What Are the Biggest Organizational Cost Saving Levers?

Every year there is a new survey or research report that will name one to three levers as the biggest cost savings levers in an organization, but it’s really not that simple. For example, the SCMR last year reported on a BCG study and the Hackett Group 2024 Procurement Key Issues Report and said, in Managing Procurement in a Price-Sensitive Environment, that:

  • supply chain costs and
  • manufacturing costs

are the biggest levers for cost savings. And while generally true if more than 50% of revenue is being spent outside the global organization’s many four-wall structures, it’s not true if most of the spend is internal (on headcount, property, etc.).

And it’s not true at all in the current environment in America where now tariffs are increasing costs by up to 145% (and there’s no solution, beyond BTCHaaS) and everything is unpredictable.

Moreover, supply chain is generic — is the cost inefficiency in the manufacturer (and if so, is it in their material and component supply chain or in their operation), the distributor, the logistics partners, or the organizational warehousing and inventory management. And if its manufacturing costs, is the bulk of the costs raw materials governed by commodity markets or in the production process? If the former, you can’t do much. If the latter, the assembly line is your oyster.

And then, even if you find the lever, where is it located? Who has access? Do they have the strength and permission to pull it? It’s tough!

Let’s look across the spend (ignoring tariffs because they are beyond your control):

  • products: low quantity, no lever; high quantity, sourcing if the market conditions are in your favour (or about to not be in your favour, so you lock a contract in early for a small hit); if the product was never sourced before, it’s tail spend which typically sees 15% to 30% overpsend
  • services: low quantity, tiny lever; high quantity, across a nation or the globe, if you take a multi-level view, are willing to work with multiple providers, and apply SSDO (Strategic Sourcing Decision Optimization), 30% to 40% can be shaved off with no detriment in service level
  • logistics: mode matters; intermediate storage matters; FTZs matter; source and sinks matter (if you’re selling in multiple countries, you might want to consider producing from multiple countries); easy to take 10% off just with a better network design, sometimes 20% off with a better network design, smarter load distribution across carriers, more cross-docking (and less intermediate storage), and the most appropriate (mixed-modal) transport plan
  • taxes and tariffs: source and sink matters! and, in some countries, so does minority/diversity/etc.; you can cut these in half (or even eliminate them) with better planning; when tariffs can be 20% or more, this matters
  • warehousing: major cities and hubs are expensive, secondary locations can be a fraction of the cost; and if smartly located, can cut your “local” distribution costs to your “local” stores, plants, offices, and/or customers; for years all the studies said inventory cost can be as high as 25% of product cost; better management (not just JIT, that can lead to more stock-outs and losses than a few extra percentage points) can halve this while reducing stock-out rates
  • facilities: if you’re willing to consider a balance between on-site and remote, shared spaces (and designated lockers), locale of choice, costs (and savings) can vary wildly; millions can be saved here in larger companies;
  • personnel: you pay the best people the best rates and you keep them as the best deliver an ROI multiple that is many times an average Joe; but that doesn’t mean you have to overpay for benefits (and with good negotiation, you can get great benefit plans at below market average rates); this can be hundreds of thousands to tens of millions

There are many levers, and the savings potential differs by industry, company size, organizational Procurement maturity, and individual company.

In other words, don’t just look at the top two or three levers, look at all of them and focus on the ones with the most potential, even if they are on the bottom of the “expert lists”.

Quell Your Lower Mid Market Buying Frustration with Novo-K BuyingStation!

Lower Mid-Market companies have a lot of problems modernizing their procurement practice. These include, but are not limited to:

  1. small procurement teams
  2. low budget
  3. lack of modern knowledge of best practices and tool sets
  4. few solutions that meet a. to c. on the market

This is the situation that Novo-K discovered when they started their managed procurement service offering a decade ago. Looking for tools that would support them in supporting their clients in a service-to-self-serve model (as they believe in enabling and training you to be more self sufficient as time goes on), they couldn’t find any that:

  • met the core 80/20 needs of their target market
  • came with an easy-to-use UX and built-in workflow
  • tackled tail spend effectively
  • was affordable for their customers

And having covered this space for 19 years, the doctor can confirm that when they started looking, this was more-of-less the case since:

