The retail industry has faced unprecedented disruption over the past few years. Between the rise of ecommerce giants like Amazon, pandemic-related restrictions and supply chain issues, and fast-changing consumer shopping habits, retailers have struggled to keep pace.
Many legacy processes and systems still prevalent in retail simply can’t provide the speed, flexibility and insight needed to satisfy and retain customers today. A recent survey found that 64% of retailers feel their operations infrastructure is slowing them down, while 57% believe they’ve already lost customers due to poor service and experience issues.
This mounting pressure makes intelligent automation solutions like robotic process automation (RPA) extremely appealing. By deploying software bots to handle repetitive, manual workflows, retailers can shift their human talent to more impactful work while driving far greater efficiency.
Sizeable Cost and Productivity Opportunity
An analysis by McKinsey estimates that RPA could save retailers 15-25% in operating costs while boosting productivity by 20-40%. And according to a study by Blue Prism, 78% of retail senior leaders report seeing material profit margins since adopting automation.
Forrester predicts that by 2025, half of all retailers will turn to intelligent automation, enabling an average of 30% savings across key functions. Extrapolated across a giant retailer with $50 billion in annual sales, that represents up to $15 billion in savings – an enormous financial impact from RPA adoption.
Translating these dizzying efficiency stats into human terms, RPA helps leading retailers shift the time spent on repetitive tasks from ~70% of an employee’s workweek to less than 5%. The recovered hours get reallocated to customer-impacting initiatives, a far better use of human ingenuity and talent.
Broader Transformational Benefits
Cost efficiency tells only part of the RPA story. Additional compelling benefits for retailers include:
Higher processing speed – Software bots handle work up to 5X faster than human pace. They don’t take breaks, get interrupted or switch tasks – allowing processes like reporting, data migration and purchase order creation to happen in near real-time.
Reduced errors – By minimizing manual workarounds, RPA cuts retail process error rates by 20% to 50%. This improves decision-making, financial performance and regulatory compliance through better data quality.
Enhanced scalability – Unlike labor, software bots can scale instantly to accommodate peaks in seasonal order volumes, returns etc. This helps retailers keep up with spikes in activity.
Tighter security – Bots enable strict user control protocols for accessing confidential retail data like customer information, with full auditing. This reduces risks of data theft or unauthorized access.
Improved compliance – With detailed audit logs and monitoring capabilities, bots create transparency that simplifies compliance. Retail processes also grow far less vulnerable to inconsistencies or human lapses.
Cost avoidance – By deskilling repetitive tasks that once required specialized (and expensive) talent, RPA drives significant labor cost reductions over time while maintaining output consistency.
Platform for innovation – Perhaps most profoundly, RPA alleviates the retail “innovation tax” – the inertia imposed by dated legacy systems, inflexible processes and constant fire drills. By injecting speed, agility and insight into operations, RPA liberates human creativity to transform retail experiences.
But where exactly can RPA make the biggest difference for retailers in practical operational terms? Below we explore some of the highest-ROI and most frequently-cited use cases.
Top RPA Retail Use Cases
1. Cashier Reporting
For any brick-and-mortar store, aggregating sales data across registers to generate daily/weekly cashier reports is a must — but also a tedious manual burden. Employees typically have to extract figures from each register or POS database then manually input them into reporting templates to create consolidated views.
RPA removes this drudgery by automatically:
- Pulling registered sales data from source systems
- Structuring extracted data as needed (items purchased, quantities, payments etc.)
- Accurately populating reporting templates without human effort
This ensures cashier reports are produced significantly faster – daily reports in <60 seconds rather than hours. The reports also grow far more accurate and consistent when created by bots vs. manual approaches. Employees can then better utilize the reports for insights into customer purchasing patterns, guidance for inventory orders and other analytics use cases.
2. Invoice and Payables Processing
Processing supplier invoices and payables continues to drain retail finance teams. Typical challenges include:
- Manual data entry across procurement, accounting and ERP systems
- Complex matching purchase orders to invoices
- Long approval chains
- Difficulty finding and fixing exceptions or errors
RPA bots excel at many of these repetitive finance operations – unlocking big savings. After scanning paper or electronic invoices, they can extract key details for coding. Bots then input the digitized data into multiple backend systems to trigger processing, payment and accounting.
