Category Archives: Anti-Trends

Dear Fellow Analysts: It’s Time to Step Up And Deal with the PROCUREMENT STINK!

Because if we don’t, no one else will!

What am I talking about?

As per last Wednesday’s article, PROCUREMENT STINKS and we just can’t deny it anymore. In a nutshell, and this is just the tip of the garbage heap:

  1. Case studies are ranker than expired fish in a microwave on high.
  2. Approximately 85% of companies are AI-washing everything.
  3. The Gen-AI claims that it will deliver Procurement to the enterprise are FALSE.
  4. Intake/Orchestration is totally useless on its own.
  5. Consultancies are often more in the dark than the Procurement departments they are claiming they can help.
  6. DEI is being misused to push agendas and sometimes to Do Extra-legal Initiatives,

But this isn’t even the worst of it!

THE REVELATOR recently conducted a poll on who do you trust, and the results were more than a little disturbing as far as I am concerned.

 

That’s right. Only 50% of practitioners trust analysts to help them make the right decision when selecting technology. 36% would rather a consultant, who likely has a very strong incentive to either recommend a preferred partner solution (where they are guaranteed to get the implementation contract) or the solution that requires the most implementation effort (to add months, or years, to the engagement), and, even worse, 14% would rather trust a marketer or salesperson, who gets paid for leads or sales, not for solving a customer’s problem!

As far as the doctor is concerned, anything less than 75% is appalling. While he will happily admit there are some independent consultants at smaller firms without vendor partnerships who will be truly objective and will offer valuable advice, this is not the norm at most of the larger firms that are preferred partners or implementation providers for the bigger players in our space (where the majority of consultants reside), so the fact that the consultant trust is so high is a little off-putting. However, he’s simply aghast at the fact that 14% would rather trust a salesperson or a marketer for solution advice. Frankly, this means we are definitely failing the market.

Basically, if we can’t be the unbiased experts and independent voices of reason that the Procurement practitioners can always trust for good, unbiased, advice, then what good are we?

So what can we do to regain the trust? the doctor is sad to say he’s not exactly sure and hopes that

  • some other analysts will echo the call to action to deal with the PROCUREMENT STINK,
  • analysts will collectively take the lead in cleaning it up and restoring our reputation, and
  • offer up suggestions on what we can do to make it better!

Now, while the doctor doesn’t have all the answers, he does have suggestions on where we can start.

1. Be fully transparent on whom we do and don’t include in maps and logo charts, why, and the business situation in which our recommendations are, and are not, relevant.

This is quite obvious, and most of us are getting pretty good at being very explicit about the inclusion requirements for our maps and studies, but we don’t always take the time to clarify what this means for the market and, more specifically, which types of organizations the reports and maps are targeted at, which types of organizations will get the most value, and, most importantly, which types of organizations are unlikely to get any value because they don’t fall in the size/verticals/etc. the map or report is targeting. As far as the doctoris concerned, now more than ever we need to double down and get it right on both sides of the equation — who is being included, and why AND who should, and should not, be reading the report, and why, when we release something to the market. (Like the doctor did with his mega map.)

2. Stop glamourizing hype cycles and start busting them when there is no perceivable value to Procurement.

Procurement is supposed to be about solutions that deliver enterprise value, not cool technology. Leave that to the Consumer Electronics Show. When we promote tech for the sake of tech, we’re not helping anyone. We need to promote solutions to business problems with measurable ROI, regardless of what the underlying technology is. It’s irrelevant how many vendors embrace Gen-AI, when it has yet to demonstrate even a single use case that offers value beyond traditional tech, and the majority have failed to deliver any value.

3. Stop taking our cues from vendors as to where the space is going and start leading vendors to where the space should be going.

For example, intake-to-orchestrate is the craze, vendors are popping up faster than rabbits in a carrot field, and it’s likely only a matter of time before we see a map covering the intake-to-orchestrate space. (Especially since the doctor has been led to understand that one major analyst firm is already considering such a map, and where one leads, others will follow.)

