Category Archives: Exact Purchasing

Next Generation Analytics NEEDS to Surface Root Cause Analysis …

… but relationship modelling alone is NOT going to get us there!

In another great article by Xavier Olivera of Hackett Spend Matters, he dives into the topic of how procurement analytics needs to work – from visibility to orientation because current procurement analytics offerings, while reasonably good and actionable at the process level compared to where they were a few years ago, are poor at helping users orient themselves when a specific goal or problem comes into focus.

He notes that when a procurement leader decides they want to improve X, the challenge is no longer visibility. It is knowing which analytics matter for that objective and which do not. But all the analytics platforms give them today is metrics, they don’t give them direction. Even if the user knows what metric to drill into first (because it is the highest, lowest, or outlier), all they can see is the data that contributed to that metric. For spend, the transactions. For a supplier rating, the Net Promoter Scores. For a process, the time in each step.

The users see the immediate “what”, but not the “why”. Why were the transactions high? Is this market price, has the quantity gone up, or is the supplier charging above the agreed upon rate. For a rating, is it because the performance wasn’t up to spec, the delivery is consistently late, or the service/interactions are very poor. For a process, which time was too long (compared to average), unless you can dig into another level (and even then, why it was too long).

According to Xavier, in situations like these, analytics has to work different. When a procurement leader wants to improve contract compliance, the starting point should not be a full review of all compliance metrics, benchmarks and dashboards. It should be a guided path that surfaces the specific reports, KPIs and comparisons most likely to explain the gap, given the organization’s operating context.

Which is a great start, but just surfacing those reports, KPIs, and comparisons that are statistically relevant or deviations from a norm doesn’t explain the gap, it just captures the gap. Not only is it the case that a KPI only becomes meaningful once it is examined in the right context, but it only becomes useful if there is enough data to allow the system to determine, with high statistical likelihood, the root cause and actions to take that could address the root cause (and not just the symptom these systems surface today).

Xavier than tells us that the ability to orient analytics effectively depends on the data’s structure, which is partially right, but doesn’t quite capture the entire requirement. He goes onto state that Procurement outcomes do not arise from isolated transactions … they emerge over time from relationships and analytics is most effective when the underlying data model can express these relationships explicitly. Which is closer. But the reality is that this still isn’t enough for proper root cause analysis.

It’s critical, because without relationships you can’t trace the end metric back to the source data, but just being able to identify the source data only tells you what is fundamentally wrong, not why, or what you need to do about it.

That’s where analytics needs to get to.

If your steel category transactions are high, you can trace back to the contracts and whether or not the rates are per contract, the shipping is per carrier quote, the tonnage as expected, and the breakdown across steel categories appropriate for your current product lines or construction products. If any rates or tonnage don’t add up, you know the issue is the invoices — but you don’t know why they are being paid. Were the new rates not properly encoded? Were the tolerances within acceptable limits and the automatic OK-to-Pay issued despite the mismatch? Are category managers blindly overriding the system because the supplier was threatening late shipments if payments didn’t appear on time?

In Xavier’s example, if contract compliance is low, why? Is it just a few suppliers, or even a single supplier, across a category. If just a few suppliers, are they unaware of the contract because of personnel changeover? Did a new industry regulation adversely affect them? Was it actually the fault of a carrier or sub-tier supplier they had no control over? This is what you need to determine to ensure that compliance actually improves and stays improved.

In other words, you need more than the data, you need models that capture what the data element used in a KPI is, who or what creates the data in the first place (and how they create that data), what the data range and typical mean/median/mode values are, what positively or negatively impacts the data, and what can be done if a shift is desired in the data.

Without this baked in intelligence into the model, even if the root data in the system can be uncovered, a user won’t understand what it means or where to start doing something about it. That’s where analytics needs to get to for analysts to be proactive instead of reactive.

And this is another area where the Busch-Lamoureux approach to Exact Purchasing will help. When you define your categories at a granular level appropriate to to the quadrant of the pocket cube they occupy, you not only know what influences their cost, but what also influences their supply, what defines their quality, and what role third parties (that you may have to monitor) play. You have the foundations for doing real proactive analysis and identifying not only what “good” is but what is most likely contributing to a “not good” metric or data point and what standard options exist to address, and try to improve, the data point (as you need to mitigate high risk and manage high complex categories at a detailed level).

In other words, the future is knowledge-based models that capture more than data points and calculations, but what the data points actually mean and what factors (represented by other data points) directly influence the data points you are analyzing.