Bots also automatically flag any invoice abnormalities for human review, such as mismatches detected between purchases orders and supplier charges. This logic check helps spot problems before downstream issues emerge.
By automating 80-100% of payables processing using this approach, retailers have cut invoice costs by 50% to 75%, sped cycle times by over 80%, and reduced errors substantially.
Real-World Examples of Payables RPA Success
UK grocery chain The Co-op launched an automation initiative that cut invoice processing costs by 75%, while improving accuracy to 100%. RPA also enabled The Co-op to integrate supplier invoicing data directly with its general procurement system, reducing duplicate entries.
Similarly, leading UK department store John Lewis saved ~175,000 processing hours annually by deploying RPA for payables and expense management. Bots helped slash the time spent validating expense claims by over 95%.
3. Returns Management Optimization
Managing product returns and exchanges remains largely mired in manual efforts – but it doesn’t have to be. Processing each return requires significant employee time across numerous tasks:
- Checking the validity of returns requests
- Adjusting inventory figures across multiple enterprise systems
- Calculating and issuing accurate credit to the customer
- Coordinating warehouse/logistics operations if needed
Rather than tackling such repetitive work, retailers using RPA can fully automate returns handling:
- Initiate workflows – Bots trigger configured workflows as soon as a customer initiates a return request
- Update systems – Key details like affected SKUs get seamlessly reflected across connected retail systems – POS, CRM, inventory etc.
- Handle credit – Integrations with payment systems allow bots to directly issue refunds or gift cards
- Notify stakeholders – Customers and internal teams get updates on return status through automated notifications
- Enable self-service – Chatbots now allow customers to independently process returns without agent assistance
These capabilities make returns processing faster, more accurate and far less costly for retailers, while also providing superior customer experiences.
Leading retailers using RPA for returns and other contact center workflows are seeing major efficiency gains. For example, The Very Group cut returns processing time from 11 minutes to 30 seconds using chatbots and RPA, saving thousands of hours annually.
4. Supply Chain Optimization
Modern retail supply chains contend with immense speed and complexity. Keeping shelves perpetually stocked while minimizing waste requires coordinating intricate workflows across suppliers, manufacturers, distributors, warehouses and logistics providers.
RPA helps tame this supply chain complexity through smarter, continuous inventory orchestration:
- Inventory tracking – Bots monitor on-shelf availability, backroom inventory levels, inbound supply etc. in near real-time
- Shortage alerts – Machine learning models forecast demand swings and notify when inventory stocks may soon be depleted
- Automated reordering – Using programmatic bots, retailers instantly trigger supply replenishments if stocks hit predefined thresholds
- Data aggregation – By combining inputs like historical orders, promotions calendars, market events and more, forecasts grow vastly more accurate
In essence, RPA becomes the connective tissue linking crucial supply chain steps. This prevents costly out of stocks while optimizing spend on inventory holding, logistics and waste.
An analysis by Deloitte estimates that RPA could save retailers 8-12% in supply chain costs through tighter coordination and visibility. With average retailer supply chain costs nearing $60 billion, that translates to $5 billion or more in unlocked savings.
inventory management success stories
UK online grocery Ocado deployed RPA and warehouse automation to help optimize perishable inventory management across picking, quality control and packing processes. The robots not only improved speed and efficiency, but also boosted order accuracy to over 99% and cut food waste by 40-50% – creating enormous savings.
Similarly, leading UK retailer Tesco has tested using automated drones to perform real-time inventory checks instead of error-prone human counting. Initial results suggest drones can slash the time needed from several days to under an hour. Drones also boost accuracy from 63% to over 99% while eliminating shutdowns or restricted access needs.
5. Marketing Personalization
Delivering targeted digital marketing and promotions tuned to each customer’s needs is hugely impactful for conversion and sales. But for most retailers, one-to-one personalization at scale remains extremely difficult without automation. Challenges include:
- Constantly obtaining fresh customer preference and behavior data from purchases, web traffic etc.
- Ingesting this data across siloed marketing tools
- Skillfully translating insights into customized creative for each persona
- Iteratively optimizing campaigns and offers based on response
Powerful RPA solutions can overcome these personalization barriers to drive immense value from CRM and campaign automation:
- Dynamic profiling – Bots build rich customer records by continually aggregating data from POS, ecommerce and other sources to reveal preferences.
- Campaign creation – Leveraging integrated creative tools, bots generate customized digital/email content and promotions for microsegments.