However, in the doctor‘s view, this SHOULD NOT happen. Because, as stated above, and explained in detail in our article on why PROCUREMENT STINKS, there is NO VALUE in intake/orchestrate on its own. NONE. Intake is nothing more than pay-per-view on your data and orchestrate is just pure SaaS-based middleware, and middleware is something we’ve had for decades (and the need for such is negated completely if all the applications you use have complete, open, APIs as they can then be connected directly). The only value in these offerings would be in any additional functionality they embed to enhance the value of the applications they are linking together so that 1+1=3.

It would be understandable if they all embedded additional functionality that was comparable, valuable on its own, and formed a new application category that made sense to evaluate separately. However, right now, many don’t embed sufficient functionality; those that do are, for the most part, not comparable (as they all tend to specialize in something different, such as easy self-serve Procurement, services management, statements of work, etc.); and there has been no application thereof that wasn’t designed to enhance, or, most of the time, just make existing applications accessible. A standalone map would be senseless. (Instead, the intake and orchestrate requirements that are necessary for success should be included in the definition, and measurement of, Procurement, Sourcing, Supplier Management and other existing applications that can deliver enterprise value.)

3b. Start calling vendors out on bullsh!t when they start chasing, or putting, cool tech before practical solutions with actual ROI.

Privately at first (of course), unless the vendor insists on marketing it through a bullhorn. Then we may have no choice but to publicly call them out on it. Vendors may not like it, and may get upset when we burst their tech-centric bubble, but we’re not helping anyone when we don’t. Not us, not the procurement professionals we claim to support, and definitely not the vendors if we don’t try to dissuade them from throwing good money after bad on tech that won’t solve actual problems and ultimately won’t sell once their potential clients see the lack of value that comes with the price tag. This space has always been about ROI, we need to remind vendors of that, and guide them to where the ROI is just as we guide the practitioners. We need to be helpful to both sides to mature the space.

the doctor‘s not sure it’s enough, but it’s a start, and if other analysts make an effort to figure out how to restore our reputation, maybe we’ll find the answer, provide the unparalleled value that only we can provide, and get back the trust we should have.

Thoughts?

PROCUREMENT STINKS!

Note the Sourcing Innovation Editorial Disclaimers and note this is a very opinionated rant!  Your mileage will vary!  (And not about any firm in particular.)

Why aren’t you bothered by the smell?!?

If you haven’t been following along, we’ll lay out the top six reasons for you.

1. Case studies are ranker than expired fish in a microwave … and you don’t seem to care.

As per yesterday’s post, Have We Been In The Dank Basement So Long That We Don’t Care If the Fish Stinks?, we’re accepting that case studies are now nothing more than meaningless marketing mush and not even saying anything.

2. Approximately 85% of companies are AI-washing everything.

And the majority of these solutions don’t have any AI, or at least don’t have any native AI and are reliant entirely on questionable AI integrations. AI is hard. Really f6ck1ng hard. It’s not something you whip up overnight, especially if you want a solution that addresses a real problem with a real solution with any reliability. Before the Gen-AI craze, the doctor spent almost two decades here on Sourcing Innovation (and six years on Spend Matters) trying to educate you on the value of (strategic sourcing) decision optimization (SSDO), advanced (predictive) analytics, and proper targetted machine-learning AI that could provide better projections than the majority of “experts” — and the handful of vendors (and he means handful) that had this technology because, at any one time, we’ve never had more than half a dozen or so true SSDO vendors, a dozen or so true spend analytics providers with best-in-class technology, and more than 1 or 2 companies out of every 10 with true AI (and none with AI for more than a few targeted problems, but sometimes that was all you needed to identify extremely significant pockets of value and savings). Now, all of a sudden, we’ve gone from less than 20% to 85% literally overnight, when true AI advances have traditionally taken decades? Not f6ck1ng likely! Not only is AI a buzzword (as pointed out by Sarah Scudder), but it’s a delivery mechanism which, FYI, is a method by which the virus spreads itself.

3. Gen-AI claims that it will deliver Procurement to the enterprise are false.

It will deliver Procurement somewhere, but not the enterprise, unless the enterprise is code for Purgatory or Sheol. Gen-AI, which stands for Generative AI, literally means “AI that makes stuff up“, and, more specifically, since it’s trained to please, it makes stuff up that it thinks you want it to, not stuff that’s true, safe, or even legal. It’s NOT trustworthy, and won’t solve your Procurement problems. And while it may be a bit better at creating natural language responses, we’ve had Natural Language Processing (NLP) commercially for almost two decades, and a few vendors built very good, very reliable solutions, that will provide you with a significantly better chatbot than yet another custom variant of “chat, j’ai pété“. (There are no valid uses for Gen-AI that can’t be accomplished better, faster, and cheaper with existing tech.) [FYI, we blame the AI vendors who are pushing one side marketing here, and not the Procurement Vendors and Consultancies who fell for it.  If you don’t get both sides of the story, how can you form a good opinion?]

