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    Home»AI Technology News»How a furniture retailer automated order confirmation processing
    AI Technology News

    How a furniture retailer automated order confirmation processing

    Editor Times FeaturedBy Editor Times FeaturedMay 19, 2025No Comments9 Mins Read
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    Photograph by Jessie McCall / Unsplash

    Promoting custom-made furnishings on this age of mass manufacturing is just not simple. However this mid-sized, Europe-focused furnishings retailer was making it work. Their secret? Letting prospects select all the things — from material selections to couch leg kinds, even all the way down to the colour of ornamental nails.

    Nevertheless, as gross sales grew, the made-to-order created a serious drawback. Every order was distinctive — completely different materials, {custom} options, and particular necessities. The workforce needed to fastidiously deal with every customization, create detailed specs for suppliers, and guarantee each particular request was appropriately manufactured. When suppliers despatched again order confirmations, the actual problem started.

    With an 8-week order cycle, processing delays meant prospects waited with out updates. Order backlogs grew, damaging critiques elevated, and 20-30% of all orders have been experiencing some type of error or problem. They wanted a technique to course of these paperwork precisely with out hiring extra employees.


    The actual value of handbook provider order administration

    The provider paperwork arrived as complicated PDFs — some as much as 16 pages lengthy, in a number of languages, and with completely different technical notations. Their seven-person operations workforce spent 10-15 hours per week per individual processing these paperwork. That is 70-105 hours weekly simply matching codes and verifying particulars.

    At a median hourly price of 180 SEK for operations specialists in Sweden, the handbook processing was costing them roughly 655,200-982,800 SEK (€59,600-€89,400) yearly in direct labor prices.

    On high of that, the handbook course of resulted in 20-40 order errors throughout 100-150 month-to-month orders. It meant both the shopper needed to be compensated or the wrong merchandise needed to be offered off at a loss. The potential losses resulting from incorrect order might find yourself costing €12,000 month-to-month.

    To sum up, the processing inefficiencies had main downstream results:

    • Prospects left ready for updates about their orders
    • Incapacity to offer correct supply timelines
    • Rising damaging critiques particularly mentioning poor communication
    • Time spent correcting errors managing and promoting off returns
    • Alternative value of expert workforce members doing handbook work
    • Further hiring wants as order volumes grew

    Automation appeared like the apparent answer. Nevertheless, their distinctive processes and excessive degree of customization meant they needed to discover a system that might deal with their particular wants. They wanted one thing that might not solely course of complicated PDFs precisely but additionally adapt to their cautious, detailed verification course of whereas working seamlessly with their present methods.


    Why conventional order affirmation processing failed the retailer

    Let’s check out how this retailer’s order dealing with workflow appeared like.

    • Buyer locations order on their web site
    • Order flows via their e-commerce system, Crystallize, into their ERP, Enterprise Central, as a gross sales order
    • Crew manually collects these orders 2-3 occasions weekly and makes use of inner filters to pick out the suitable provider for the order
    • Creates Excel recordsdata for suppliers detailing what must be manufactured
    • Suppliers ship again order confirmations confirming what they’ll make and once they can ship
    • Order affirmation information is manually extracted and matched to gross sales orders
    • Order affirmation quantity and promised supply dates are added to Enterprise Central for matched gadgets
    • When all gadgets in an order are matched, prospects are knowledgeable the tentative supply information
    • As soon as the product is in manufacturing and transit, suppliers ship packing lists
    • Crew verifies these in opposition to gross sales orders to make sure every merchandise is being readied
    • Continia is used to create POs from these packing lists
    • These assist mark gross sales orders for supply and schedule product launch of their warehouse administration system

    This complicated course of created a wierd workflow the place buy orders have been created after receiving packing lists moderately than earlier than inserting orders with suppliers. This uncommon strategy was vital as a result of they collected web site orders on particular days earlier than sending them to suppliers. Moreover, not all gadgets in a buyer order would go to the identical provider, which means elements of a single order may arrive at completely different occasions.

    Moreover, three extra components made this course of notably tough to automate:

    Variations in product listings

    Since customization was on the core of their enterprise, they wanted to trace every part of a {custom} order individually. So a {custom} couch received’t be recorded as a single merchandise in Enterprise Central however as separate line gadgets — one for the couch mannequin, one other for the material alternative, and extra for particular options like bronze nails.

    Nevertheless, the provider usually lists all these particulars as a single merchandise of their order affirmation. For instance, if a provider confirmed ‘Valen three-seater in Blue material with bronze nails‘, the workforce must match this single entry to 3 separate strains in Enterprise Central. This complicated construction made processing order confirmations notably difficult.

    Language and notation variations

    The furnishings firm’s suppliers used completely different languages and technical notations of their paperwork. One provider used English with German technical notations, whereas one other blended Swedish and English phrases. This made matching with gross sales orders notably difficult as a result of Enterprise Central wanted clear, standardized product codes.

    So, even one thing easy like metal nails might seem in a number of methods — as a technical code in a single doc, in plain English in one other, or as a German notation in a 3rd. The workforce needed to manually interpret and translate these variations throughout information entry to make sure correct matching. 