  • most of the suites are over-engineered for the lower mid-market (LMM: £150M to £500M)
  • many could be configured, but the workflow wasn’t always simple out of the box, and UX varied
  • to this day, only a handful of providers have focussed on tail spend
  • most providers were priced out of the LMM range, and those that weren’t got scooped up in the M&A mania in the mid-to-late 2010s

but most importantly,

  • none (at the time) were really built to power a consultancy or MSP to serve it’s LMM customers in a service-to-self-serve model (where, over time, the customer would do more and more for themselves, only using the MSP on high-value/critical projects where it needed expertise or extra manpower or occasional strategic spend/category analysis projects)

So, after digging and digging and coming up empty (as most of the mines were at the point in time they were looking), they decided to build their own solution for the mid-market growth companies they focus on. They started by prototyping the workflows on Sharepoint, proved out the value proposition with their clients, then rebuilt a solid, modern, SaaS solution on AWS (which is SOC-2 compliant, G-Cloud approved, and currently going through ISO 27001 certification) [in the EU West Data Center 2 in the UK].

While the solution is new, it’s a really good Source-to-Contract solution for their target market, and especially so when you consider the price point is only £649 a month for most LMM procurement departments (as you can have up to 50 users at that price), can fit on a P-Card, and allows their Procurement department to manage all of their tendering processes for less than £8K a year! (And when it comes to saving, 80% often comes just from doing proper processes.)

So what does the solution do:

  • requests
  • project pipeline
  • quoting and tendering (RFQ)
  • supplier (information) management (and some supplier discovery)
  • contract management
  • savings tracker
  • administration

Requests

The platform is organized into a typical Procurement Project Workflow which starts off in an average (Lower) Mid-Market organization with a requisition from an organizational employee who needs to buy something. When the requisition enters the system, it is then routed to the appropriate budget owner(s) and approval queue for review and approval. If approved, it kicks off a project which is used to manage the source-to-contract process in the system.

Project Pipeline

Projects in the BuyingStation system go through the following standard workflow:

  • (approved) request
  • sourcing
  • selection
  • signing
  • supervision
  • document management (ongoing)

When a request is approved, it kicks off the project which captures all of the relevant information about the request (owner, budget [type], categories, need by date and/or sourcing timeframe, etc.) which can be used to inform later stages. Standard fields are pre-configured from the request, but more can be added to the request on a self-serve basis by the organization.

Quoting & Tendering

In the sourcing phase, the buyer defines the sourcing details, which will include, but not be limited to all of the standard definition fields (as the organization can define any additional fields that they need); uploads, or selects from the library, the terms and conditions, any required product or service specification documents, the pricing matrix and, optionally, the evaluation matrix (and indicates whether or not that will be shared with the supplier), and then selects the suppliers who will receive the quote requests (which have to be part of their organizational supply base — more on this later).

Sourcing Project Specification is the one place they currently use Gen-AI LLMs, and its specifically used for creating draft natural language project specification documents in standard formats using the sourcing event type (product or service), specific categories (and items) being sourced, project metadata, and other key elements of interest (which will be included in the prompt). Since they have no clue what you will source, their LLM training has focussed heavy on proper structure, core requirements, and high-level category specifics, and they expect their clients to use what is generated as a starting draft (that should only need a bit of editing for most standard products and services), and not a final document.

Once the sourcing specifications are complete, the quotation/tendering phase can be launched, and then requests are sent to the suppliers for completion. The suppliers get an email with link that takes them straight to the supplier portal where all they have to do is enter their password and they can upload their quotes and specifications. (As we’ll discuss later, chances are they already have their password setup as they would have completed their one-click registration when they were onboarded.)

Once the quotations are returned, the buyer can click into each and review them one by one. Note that, as of now, there is no in-platform support for viewing the Excel file responses, nor is there any support for the evaluation matrices, which will have to be completed and uploaded by the buyer once all of the quotations are reviewed.

Supplier Information Management

Backing up, when the user selects the suppliers, they select them from “My Suppliers” that tracks all of the organization’s suppliers and their current state of (un)approved and (un) contracted which lets the organization know where the supplier is in its onboarding, validation, and selection lifecycle. An unapproved supplier cannot be invited to quotations. An approved supplier is one that can be considered for business, but is one that hasn’t been selected if still un-contracted. (And, thus, an approved contracted supplier is one that has been approved and awarded business.)