When a Conflict Starts, It’s Already Too Late For Procurement To Pay Attention!

Supply Chains are not only hurting, they are breaking, and they have been since the US and Israel renewed the conflict with Iran and more-or-less brought the Strait of Hormuz to a close for pretty much every western country that is associated with the US.

A Strait that is critical not only for

  • global energy (as it normally sees 20% to 25% of global oil passing through it daily)

but also for

  • natural gas (up to 25%, at least it will further delay the AI Data Centers)
  • fertilizer (as it saw up to 50% of urea, ammonia, and sulphur supply passing through it daily, with the former a key fertilizer component)
  • methanol (but at least bootleggers will have to use real grain alcohol now) and petrochemicals
  • etc.

In other words, the Strait being close off is not just a logistics nightmare for the shipments you were expecting that needed to pass through the Strait on time, it’s a nightmare across your entire supply chain as all of your suppliers dependent on the oil, natural gas, chemicals, gasses, etc. that normally pass through the Strait daily are also suffering their own nightmares. Delays will compound through the chain for the lucky ones, and the rest will see shipments just stop.

And articles that tell you this is a leadership moment are missing the point.

Where it was critical, you should already have known your exposure, had monitoring in place, and been alerted the day the conflict started that an issue was coming your way.

Where supplier Force Majeure was unacceptable, you should already have had the flexibility in your contract to shift, pause, or end the contract immediately upon supplier failure.

Where supply was critical, you should have been geographically dual-or-tri sourcing with order escalation clauses built into the contracts so you can quickly secure supply when potential shortages are detected.

Where margins are tight or costs can vary widely based upon external events, your cost models should already be taking this into account, should be monitoring for market price changes, and should be updated upon such changes with immediate alerts if prices shift beyond typical market fluctuations.

And strategic and critical suppliers will already be treated as such. They will be given fair margins, access to buyer expertise that will help them with efficiency and negotiating their own raw material contracts, and placed in a financial position where they too can dual or tri-source and explore optionality in their own supply chains.

Because, as Paul Martyn commented on one of the many articles on why the conflict is apparently time to pay attention and step up (even though, as we stated in our opening, it’s already too late):

If you:

  • defer supplier investment –> you pay in disruption
  • squeeze supplier margin –> you pay in resilience loss
  • ignore (supply chain) optionality –> you pay in constrained decisions and lack of supply

The answer, of course, is to be paying attention to any high risk or high impact category from the day you identify it to the day you end the last product line that uses it. And to use the Busch-Lamoureux Exact Purchasing model to properly place your category, determine which cost factors and risks you need to track, how often, when alerts should be triggered, what mitigations can be taken up front, and what actions need to be taken when an issue likely to cause a disruption arises.

Analytics Must Drive Source-to-Pay, but not necessarily Gen-AI

Xavier recently penned another great piece on Analytics in P2P: From visibility to actionability where he highlighted the failures in analytics in traditional P2P:

  • static, backward looking, spend by category, invoice cycle time, approval rates, compliance rates
  • insights only after transactions are processed, payments are made, and cycles completed
  • late payments multiplying, exceptions accelerating, and supplier risk accumulating
  • lack of operational insight

According to Xavier, P2P can only be modernized if the embedded analytics shift from descriptive to diagnostic.

  • don’t report KPIs, explain the root causes (which approval paths contributed the most to approval time)
  • don’t report exception rates, identify suppliers that consistently cause them
  • don’t report spend anomalies, break it down and identify root causes

It’s a great start, but where it needs to get to is actionability. Xavier begins to address this point by stating the next step is “predictive awareness” where the system anticipates likely outcomes within active processes, such as predicting which invoices are likely to miss payment terms, which requisitions are likely to stall in approval or which suppliers are likely to generate disputes based on current patterns as that allows a Procurement professional to intervene before issues arise.

Finally, Xavier gets to the main point — the real inflection point comes when analytics begin to recommend actions and influence execution paths. Prescriptive analytics in P2P requires tight coupling between insight and control. If analytics identify a high-risk transaction, the system must be able to route it differently, apply additional validation or prompt a specific decision. If analytics detect a low-risk, repetitive transaction, the system must be able to reduce friction without manual intervention.

But it needs to go one step further. It must not only route differently, and apply more controls, but it must still do so automatically based on the diagnostic and predictive analytics. It can’t just apply a “one-size-fits-all” approach for automation and kick every exception out for human processing. You can’t always make the default path smarter because there should be different paths depending on the cost of the purchase, the risk associated with the purchase, the discrepancy between the invoice, goods receipt, PO, and/or contract terms and conditions. You need multiple streams that are auto-selected by predictive analytics that support the right actions given the assessment of the conditions.