    Particular case dealing with

    Some orders required particular dealing with guidelines. As an illustration, when an order affirmation was marked as ‘Showroom’ as an alternative of getting a buyer reference, it wanted completely different processing because it wasn’t tied to a buyer order. 

    The workforce needed to first spot these distinctive instances, then apply completely different verification guidelines — including extra steps to their handbook processing. This meant always switching between completely different procedures relying on the kind of order they have been dealing with.

    Break up orders

    Prospects might order gadgets that got here from completely different suppliers. For instance, a buyer may order a settee from one provider and a footstool from one other. 

    So when order confirmations arrived, the workforce needed to fastidiously match every to the precise elements of the shopper’s order in Enterprise Central. Since confirmations got here individually from completely different suppliers, they wanted to trace which gadgets have been confirmed and which have been nonetheless pending — all whereas making certain they have been updating the right line gadgets for every product.

    They tried numerous instruments, together with Continia, however they could not successfully deal with these complicated paperwork whereas sustaining the accuracy their course of demanded. They wanted a versatile answer that might precisely extract and interpret inflexible, prolonged PDFs whereas adapting to their particular workflow wants.

    That is once they approached us at Nanonets.


    How we automated the retailer’s order affirmation processing workflow

    their complicated order dealing with course of, we knew automation wanted to occur step-by-step. We began with order confirmations. We constructed a versatile workflow that might automate the method from receiving provider paperwork to updating Enterprise Central with supply dates. The thought was to make use of this as a basis for different potential workflows, like packing record processing.

    Here is a fast overview of how the automated workflow labored:

    • Crew forwards order confirmations to a devoted e mail tackle or uploads them to a Dropbox folder
    • Our system identifies the provider format and applies related processing guidelines
    • For every doc, our mannequin:
      • Extracts order references, product particulars, and supply dates
      • Finds corresponding gross sales orders in Enterprise Central
      • Maps provider product descriptions to appropriate Enterprise Central codes
      • Identifies particular instances like showroom orders
    • Nanonets flags gadgets needing overview:
      • Amount mismatches
      • Product code discrepancies
      • Unmatched gadgets
    • Crew critiques flagged gadgets via easy interface
    • System learns from corrections
    • As soon as verified, updates Enterprise Central with supply dates

    Right here’s how we went about fixing completely different challenges of their doc processing workflow:

    1. Automated doc consumption:

    We established dependable doc consumption channels by configuring e mail forwarding guidelines and organising Dropbox folder monitoring. This eradicated the handbook downloading, sorting, and classifying of order confirmations. The system routinely detects new confirmations and routes them for processing.

    2. Product matching:

    The largest problem was matching provider product descriptions to a number of Enterprise Central line gadgets. 

    So, we constructed an identical system that:

    • Begins with precise description matching
    • Falls again to fuzzy matching when wanted
    • Filters outcomes based mostly on further standards like upholstery codes
    • Handles the “one-to-many” drawback (one provider merchandise to a number of Enterprise Central strains)

    When a provider lists “Valen three-seater in Blue material with bronze nails” as a single merchandise, our system can now routinely determine and replace the corresponding couch mannequin, material, and particular function strains in Enterprise Central.

    3. Provider-specific guidelines

    Every provider’s paperwork required {custom} dealing with:

    • For provider A: The system extracts article numbers and variant codes from product descriptions, checking “Choices” fields for particular options like ornamental nails
    • For provider B: The system handles blended Swedish-English phrases and matches based mostly on product descriptions and portions
    • For each: Further verification steps for upholstery codes, kinds, and particular notes

    4. Managing exceptions

    To deal with their particular instances, we constructed particular detection and processing guidelines:

    • System identifies showroom orders routinely
    • Handles cut up orders by monitoring a number of confirmations
    • Processes particular product codes with particular guidelines
    • Flags exceptions that want human overview

    The interface lets the retailer overview these exceptions effectively. After they make corrections, the system learns from these adjustments — bettering future extraction and matching accuracy.


    The ROI of automated provider order administration

    Inside 3-4 months, the automated system delivered measurable outcomes throughout 4 crucial areas:

    • Processing time lower from 70-105 to 40-50 hours weekly
    • Full elimination of order backlogs
    • Means to deal with rising order volumes with out further employees
    • Built-in with Klaviyo for automated buyer communications
    • Proactive order updates all through the 8-week order cycle
    • Fewer damaging critiques and buyer inquiries
    • Early detection of product mismatches earlier than manufacturing
    • Month-to-month financial savings of €12,000 from error prevention
    • Operations workforce shifted to value-creating actions
    • Growth into the German market with the identical workflow

    What moved the needle most for the retailer? Our system’s means to precisely course of complicated PDFs – it’s one thing they did not anticipate might be achieved successfully. Even 16-page paperwork with blended languages and technical notations at the moment are processed precisely.

    They’re additionally planning to increase the automated workflow to their Germany-region operations for the reason that course of would stay the identical, roughly. The one distinction can be the language – one thing that Nanonets would have the ability to deal with seamlessly.



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