An introduction to Sourcing Optimization - Part 1

Boosting Procurement efficiency and impact with sourcing optimization – using advanced sourcing analytics and scenario modelling for improved negotiation results.

Sourcing Optimization (/ɒptɪmʌɪˈzeɪʃ(ə)n/) in Procurement describes the process of solving complex mathematical allocation problems with powerful computations, using a combination of advanced linear or non-linear mathematical models.

Procurement is a great place to be in – at least if you have a strong stomach and are willing to face off with Volatility, Uncertainty, Complexity and Ambiguity. The VUCA concept has been around for some time, just as the topics being top of mind of every CPO of the past, present and future. Balancing and prioritizing the security of supply, cost savings, sustainability efforts, efficient processes, people capabilities, supporting technologies and the organizational structure required to service the business, just to name a few common topics, will continue to be a challenge.

If this wasn’t enough, CEOs and CFOs continue to up the ante and request increased efficiency and improved impact. They expect more savings from Procurement at reduced operational cost. This really only leaves a limited number of options to CPOs: they must enable their teams to run more sourcing events, touch more spend while delivering higher savings and improve the relationships with business stakeholders and suppliers simultaneously. To achieve this, Procurement needs to embrace digital tools that truly transform the source-to-settle process from spend analysis to sourcing, contracting and purchasing.

Here’s the highlights:

‍·  To meet changing expectations and reach the next stage of their digital journey, Procurement needs to embrace advanced sourcing software  
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·  The complexity, inefficiency, and limited capabilities of today’s sourcing tools drive sourcing managers back to their well-known Excel files
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·   Sourcing analytics in Excel comes with its own challenges: it’s manual, error-prone, time-consuming, and highly dependent on user’s individual ability

Technology can truly support driving efficiency and impact by facilitating and optimizing processes. Especially in sourcing, some technologies have been around for some time but have struggled with low adoption ever since (think about auctions). This is why over the last three years a variety of start-ups have been developing new approaches to the old challenges. These start-ups are rethinking Procurement tools from the perspective of the user rather than the capabilities offered by technology.

With Archlet, we rethink strategic sourcing and sourcing optimization. We believe the associated capabilities for tender management, analytics, scenario modeling and negotiation guidance can help organizations reach the next stage of their digital transformation journey. The modular approach of the product allows organizations to take one step at a time or to leapfrog ahead. Either way, organizations can boost their Procurement efficiency, impact and strategic relevance to the business. We have hosted a webinar to help you navigate the technology landscape and support this introduction to the topic.

Explaining sourcing optimization with everyday technology

Sourcing optimization and the associated technology has been around for over 15 years. Yet, most people haven’t heard of it and struggle with the concept. In short, sourcing optimization refers to the process of solving complex mathematical allocation problems with powerful computers, using a combination of advanced linear and non-linear mathematical models. The complexity in Procurement is introduced through large amounts of information like supplier bids on large sets of items with complex cost breakdowns and secondary information (e.g., capacity limitations, alternative offers, rebates). Furthermore, a variety of business constraints (e.g., switching costs, supplier preferences, risk or performance, etc.) that need to be considered in an award decision.

Because this concept is rather abstract, an analogy from our everyday life might be more useful. Optimization is the concept that helps us manoeuvre through foreign cities and countries with the push of a button. Google Maps has been using optimization for many years to guide us from A to B. We can pick the mode of transportation, specify if the shortest or the fastest route is more desirable. We can exclude toll roads, avoid taking the ferry or whatever else might impact our journey.

One suggested route within the road network is the equivalent of an awarding scenario in a sourcing tender. An awarding scenario describes the outcome with one winning supplier for each item. The shortest travel route might now represent the cheapest option or the best price scenario. Only working with incumbents represents the fastest route. Limiting the number of suppliers or including non-cost parameters (e.g., supplier reliability or sustainability scores) into the optimization will lead you to your most desired route.

Sourcing analytics and optimization capabilities enhance the technology stack

The advanced analytics and optimization features that can guide us through our sourcing events are not generally found as a part of existing eProcurement suites or solutions. While basic analytics capabilities exist with some providers, the more powerful features are usually found in separate modules that don’t share many similarities with their standard sourcing counterparts. Sourcing optimization therefore creates a separate entry in the Source-to-Contract space. This technology enhances the RFx management and auctions offered as part of standard sourcing modules with powerful analytics and scenario modelling capabilities to enable holistic decision making.