- Testing & refinement – Bots tweak messaging or offers for different customers based on response patterns to optimize sales lift.
- Multi-channel coordination – Personalized push notifications via mobile apps expand campaign exposure and conversions.
Such RPA-powered personalization unlocks major commercial results. Top retailers using these tactics see email open rates and click-throughs improve by 20-30%. Higher online and in-store campaign engagement directly fuels increased sales and customer lifetime value – with one retailer reporting a $24 million annual revenue increase from personalization.
Emerging Innovation Will Supercharge RPA
As remarkable as current RPA applications are, they merely scratch the surface of intelligent automation’s transformative potential for retail. When layered with artificial intelligence, advanced analytics and process mining, RPA grows far more versatile, insightful and value-creating.
AI for Unstructured Data – Machine learning algorithms can teach software bots to handle forms, emails, scanned documents and other unstructured data – unlocking process efficiencies beyond narrowly-defined repetitive tasks.
Enriched Analytics – Augmented analytics tools give bots intuitive, real-time dashboards with data visualizations, alerts and recommendations that help them continuously optimize work quality and output.
Hyperautomation – By connecting RPA with complementary technologies like BPM, OCR and NLP, retailers can automate entire processes from end-to-end, eliminating more manual effort.
Process Discovery – Before automating processes, analytics tools first help retailers intelligently map them. Process mining provides x-ray-like visibility to enable maximum transformation via RPA.
Self-Healing Bots – With enough training, machine learning allows bots to recognize problems in their work, adapt approaches independently without human oversight and know when to escalate issues. This self-learning ability makes them true digital workers.
Conversational Interfaces – Chatbots and virtual assistants create simpler, more engaging bot-human interactions for managing RPA tools, querying data and handling external requests.
Ultimately, this fusion of automation, AI and next-gen IT turns RPA bots into versatile, self-learning and continuously-optimizing “digital colleagues” rather than simplistic scripted labor. They tackle the most complex, knowledge-intensive processes at extraordinary speed, quality and scale.
Just as profoundly, intelligent automation liberates human talent to focus on the creative, emotional, analytical and strategic challenges essential for sustaining retail innovation. This makes emerging technology not a threat to retail jobs, but an enabler of more meaningful and impactful work.
Getting Started With Retail RPA the Right Way
The business case for RPA and AI adoption has never been stronger for retail. But where should leaders start on this automation journey?
We recommend taking an iterative, use case-driven approach focused on key operational pain points first, like cashier reporting or returns processing. Prove out ROI through targeted pilots before attempting full-scale rollout across the organization. Patience and phased expansion bring better long-term results than a rushed big-bang implementation.
It’s also wise to secure buy-in early from both executive leadership and frontline staff who will interact with automation daily. Make training on working alongside bots integral to adoption success. Users must become confident leveraging RPA as collaborative “digital colleagues” rather than disruptive threats to human jobs.
Governance is another vital pillar that enables retail RPA scale and sustainability. Define policies for bot procurement, development, change control, performance oversight and maintenance early on. Plan bot workforce expansion cautiously based on pilots. Leverage CoEs and CoBs to ensure organizational alignment.
As tempting as it is to “boil the ocean” with automation, restraint and focus often bring better outcomes. Keep RPA centered on highly repetitive tasks offering clear ROI based on costs, throughput or quality defects.
Reinvest a share of RPA savings into innovations beyond operations – from unrivaled customer experiences to frictionless stores powered by computer vision and sensors to blockchain transparency across global retail supply chains.
Done thoughtfully in this manner, intelligent automation in retail ceases being just a cost play. Instead it lays the foundation for fulfillment transformed through predictions, virtual reality enhanced shopping and lifelong customer loyalty built on awareness and trust.
The Future Beckons
In the world of retail, the only constant is change – and the pace of change today is utterly unforgiving. Disruption has become the norm. To stand still means falling behind.
Intelligent automation provides the key to unlocking retail’s next phase of growth, relevance and human impact by overcoming the barriers of dated technology, static processes and idle time. RPA and AI can help retailers do far more than just keep pace with change – they enable getting ahead of change.
The robotics revolution reaches far beyond narrow task elimination. Its ultimate destination lies in elevating human creativity, empathy and purpose in every facet of retail. The future beckons those bold enough to envision it. The time for intelligent automation is now.