The reality is this — except for truly exceptional situations, once you’ve made the decision on what to purchase, procurement should be 100% automated. It’s all e-document exchange, analysis, authorizations, and (payment) transactions. Unless something is really off, a buyer should never be involved once all the workflows, rules, and authorizations are setup.

But this automation should extend back into, and through, source-to-contract. Building on the Busch-Lamoureux Exact Purchasing pocket-cube framework, there are categories that are low risk, low value, and low complexity — you should NOT be buying these manually. “Agentic” automation should be taking care of these for you, considering that even a worst-case screw up will be of little impact. Then there are categories of moderate risk, value, and/or complexity which can be fully automated if all of the necessary data is available and there is a cost and supply history to build on, there are no special situations that need to be taken into account, and a worst-case analysis indicates that even a statistically unlikely “bad buy” will be of minimal impact. These should be 90%+ automated from the decision to buy to the recommended award, with extensive analytics and augmented intelligence for human review. And if the buyer likes the default recommendation, it should be just one click for the process to go from award to e-signed contract.

All of this requires very extensive descriptive, diagnostic, predictive, and actionable analytics and intelligence with extensive, adaptive, robotic process automation ([A]RPA) that can automate everything that should be. The reality is that while everything should be sourced (or exactly purchased), when you have all of the (market) intelligence, the standard processes, and the organizational goals encoded, then there’s no reason that the systems shouldn’t do the majority (or the entirety) of the work for you.

While buyers won’t be replaced by agentic systems (despite the over-hyped BS claims of AI Employees), they will be heavily augmented by them when most categories aren’t complex, risky, or strategic enough to require human review or intervention.

There’s No Cost Management UNLESS It’s By Organizational Design

Cost Management is what thought leaders and analysts have been talking about for 25+ years in Procurement (and is something that has been discussed on SI since its founding in 2006), but not something that is typically realized.

It’s more than just strategic sourcing, contract [lifecycle] management to capture the agreements and obligations, e-procurement, and 3-way matching for cost assurance (and obtainment), but rarely does an organization even achieve these (and that’s why up to 30 to 40 cents of every negotiated savings dollar never materializes).

It’s even more than including Procurement in NPD and NPI (which is where 80% to 90% of the cost is baked in), or in supply chain / logistics network (re) design, which still isn’t the case in the majority of organizations.

It’s a fundamental organizational realignment from traditional budgeting, pricing, forecasting and spend planning based on historical spend and revenue to dynamic budgeting, pricing, forecasting and spend management based on real-time market data as categories come up for sourcing or renewal, internal organizational spend increases or decreases (on hires or fires; internal development projects; assets are acquired, fully paid off, or divested) where budgets are defined based on real-time market data and updated forecasts when a sourcing event is kicked-off, pricing is adjusted based on actual costs and expected market tolerance to standard margins/mark-ups, forecasts are re-run using advanced curve fitting models with the most recent data, and spend planning is adjusted based on all of the prior updates.

The “when a sourcing event is kicked-off” is the key — not when it’s planned, when it needs to happen because the company has decided to introduce a new product, accelerate a planned event due to an expected demand or cost increase, or a supply chain disruption has necessitated emergency replacement of supply.

The harsh reality is that if a chip or RAM factory was just wiped out by a natural disaster or fire (which happens about once a decade), prices are going up. Doesn’t matter what you spent last year, this year is a whole new type of ball game — especially if supply routes become cut off and your only options are longer sea routes, air routes, or new (already overloaded) suppliers in new regions that aren’t cut off.

And any savings or cost avoidance success needs to be measured against the average market price at the time.

But, as pointed out by this article in Supply Chain Digest on how to get From Supply Chain Cost Cutting to Cost Management, this is not what happens every time a market shock hits, executive pressure rises, and the organization is told to take costs out fast.

As the article continues, the danger is not the mandate itself. It is what repeated, reactive cost-cutting does to the supply chain’s long-term health. It can lead to diminishing returns on cost cuts, weaken operational effectiveness, and narrow options the next time volatility strikes.

And it’s all due to a hidden problem with the traditional approach. Namely static budgets create the wrong conversation. Because, when supply chain performance is judged primarily against an absolute dollar budget, leaders often get pulled into debates about compliance instead of outcomes and, even worse absolute-dollar metrics can also steer attention toward the biggest cost line items, even when those costs enable profitable growth.