4. Intake / Orchestration is totally useless on its own.

There’s always a bandwagon we have to deal with, but rarely do we have two competing, often overlapping, equally useless bandwagons to deal with, with intake-to-orchestrate now speeding towards the cliff almost as fast as Gen-AI. As we discussed in Marketplace Madness, the days of pure intake-to-orchestrate are numbered because:

  • Intake is Pay Per View on YOUR data. Why are you paying for another view into your data?!?
  • Orchestrate is Solution Sprawl. It’s adding to the problem it purports to solve.
  • Intake-to-Orchestrate is Where’s the Beef? Sure you’re integrating everything and getting visibility into everything, but that’s not Procurement — which is identifying and strategically managing spend. So if the platform isn’t doing that, why not buy a platform that is that supports intake-to-orchestrate natively and allows you to manage strategic spend for risk reduction and savings???

5. Consultancies, purporting to help you, are often more in the dark than you are!

Big X and Mid-Sized Consultancies, which followed the money into tech, and then followed the money into Procurement, did so without any knowledge of where they were going or what was at the end of the yellow brick road, expecting to learn on the way. While some of the firms had good knowledge of Procurement from an operational or logistics perspective, they generally had little knowledge in tech and even less knowledge on the ProcureTech landscape (and most would be challenged to name 66 vendors, yet alone the 666 companies in the Sourcing Innovation Source-to-Pay+ Mega Map). And while some rolled up their sleeves, kicked off their shoes, and dug in until they got it, others still have no clue how to differentiate the vendors that purport to offer the same (set of) module(s) and determine which one is best for you … and, as a result, all they end up doing is recommending a “best-in-class provider” for which they are a preferred implementation partner (which usually happens to be one they picked from a Market Map, all of which give THE REVELATOR a migraine and the doctor anger management issues because meshing 6+ dimensions on an axis and/or putting a roll-up interface on top of the map that no one understands only adds to the confusion).  [It’s up to you do differentiate the good from the bad, know when you should be using Big X and mid-sized consultancies, when you should be using niche firms and independent experts, and when you should still be doing your homework and understanding your problem before even engaging anyone!  Otherwise, the failure is on you!]

But it’s even worse than this … many of the mid-market and smaller specialist consulting firms don’t have any more knowledge than the Big X  and larger mid-sized consultancies beyond the vendors they have personally worked with. the doctor is sad to say that he’s been talking to quite a number of them and has yet to find one that has a methodology for identifying third party solutions beyond hiring true expert consultants and practitioners with decades of solution (related) experience. And while you will get a good solution from one of their consultants (as they are hand picked by people that know what they are doing), there are two problems here for you:

  • you won’t necessarily get the best solution because the consultant won’t know about it
  • if that consultant retires, which is inevitable as the consultants with the cross-role and industry experience to get this right are closing in on three decades of experience (because you need practitioner/developer, manager, integrator, and consulting experience), and are, thus, a decade or less from retirement, will her replacement be as good?

and two problems for the firm:

  • when the leaders retire, will there be anyone with the necessary depth of knowledge to take their place
  • with not enough senior people to fill the roles relative to the large number of companies that need digitization and Procurement transformation, how will they scale and grow?

It’s too bad that, unlike the next generation of Procurement Providers (like Zip, who realized they needed a Head of Research in-house to help identify what their market was looking for so they could develop the right solution), it would appear that none of these consultancies have realized that they need an internal consultant to keep tabs on the market and help them not only manage technology partners, but qualify the solutions and figure out which clients those technology partners are most appropriate for, so that they can ensure the success of both their clients and their technology partners (and be the consultancy of choice for that partner who will prioritize their deals because they are confident the consultancy vetted the potential client before dangling a “deal” in front of them). (Or, if they are just starting to think about the issue, realize that they can’t just give an existing consultant this role as the background required is different than that of the consultant who works with the clients day-in-and-day-out.)

