The shift towards innovation and value creation for procurement and function functions requires leaders to reimagine how work gets done across the source-to-pay value stream. In a post-COVID-19 world, procurement leaders are faced with fresh challenges as organisation prioritise reducing supplier risk and increase supply chain resilience. Procurement leaders will need to transform the procurement function and source-to-pay processes to become strategic enablers who improve competitive advantage.
Industry benchmarks suggest that organisations typically waste 3-4% of their overall spend on excessive transaction costs, inefficiency and non-compliance. This spend leakage is significant, and with revenues being squeezed across many industries, the need to address it has never been greater.
Understanding and adopting the proliferation of digital tools is no longer optional for procurement functions that want to be best in class. Despite this, adoption is slow.
Procurement departments are still in the early stages of adopting technologies such as robotic process automation. According to Gartner, only 8% of procurement teams are using RPA and 73% currently have no plans to adopt RPA at all.
Industry benchmarks suggest that organisations typically waste 3-4% of their overall spend on excessive transaction costs, inefficiency and non-compliance
Source-to-pay is a process that starts with sourcing, negotiating with and contracting the supplier of goods and ends with final payment of those goods. It is a large, complex process that cuts across procurement and finance functions.
Emerging technologies such as RPA and AI mean that over 50% of the source-to-pay process could be automated. Combined with other improvement levers such as process simplification, standardisation and outsourcing, a significant amount of time can be saved to free buyers to work on strategic category management, building and developing supplier relationships and managing supplier chain risk.
Figure 1: Source-To-Pay Process Framework
To unearth opportunities to optimise source-to-pay, organisations should use multiple improvement levers. Combining traditional lean process improvement techniques to remove waste and re-work with various digital and automation capabilities can produce transformational results. Revealing opportunities doesn’t need to be complicated. It simply entails asking the right questions.
Simplification
How might we remove non-value-add activity and reduce waste and rework?
While this question will be familiar for any organisations that have embraced lean, it remains as relevant as ever. We worked with a large telecommunication company and found that the average time from the submission of an existing supplier work package to purchase order approval was 46 days. One of the key drivers was duplication of approvals and excessive approval cycle times. As a result, 95% of suppliers ended up working at risk without an approved purchase order. To address this, process simplification improvements were suggested and delivered which eliminated duplicate approvals.
Standardisation
Is there one best way of carrying out this process today?
In many cases, the same procurement processes are carried out differently across multiple business units, geographies and categories. There are often opportunities to harmonise processes to reduce variation. However, when it comes to category management, standardisation can deliver superior supply chain performance and cost savings by allowing procurement teams to leverage their spend across fewer manufacturers and maximize operational efficiency by managing fewer stock-keeping units.
Robotic Process Automation
Is the organisation carrying out rules-based, repetitive activities?
Robotic Process Automation lends itself to activities that are rules-based and transactional in nature. RPA is suited to source-to-pay activity in which there is no room for interpretation.
A typical RPA use case in source-to-pay:
A majority of companies continue to match invoices, purchase orders and goods/services receipts manually. This work is accompanied by manual resolution of issues like mismatches between the prices and quantities on POs and those on invoices. Automated matching bots can be employed earlier in the process and toward the front-end. Using intelligent character recognition and confidence intervals to automatically identify mismatches helps minimise the need for manual intervention and queries.
Intelligent Automation: Smart workflow
How might the workflow and key rules and decisions be digitalised and automated end-to-end?
Full end-to-end digitalisation of source-to-pay can be achieved with Smart Workflow, a process management software tool that sits between humans and digital capabilities such as RPA to manage the hand-offs and provide real-time visibility on status.
A typical Smart Workflow use case across source-to-pay:
Contract Management
Smart Workflow can be used to automatically scan contracts, extract terms, predict approvals and send remaining documents to procurement resources to process. The length of the whole contract review process can thus be reduced dramatically.
Intelligent Automation: Machine Learning
Are there outcomes that can be predicted using data?
With the right data, machine learning can be used to process tasks that involve more complex rules. By defining the inputs that enable predictions, organisations can automate tasks that would otherwise require human judgement.
Typical machine learning use cases in source-to-pay:
Supplier risk management
Procurement leaders can adopt machine learning to make predictions on supplier risk based on supplier stability and financial viability.
Invoice processing
Organisations are also using machine learning algorithms to match invoice data to the correct spend category, automatically sorting procurement spend into categories and sub-categories.
Intelligent Automation: Natural language processing
How might insights be derived from language translation, semantic understanding and text summarisation?
Natural language processing (NLP) is focused on understanding, interpreting and manipulating human language. For procurement, NLP can unlock insights from textual data. NLP entails applying algorithms to identify and extract the natural language rules such that the unstructured language data is converted into a form that computers can understand.
A typical NLP use case across source-to-pay:
Contract mining
Legal contracts contain valuable information for procurement, including payment terms, termination dates and re-negotiation rights.
Whereas contracts have previously been stored offline or in shared folders and thus not readily accessible to procurement teams, text parsing enables the contracts to be mined for the data. Optical character recognition enables text to be automatically identified within previously un-digitised images including photographs and scans of contracts.
Transition/outsource
Which processes or activities are non-core and don’t require proximity to the central team?
Offshoring or outsourcing of procurement processes remains a viable option to release capacity and reduce cost. Typically, transactional activity is the most obvious procurement process to outsource. This includes typical day-to-day buying activity such as reviewing and approving purchase orders. However, it’s also possible to achieve cost savings for more strategic buying activity such as the management of category groups that aren’t as closely managed. Typically, these are indirect categories.
To increase business value from sourcing and procurement functions, organisations must go beyond foundational approaches. By accelerating digitalisation and combining various improvement levers, procurement leaders can thrive in the post-COVID-19 world.
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