According to the author, the solution is to ditch static dollar budgets, assess performance through an adaptive lens that aligns with margin assessment, and report costs as a percentage of revenue. Which is great advice, but doesn’t really help you transition the organization to being cost management (vs the current method of cost mandating that is completely divorced from reality and regularly results in organizational failure) focussed.

That’s where the Busch-Lamoureux Exact Purchasing model comes into play. When you align around exact purchasing, and segment your spend into the pocket cube, you realize that for all of your high complexity, high risk, and/or high impact categories, you need to either architect the cost model and the supply chain around it, monitor market conditions in real time (and possibly trigger [re]-sourcing events as a result), or continuously monitor input pricing as well as the price points an average consumer will pay across your markets at different volume levels and adjust your cost and revenue model accordingly.

You no longer plan around fixed costs and prices for the next year, that never happens, but around evolving market realities. And if your price point adjustments are limited, then you know you need to scale back on service commitments, marketing during a downward market trend (when consumers don’t have time to buy), or overpriced sales personnel just adding to expenses with no identifiable return. i.e. Spend is reallocated as appropriate to keep the organizational profitable and productive during extreme events or market conditions while other companies can’t adapt due to lack of category management structure and organizational alignment around what is actually being bought as they still operate off of a spreadsheet that represents a fictional model of non-reality.

The Kraljic Matrix is NOT a Foundation for Future Fit Supplier Segmentation

A recent piece over on Procurement Leaders noted how the author had several recent conversations about how the Kraljic Matrix has become outdated (and, as per our series last week, it has) and how one consumer goods company came up with their own approach to supplier segmentation to “leverage critical supplier capabilities to maximise value”. More specifically, he company has focused its supplier segmentation on two completely different matrices: first, the level of engagement; and second, suppliers’ ability to execute commercial growth and capabilities in an attempt to allow the company to do is to segment suppliers based on the strength of their relationship and the specific value they should bring to the business.

And, in effect, shift the Kraljic matrix from “noncritical, leverage, bottleneck and strategic” to “transactional, essential, visionary and strategic”.

It’s progress, but not much. It’s making the same error that every analyst firm (and even analyst) is making, and that’s thinking that segmentation can be appropriately captured by a 2*2.

As per our series last week on what the Busch-Lamoureux Exact Purchasing framework really is, it’s not a matrix, it’s a pocket cube* — which accomplishes the goal of the Kraljic matrix by appropriately segmenting categories in a manner that allows them to be properly managed from a supply-assurance based Procurement perspective. This is the point you need to start from if you want to create a supplier segmentation strategy for appropriate supplier management.

Then you see it’s not just

  • transactions (transactional in Exact Purchasing)
  • essential (governance in Exact Purchasing)
  • visionary (risk monitoring in Exact Purchasing)
  • strategic (architecture in Exact Purchasing)

Because

  • transactions can be low impact (and non-critical) or high impact (and create a bottleneck if they don’t show up)
  • governance can be accomplished at the spend level if the spend is low impact, but needs to be relationship level if the spend is high impact
  • risk monitoring is enough (and no vision required) for low impact spend but detailed risk management with mitigation plans that involve strategic, and maybe visionary, relationships will be key for high impact spend
  • strategic can be accomplished through cost architecture and mitigation strategies for low impact categories, but require detailed supply chain architecture with supplier participation in the high impact categories

This means that there are at least seven categories that need appropriate supplier management — all of the high impact transactions, plus the cost architecture (as you need supplier input), market risk management (as you need supplier relationships to rapidly shift demand), and relationship governance (as you need cooperation to manage obligations). And the degree of management depends on the categories.

Plus, to make matters even more difficult, some suppliers will cross multiple categories — which means that you can’t just put them into the most intense management category and treat all interactions as interactions in that category. You have to take the category into account, and focus the management on what’s critical, not what isn’t. Management requires HUMAN INTERACTION, and you only have so many people with so much time to build the RELATIONSHIPS, so you have to focus based on the category being supplied.

In other words, it’s not a matrix, it’s a cube that manages the supplier based on the category impact to the P&L, the market risk (that lies primarily with the supplier or the supply chain they introduce), and the complexity (where the supplier needs to be able to produce items that meet the complex requirements). And suppliers who supply more than one category will fall into more than one bucket.

In other words, to fix supplier management, first fix Purchasing.

(And that’s why it’s so critical to Take Purchasing.)

* and, one that’s different for every industry, which might make it a 4-polytope, but since each company can customize the pocket-cube, we’ll stick with the pocket cube