(FYI: the doctor is not the only one thinking this or saying this, although me might be the only one willing to state it publicly. He’s talked to a number of growing technology solution providers in our space that literally have “consulting” firms tripping over each other to be the provider’s “partner” as a result of the downturn many of these consultancies are experiencing [as qualified by THE PROPHET in his piece on the Consulting Bloodbath], but many of these consultancies are unable to qualify what unique value they would bring to the provider or joint clients [since that first requires understanding what the provider does, how it overlaps with what they do, how that intersection overlaps with what their customers actually need, and being forced to sell, they don’t have time to do all that research]. What these consultancies are failing to understand is that providers who are offering real, sometimes almost immediate, value with their SaaS solutions are getting a lot of traction in this down market and don’t have time or personnel [due to budget cuts when the funding taps turned off] to chase poorly qualified deals or deals with little or no profit for the provider. So when all the provider saw in the past from some of these consultancies was poorly qualified deals, they are wary of working with the consultancy that didn’t take the time to understand the potential customer, the necessary solution, and what the hot provider actually did.)

6. DEI is being misused to push agendas and, in some cases, commit fraud!

DEI, which was supposed to be about “equity” (which is supposed to be “fair” and “impartial” and “freedom from bias or favouritism”, as defined by the Oxford and Webster’s dictionaries), somehow became all about “equitable outcomes*, and now that is being used to push agendas and, sometimes, commit outright fraud as we have numerous examples of not only universities, cities, organizations, and countries mandating a lead Procurement role be filled by a minority (whether or not any exist with the required qualifications), but sometimes firing the person in the role to place a more junior person into the role under the guise of “DEI” so that the leader can ensure that all Procurements go his way (which can include purchases to organizations he is invested in, or gets campaign funds from, and so on). The most recent example is the city of Chicago, with the ramifications laid bare by THE PROPHET in his recent article on Why Would Chicago’s Mayor Fire Its Top Procurement Executive and Bring in Someone With a Fraction of the Experience?

* which is not at all equitable because that is not “fair”, “impartial”, or “free from bias” when you insist a minority be hired; equity is supposed to be about “equitable opportunity”, but apparently no one in DEI knows how to use a dictionary anymore

Now that you understand this, why are you putting up with it? Why aren’t you demanding more? You have every right to demand more, and you should be demanding more of your vendors, consultants, and Procurement leaders!

Because if you don’t, The Prophet‘s April Fools Day joke on how we must #EndProcurement might just become reality!

“Generative AI” or “CHATGPT Automation” is Not the Solution to your Source to Pay or Supply Chain Situation! Don’t Be Fooled. Be Insulted!

If you’ve been following along, you probably know that what pushed the doctor over the edge and forced him back to the keyboard sooner than he expected was all of the Artificial Indirection, Artificial Idiocy & Automated Incompetence that has been multiplying faster than Fibonacci’s rabbits in vendor press releases, marketing advertisements, capability claims, and even core product features on the vendor websites.

Generative AI and CHATGPT top the list of Artificial Indirection because these are algorithms that may, or may not, be useful with respect to anything the buyer will be using the solution for. Why?

Generative AI is simply a fancy term for using (deep) neural networks to identify patterns and structures within data to generate new, and supposedly original, content by pseudo-randomly producing content that is mathematically, or statistically, a close “match” to the input content. To be more precise, there are two (deep) neural networks at play — one that is configured to output content that is believed to be similar to the input content and a second network that is configured to simply determine the degree of similarity to the input content. And, depending on the application, there may be a post-processor algorithm that takes the output and tweaks it as minimal as possible to make sure it conforms to certain rules, as well as a pre-processor that formats or fingerprints the input for feeding into the generator network.

In other words, you feed it a set of musical compositions in a well-defined, preferably narrow, genre and the software will discern general melodies, harmonies, rhythms, beats, timbres, tempos, and transitions and then it will generate a composition using those melodies, harmonies, rhythms, beats, timbres, tempos, transitions and pseudo-randomization that, theoretically, could have been composed by someone who composes that type of music.

