail.
4-step strategic roadmap for smart data capture
We have worked with thousands of companies in making their data capture smarter. While this strategic roadmap naturally draws on our experiences with companies integrating the Scandit platform, it is applicable to any smart data capture project.
1. Identify a single smart data capture use case
A smart data capture strategy is iterative and often starts with a single use case.
In many ways, smart data capture is a greenfield opportunity. Even simple changes, rolled out in a matter of weeks, can result in dramatic productivity improvements.
Authentic user insights and attention to hybrid digital/ physical workflows are key to identifying high-value use cases. Best practices from similar companies who have implemented smart data capture solutions and methods such as work diaries, field visits and interviews are a good place to start. These can all reveal opportunities to improve productivity, improve data quality or better connect frontline workers and customers.
Define what success would look like and set your KPIs.
Store associates are a retailer’s most significant ongoing investment. By empowering them with smarter data, we can improve employee experience, productivity and efficiency in a single stroke.
2. Evaluate smart data capture solutions
- Core data capture performance: Don’t neglect the basics. Smart data capture fundamentally depends on accurate capturing of data, so you need to make sure the solution you choose performs with speed and accuracy in real conditions. Make sure to test solutions at an early stage in your own environment with your own data and workflows.
- Multi-modal data capture and analytics capabilities: Select software platforms with multi-modal data capture and analytics capabilities, rather than single-use applications. This will allow you to adapt and scale in the future.
- Integration effort: Consider your in-house IT resources and select platforms with flexible integration paths. Pre-built user interface elements, ready-to-go enterprise integrations, no-code smart data capture apps and fully customizable options are all available depending on your internal resources, expertise and timelines.
Think outside the box for hardware. You may not need to invest in hardware at all. If you do, today’s consumer smartphones and tablets are often more than sufficient for smart data capture.
Smart data capture is specialized. Consider what expert support will be available to you from ideation and solution design to implementation and beyond.
3. Integrate and roll out
De-risk integration and rollout by paying attention to user experience and onboarding.
User Experience: Smart data capture connects the physical and digital worlds. This means that situational and environmental factors affect the way a user interacts. Make sure you plan on-the-ground user testing into your integration. Pre-built user interface elements or specialist support from smart data capture UX experts can also accelerate the design process and reduce risk.
SAP believes the best user experience is the simplest. By incorporating smart data capture into our business processes we are able to transform user experiences down to just a few simple user interactions.
Onboarding: We’ve found that while frontline workers are often sceptical of new solutions, once they see the impact of smart data capture on their day-to-day, they very quickly come round. Focus on making the onboarding process intuitive and easy to get them to this “aha!” moment as quickly as possible.
4. Expand to transformational impact
Once you’ve implemented your first smart data capture solution and measured success and ROI, look for ways to expand. For example:
Add additional modalities: Enrich your smart data capture application with additional modalities – for example, combining barcode, text and object recognition for retail shelf monitoring and localized inventory, or adding ID scanning as well as barcode scanning to last mile delivery or airport passenger processing.
Expand to other business functions: Port the smart data capture strategies you’ve developed to different business functions. A retailer, for example, might start by adding smart data capture to a B2C app, then expand into an employeefacing app for store operations.
Build out richer analytics: Deliver richer insights to employees and customers – for example, not only scanning and tracking medical device consumption before surgery but adding analytics that verify products are in-date for patient use.
Networks have evolved to now offer gigabit connectivity, devices have evolved to now give us mixed reality, driverless vehicles and drones are becoming feasible, and consumers’ insatiable appetite to do more digitally will continue to see exponential growth; it is about time the capture of data evolves too. Every vertical should be thinking about smart data capture as traditional ways can no longer support the growing demands of today’s workforce. All businesses today should not solely be focussed on cost reductions, but instead use technology to drive revenue and empower the workforce in tandem as part of a two-fold approach for workplace transformation.
The Scandit Smart Data Capture Platform
Scandit is one of the world’s leading smart data capture companies. It was founded to capitalize on advances in smart device technology, enabling collection of data from tangible assets and physical operations to happen in a fundamentally different manner to existing data capture methods.
The Scandit Smart Data Capture Platform is a flexible software-based platform that benefits from continuous innovation to adapt and evolve in changing business environments. It automates scanning of barcodes, text, IDs and objects and supports more than 20,000 models of smart devices.