Every supplier has standard corporate and administration details (which can be augmented as desired by the buying organization), a set of minimum information requirements for doing business (which can include, but not be limited to: credit information, data protection office, insurance, and baseline regulatory requirements) reference information, RASA* (optional, but an enhanced profile that can capture supply chain policies/considerations, cybersecurity & data privacy, conflict minerals, DEI [remember, they are UK and serve primarily UK and EU right now], IP policy and protection, and, very important, AI and Automation), associated projects, and associated contracts.

In addition to this standard supplier information management module, they also have a supplier directory that consists of baseline corporate profile information of every supplier who has registered in the portal, which allows a buyer to find potential suppliers based on standard filters of location and category.

Contract Management

The platform supports a basic contract repository that indexes all of the organization’s contracts with standard, user-defined, meta-data. While they don’t include AI for auto meta-data extraction, note that if you associate a contract with a project, a lot of the meta-data can be pulled in from the project to start you off. (They don’t deploy AI to auto-extract meta-data since their tests of the low-cost options, and remember this is very low-cost suite, found that accuracy for some contract types / older documents can be as low as 30% to 40% for many fields, with average performance around 70% at best. And while you will see that some of the larger vendors will quote accuracy rates of 80% to 90%, and that a few of these claims exist, this is not low-cost off the shelf third-party tech getting these results consistently — it’s highly specialized, and still expensive, tech.) Moreover, the metadata can also be uploaded from an Excel spreadsheet if that’s easier. (And when you’re only tracking a few dozen or so fields, do you really need overpriced AI? Might take you 15 minutes to enter it if you have your mallards in a row.)

Thus, once a supplier (or suppliers) is (are) selected for an award, and once the contract has been inked, it can be uploaded to the contract repository and associated with the project.

Savings Tracker

The platform also supports a savings tracker that allows the savings for each project to be tracked over time. However, since it’s a Source-to-Contract platform, it doesn’t do any automatic tracking as it doesn’t have access to historical, current, or future spend data in the procurement system, data store, or spend analysis system, and the user has to enter the historical price, negotiated price, and, on a regular basis, monthly or quarterly spend from the AP system. It requires some diligence, but seeing results quarter over quarter, if not month over month, is worth it and shows a mid-sized organization the value of a good sourcing process in the hands of an appropriately (platform-) powered Procurement team (trying to get budget and sufficient headcount to transform the buying, and savings, power of the organization).

Administration

Administration focusses on three capabilities:

  • system settings
  • user roles
  • forms

System settings are standard system settings such as language, currency and other financial settings, finance system redirection (email or link) if a buyer wants to kick off a PO, supplier directory settings, email account (for supplier communications), and whether or not the AI feature is on or off.

Security and access in the platform is roles-based, and the buying organization, on BuyingStation acquisition, will define (or customize) the (default) user roles (of Admin, Procurement Lead, Procurement [Buyer], Legal, Operations, IT, Legal, HR, and Marketing), and lock down user access by module and permission level. One unique characteristic of the system is that if a user doesn’t have any access to a part of a platform, they are not simply locked out (often by way of a greyed-out menu item), they are restricted from even seeing an interface that would indicate its existence. Unavailable functions don’t show up on the menu or in any part of the application they access.

Dashboard

Like most modern systems, the user logs in to a summary dashboard which not only summarizes expected vs. delivered savings year to date, but also statistics on project status, supplier status, contract status, and upcoming expirations.

Summary

It captures the majority of the process the average growth-focussed (lower) mid market organization needs (closer to a 90/10 than an 80/20, and really isn’t missing that much besides the ability to view quotes (side-by-side) and evaluation matrices in the platform (vs. having to go into Excel), so we can confidently say it’s a great solution for the price (which any organization can put on a P-Card). The two other things you need to note that it’s currently missing are:

  • an Open API to integrate to your Finance system (which is being developed now to support the out-of-the-box integrations they are planning for late this year/early next year that will allow you to push POs directly into your standard platform [like NetSuite] and even pull in basic invoice data) and pull in data for tracking and spend analysis (but at least this is coming at some point)
  • integrated spend analysis to help you identify what you should be sourcing, but this is an easy fix too — just buy a few Spendata classic licenses for your power buyers/analysts at $699 a year (as most mid-sized organizations won’t have data sets beyond 5M records, need local installations, or other enterprise capabilities when there will just be a few users) — and since Novo-K offers spend data cleansing and initial spend cube construction and analysis, they can jump start you on the right cube to start your sourcing and spend analysis journey

Now, of course, since the full commercial release of this new platform is only a year old and since it was designed to be low cost (and help Novo-K provide you with a platform that you can eventually use yourself after they start you off on your Strategic Procurement journey), there are lots of improvements that could be made, but not many are needed for you to start seeing ridiculous value from a low-cost solution that puts a best practice process (which is the ultimate key to savings) in the hands of your Growth-Focussed Procurement team that, to date, probably only has email, Excel, and a buying guide from 20 years ago. So, if you’re a lower mid-market still running off of email and Excel alone, we would suggest you look at BuyingStation today.