Where standard sourcing tools are not inherently intelligent, sourcing optimization introduces Artificial Intelligence and learning algorithms to sourcing. Today, these mathematical models and algorithms support multiple aspects of the sourcing event creation, analysis and optimization. They support information matching processes, detect patterns and learn over time to recommend actions based on past data. It is the connection of many use cases that makes products intelligent and drives efficiency. While AI in sourcing might not predict the future, it most certainly solves some major challenges faced by strategic sourcing managers.

Common challenges in strategic sourcing

Sourcing optimization is often referenced in connection with complex sourcing events. The Cambridge Dictionary defines complexity (/kəmˈplek.sə.t̬i/) as a «state of having many parts and being difficult to understand or find an answer to». Translated to sourcing, this means having many items, suppliers and business considerations that make it difficult to identify the optimal combination of suppliers and items. This is especially relevant, where the best value for the organization requires balancing the cost of goods and services with other decision factors.

Organizations running strategic sourcing projects across commodities and geographies usually face their fair share of complexity, independent of the industry they operate in. While many business requisitions are fairly straight-forward and don’t require much attention from Procurement, they usually also don’t represent a large amount of spend. The most complex events on the other hand require a lot of attention while also only representing a relatively small percentage of the overall spend of the organization. The bulk of the spend is therefore managed in moderately complex events. Events involving 10 items and 5 suppliers can be awarded in 9'765'625 possible ways. This is if we only use price as the single decision factor. The truth for most organizations though is that things are not quite as simple. Additional supporting information are often required to understand supplier proposals, while external and internal business constraints need to be reflected as well. This means that the majority of sourcing events of an organization can be considered as complex in the sense of the definition and therefore benefit from optimization features. We will further review the aspects driving complexity on top of pricing when discussing holistic decision making in Part Two of this blog series.

Complex spend categories require flexible solutions

Unfortunately, the tools available to Procurement teams often limit the ability to design such complex tenders within the tool altogether or at least increase the effort of setting them up drastically. Especially events requiring price breakdowns or trying to capture qualitative information simultaneously often result in sourcing managers opting for their well-known Excel files instead of using existing sourcing tools. This means that all analytics, modelling and subsequent changes or updates will have to happen in Excel as well. While Excel is extremely powerful and flexible, it has some shortcomings as well.

Manual copy and pasting of supplier inputs is highly time consuming and error prone. Without data input validation or outlier detection, a manual verification of provided inputs is necessary, inviting further opportunity to reduce the overall data quality. With the creation of reports for complex events taking anywhere between days and weeks, the data quality challenge rises exponentially. On top, this time is now not available anymore for more value adding activities like scenario planning, negotiation preparation or stakeholder management.

With Procurement often being pressured to release RFx documents that are not 100% complete, many projects require updates throughout the event. This is especially true for events running across multiple rounds. The ability to update the tender analysis based on changing requirements like new quantities or the addition or deletion of items is limited. Changing supplier inputs within or across tender rounds therefore often requires the duplication of the above mentioned efforts, reducing the efficiency of teams even further and resulting in a prolonged event cycle time.

Besides that, complex sheets are daunting to most users, making them feel uncomfortable or intimidated. Complex formulas and multiple cross-references between information increase the risk of mistakes in the analysis, making the search for errors the search for the needle in the haystack. And with scenario modeling in Excel being highly dependent on the individual ability of users to express mathematical problems correctly, many organizations require specialist external support when running sourcing events. This service often doesn’t scale well, resulting in unsustainable investments.

Overcoming the barriers to holistic decision making

Besides these challenges focused on the analysis, the inclusion of additional internal and external information is a challenge for most organizations. Data on suppliers like performance, risk, sustainability or diversity scores is often sitting in multiple disconnected systems, making a consistent application across the organization difficult. The same is true for external market data (e.g., price benchmarks), stakeholder evaluations and soft factors relevant to the overall evaluation. The lack of consistency and availability therefore limits the ability to reuse information or inform future sourcing events.

Sourcing optimization tools offer solutions to many of the challenges outlined so far. In Part Two of our introduction to sourcing optimization we will discuss how advanced technology can help with making holistic sourcing decisions that increase the individual value contribution of sourcing managers while improving the profile of Procurement towards stakeholders and suppliers.

Archlet is a user-first sourcing software company that rethinks strategic sourcing in a way that allows Procurement managers make better sourcing decisions faster. In our blog we discuss different topics around Digital Procurement and advanced sourcing. In this series we explore how to bring sourcing optimization to life and the steps required to deliver the desired value.

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