* Risk Aassurance of Supply, Assessment

Financial Business Risk Prioritizes Supply Chain Vulnerabilities …

… but it does not identify those vulnerabilities, although it can tell you where to start looking. So while an article in the SCMR last year provided a good overview on how to evaluate, and quantify, supplier risk, the title was misleading when it said they were calculating business risk to identify supply chain vulnerabilities.

The article, which described an approach by the authors to find a way to improve the evaluation of risk impact on a business, culminated in four main findings. The approach, which looked at the total financial impact a supplier failure would have, yielded two findings that we’ve known for over a decade, ever since Resilinc pioneered the approach of assessing the financial risk associated with a supplier failure (based on mapping where all of their parts are used and which of those are single source)

  • procurement spend with a supplier is NOT correlated with the financial risk of a supplier
  • part standardization can increase business risk impact

As well as two insights that are rather new:

  • procurement spend is not correlated with the revenue of the company (the Resilinc model could have shown this, but they did not focus on this or collect those metrics last time SI was made aware of their methodology)
  • true high-risk impact suppliers are a substantially smaller amount of spend than an organization might think; in the authors’ study, they represented only 28% of total spend (whereas most companies will highlight the high spend suppliers as high risk and identify the suppliers that represent almost 3 quarters of spend, or 73% in this study)

The reason for this is that they linked all of the organization’s data sources that contained information related to the BoM for each SKU, the revenue for each SKU, and the suppliers for each BOM. By creating a network of connections between components, products, and suppliers, and identifying single source parts, the link between the criticality of a supplier and the revenue became clear. Consider the supplier who supplies that custom control chip for the fuel injection management, cruise control, or even for the monitoring of the tire pressure. If they were to fail, the absence of a single, $10, custom control chip can bring down a multi-million dollar production line, and close down an entire production plant, as the recent semiconductor shortage did to many plants during COVID. Given that these were being put into $10,000 to $100,000 cars, these suppliers would never have blipped on a spend-based risk assessment. And this is just one example.

But it is an example that demonstrates the blind spots companies have with respect to small and specialized suppliers that aren’t in the top 80% of spend but yet supply sole-sourced and/or custom parts or products. This means that when doing a risk assessment, it’s not just risky suppliers or risky supply chains that need to be assessed, it’s any supplier that supplies something that isn’t easily replaced by another source should something happen to the current supplier. The risk could be low that they will fail, and lower still that you couldn’t quickly modify a design to use an alternative, but you don’t know until you assess. And that assessment must be revenue and criticality based, not spend based. Spending $100M with a steel supplier to acquire the raw material for a frame assembly makes the supplier strategic, but doesn’t make using that supplier super risky when all their competitors offer the same grades of steel. But if you need a custom chip for that car, power transformer, etc., and you currently only have one supplier to supply it, then that supplier, no matter how stable and how low-risk its profile looks, is a risk even if it only gets one hundredth of the spend. And you need to determine if it has any vulnerabilities and, if so, monitor them so you won’t be surprised by a sudden failure.

Calculum Charts your Course to Commerce Cultivation and Cash Cutting!

Calculum is a very interesting solution offering — it’s a working capital analytics solution meant to be the missing link between Finance and Procurement that just doesn’t exist today. Built to help their customers (which are mainly Global 3000 companies) to optimize their working capital across Procurement by optimizing payments and payment terms while taking weighted average cost of capital into effect, it offers a broader, and deeper, picture of cash needs and options than most platforms today.

Moreover, it goes well beyond the typical Procurement approach of simply recommending paying every supplier on the last possible day you are legally allowed to (based on either the contract or the country regulations, which they track for you) without penalty, and possibly the last possible day with penalty (if the contract is for less than the legally allowed maximum payment term) if the organization’s cost of capital is known to be lower than the penalty.

More specifically, it allows a company to understand the impact to working capital from

  • paying on a different (later) date
  • paying early (on a discount schedule)
  • paying up front (to reduce the supplier’s cost of working capital)
  • borrowing / using supply chain finance options to pay up front / early
  • using (virtual) cards

while taking into account its

  • cash conversion cycle (C2C)
  • days sales outstanding (DSO)
  • days payable outstanding (DPO)

and provide a company with true working capital and financing option optimization across Procurement, Finance, and Treasury and, in doing so, provide an average increase in free cash flow by 10% for every dollar analyzed.

Calculum does this by being possibly the only working capital optimization platform that is built on a solid spend analytics platform with its interface customized for working capital optimization, instead of category spend optimization.

Calculum starts by uploading your suppliers, contracts, and AP (invoice and payment) data, matching the data, helping you cleanse it until they have at least 90% 3-way match across your spend data (using their large, internal, supplier database of millions of suppliers ), from which they can determine immediate working capital optimization opportunities, prioritize suppliers for the realization of those opportunities, and distribute the opportunities across their 9 boxes for term extension and financing opportunities. (And you can see the exact degree of match, as well as the reasons for exception, in the match dashboards that present statistics on the data received, match rate, data quality, exclusions, and reasons for — and give you the data you, or Calculum, needs to improve the match rate)

Let’s start with that last sentence. Once the data is matched, the platform’s built in analytics will automatically identify:

  • all of your term extension opportunities across the supply base (taking into account any country legislations and noting existing terms where they are defined) organized into 9 cash flow buckets defined by impact vs. probability of success (which can be computed based upon historical supplier decisions, tracked in their centralized supplier database with anonymized data and past decisions, and similar supplier responses)
  • all of your financing opportunities from early payment discounts that are not being realized and/or negotiable discounts for early payments based on your weighted average cost of capital vs. that of your supplier also organized into 9 cash flow buckets based upon impact vs. probability of success (calculated in a similar manner)

Once the data is loaded, matched, and verified, a user can move from matching to optimizing gtheir working capital in the Opportunity dashboards and tabs. In this set of tabs and dashboards, you can:

  • see an overview that summarizes current payment terms (by contractual, opportunity, and excepted averages), cashflow opportunity, economic profit opportunity, affected entities, opportunity by category, and opportunity by program area (spend volume, supplier count, cash flow, and economic profit)
  • undertake your supplier prioritization efforts based upon your assessment of the easiest realized significant opportunities (by getting them to agree to different terms for faster payment or larger/future orders etc.)
  • review the 9 boxes financing built during the match
  • create your waterfall plan for attacking as much opportunity as possible

Moreover, because Calculum built their working capital optimization platform on a real spend analysis platform (with real cube support), which allows them to optimize payments and payment terms on multiple factors optimized against over 3 Trillion in analyzed spend, you can filter on any (set of) dimension(s) you like down to a small group of transactions.

Once you have finalized the opportunities and your waterfall/wave plan, you can move into the manage dashboards that allow you to

  • monitor your progress in the overview dashboard that tracks progress between current and target average payment terms, cashflow improvement progress, analyzed vs. planned vs contacted (effort begun/underway) vs. agreed (which could result in an unchanged term, as the opportunity should be closed either way after an [attempted] negotiation)
  • track your negotiations and reach out

And, of course, you can drill into any supplier, parent, or spend line of interest at any time because it’s a real spend analysis platform and see all of the relevant data at any level of the hierarchy that you like.

In addition, you can get a snapshot of working capital related information (spend, spend lines, (average) contracted terms, (average) payment terms, opportunity, etc. by supplier at any time simply by entering the suppliers dashboard and drilling into the supplier (or parent) of interest. The primary view will also tell you where the supplier is in the analyzed vs. planned vs contacted vs. agreed working capital optimization workflow supported by the platform. Drilling into a supplier will bring up basic corporate details, the corporate tree, any available ratings and metrics, and a payment terms vs. pricing analysis where you can calculate impacts from changes in payment terms, financing rates, your rates vs. the supplier’s rates, etc. to determine the optimal time to pay a supplier. The platform will then calculate the cost impacts of any potential/suggested change to both you and the supplier so you can make an informed decision (because sometimes an early payment doesn’t save you anything and sometimes extending a payment term costs you dearly in the long run). This allows you to propose win-win (or at least win-neutral) options that the supplier really shouldn’t be rejecting!

In addition, the platform uses AI to analyze all of the data they have on the supplier against standard strategies and built in models to recommend a detailed strategy for each supplier in the opportunity section so that you have deep guidance on how to approach a negotiation to alter the payment terms.

Moreover, Calculum is more than just a platform, it’s also a partially managed service where they work with you to ensure your data is properly uploaded and matched, the opportunities appropriately identified, the initial plan realistic and realizable, and execution effective, especially during the first few months where results and success is critical. They’re also there to support you on an ongoing basis and, if necessary, handle the refreshes / updates for you.

It’s a very unique offering and one that complements many Source-to-Pay or Procure-to-Pay platforms nicely for mid-market-plus organizations that need to maximize the value of their cash in these difficult times. It’s certainly a platform to check out if working capital optimization is front-and-center on the CFO’s mind.

We like what it’s doing and how it’s doing it and believe it is very valuable to a large segment of the mid-market. Upon a first review, there were no obvious holes or situations where we would say “the platform really should do this“, and the only point of sorrow we walked away with is that it’s not being sold by Calculon 2.0 (but then again, they are 988 years too early).

The Lack of Adoption of Analytics is NOT Complicated!

According to THE PROPHET, the reason that we’ve never seen a breakout $100M+ pure-play (spend) analytics vendor is it’s complicated. (Source: LinkedIn)

But the reality is that it’s really not.

First of all, approximately one third of all multi-nationals are headquartered in the US. In other words, one third of global enterprise is based out of the US, where the strategic decisions are made. Let’s say that again, one third!

Secondly, and this is the real explanation, in our age of participation trophies and only focusing on the positive (when there really isn’t any), no one is willing to state the truth, and that is most of the employees responsible for strategic [spend] analysis are just too math stupid.

Analytics, at its core, requires good mathematics skills and, with traditional analytics applications, good computer skills.

However, the US, where many multi-nationals are based, consistently ranks in the lower part of the OECD international rankings and is currently 34th in the PISA [out of 79 scored countries] (with an average numeracy score of 249, below the TOTAL OECD average of 263, with over 1/3 of its adult population at level 1! This means they can’t even do basic arithmetic and problem solving [or calculate a tip FFS, but that does explain why they believed their administration when they lied and said other countries pay the tariffs] — and that’s the average business employee in the US, since anyone with a level 2 on the OECD can likely fake it in a STEM career in the US.

As for THE PROPHET‘s reasons as to why Spend Analysis has consistently underperformed the hype:

  • While 3/4 of solutions have always been reporting in drag, I’ve been highlighting at least a dozen Best of Breed solutions consistently for the past decade. They have existed for the past 20 years, you just had to look (and understand what to look for. But this site did a great job of helping you with that!)
  • Yes, scale came at the cost of dumbing down the UX (for the US market in particular)!
  • Unfortunately there is no faster way to die as a Spend Analysis vendor then to get scooped up by a (mega) suite or a Big X Comsultancy.
  • Actually, the analytics and optimization is not powerful or complex enough in most solutions. Again, the problem is that the vendor didn’t add incremental levels of simplification (i.e. dumbing down) so each user could take advantage of it at their mathematical (in)competency level.

But the real reason, as hinted above, is that employees resisted these advanced spend analytics solutions because they knew they didn’t have the mathematical skills to use them. (Which the US Education System should be blamed for [and why it should be fixed, not dismantled], not the employees, unless those employees went to University and chose not to take math courses to try and make up for the failings of the public education system they were subjected to.)

As for THE PROPHET‘s signals that the times they are a changin’:

  1. Good + Cheap = Dangerous
    Faster? Check! Cheaper? Check! Smarter? Well … Ask Woody!
  2. Analytics is Merging with Execution
    This is key for adoption of analytics — do it when you need it and apply the findings right away.
  3. Intake, Orchestration and Agentic Tech
    I guess I have to say it again!
    𝐒𝐩𝐞𝐧𝐝 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐢𝐬 𝐂𝐥𝐮𝐞𝐥𝐞𝐬𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐏𝐨𝐩𝐮𝐥𝐚𝐫 𝐊𝐢𝐝𝐬!
    When what we really need is a Revenge of the Nerds! (If the USA even has any left!)

However, the real reason that we may finally be entering a new era in analytics is the following:

4. Most companies are trying to stave off bankruptcies as a result of US trade, market, etc. decisions that have already bankrupted many SMEs and they now realize that analytics is a key part of that solution. You can’t optimize spend you don’t understand, or understand the impact of a sudden 145% increase in tariffs if you don’t understand how much you are sourcing from the country in question.