Or, you feed it a set of stories in a genre that follow the same 12-stage heroic story arc, and it will generate a similar story (given a wider database of names, places, objects, and worlds). And, if you take it into our realm, you feed it a set of contracts similar to the one you want for the category you just awarded and it will generate a usable contract for you. It Might Happen. Yaah. And monkeys might fly out of my butt!

CHATGPT is a very large multi-modal model that uses deep learning that accepts image and text as inputs and produces outputs expected to be inline with what the top 10% of experts would produce in the categories it is trained for. Deep learning is just another word for a multi-level neural network with massive interconnection between the nodes in connecting layers. (In other words, a traditional neural network may only have 3 levels for processing with nodes only connected to 2 or 3 nearest neighbours on the next level while a deep learning network will have connections to more near neighbors and at least one more level [for initial feature extraction] than a traditional neural network that would have been used in the past.)

How large? Large enough to support approximately 100 Trillion parameters. Large enough to be incomprehensible in size. But not in capability, no matter how good its advocates proclaim it to be. Yes, it can theoretically support as many parameters as the human brain has synapses, but it’s still computing its answers using very simplistic algorithms and learned probabilities, neither of which may be right (in addition to a lack of understanding as to whether or not the inputs we are providing are the right ones). And yes it’s language comprehension is better as the new models realize that what comes after a keyword can be as important, or more, than what came before (as not all grammars, slang, or tones are equal), but the probability of even a ridiculously large algorithm interpreting meaning (without tone, inflection, look, and other no verbal cues when someone is being sarcastic, witty, or argumentative, for example) is still considerably less than a human.

It’s supposed to be able to provide you an answer to any query for which an answer can be provided, but can it? Well, if it interprets your question properly and the answer exists, or a close enough answer exists and enough rules for altering that answer to the answer that you need exists, then yes. Otherwise, no. And yes, over time, it can get better and better … until it screws up entirely and when you don’t know the answer to begin with, how will you know the 5 times in a hundred it’s wrong and which one of those 5 times its so wrong that if you act on it, you are putting yourself, or your organization, in great jeopardy?

And its now being touted as the natural language assistant that can not only answer all your questions on organizational operations and performance but even give you guidance on future planning. I’d have to say … a sphincter says what?

Now, I’m not saying properly applied these Augmented Intelligence tools aren’t useful. They are. And I’m not saying they can’t greatly increase your efficiency. They can. Or that appropriately selected ML/PA techniques can’t improve your automation. They most certainly can.

What I am saying are these are NOT the magic beans the marketers say they are, NOT the giant beanstalk gateway to the sky castle, and definitely NOT the goose that lays the golden egg!

And, to be honest, the emphasis on this pablum, probabilistic, and purposeless third party tech is not only foolish (because a vendor should be selling their solid, specialty built, solution for your supply chain situation) but insulting. By putting this first and foremost in their marketing they’re not only saying they are not smart enough to design a good solution using expert understanding of the problem and an appropriate technological solution but that they think you are stupid enough to fall for their marketing and buy their solution anyway!

Versus just using the tech where it fits, and making sure it’s ONLY used where it fits. For example, how Zivio is using #ChatGPT to draft a statement of work only after gathering all the required information and similar Statements of Work to feed into #ChatGPT, and then it makes the user review, and edit as necessary, knowing that while the #ChatGPT solution can generate something close with enough information and enough to work with, every project is different and an algorithm never has all the data and what is therefore produced will never be perfect. (Sometimes close enough that you can circulate it is a draft, or even post it for a general purpose support role, but not for any need that is highly specific, which is usually the type of need an organization goes to market for.)

Another example would be using #ChatGPT as your Natural Language Interface to provide answers on performance, projects, past behaviour, best practices, expert suggestions, etc. instead of having the users go through 4+ levels of menus, designing complex reports/views and multiple filters, etc. … but building in logic to detect when a user is asking a question on data versus asking for a prediction on data vs. asking for a decision instead of making one themself … and NOT providing an answer to the last one, or at least not a direct answer. For example, how many units of our xTab did we sell last year is a question on data the platform should serve up quickly. How many units do we forecast to sell in the next 12 months is a question on prediction the platform should be able to derive an answer for using all the data available and the most appropriate forecasting model for the category, product, and current market conditions. How many units should I order is asking the tool to make a decision for the human so either the tool should detect it is being asked to make a decision where it doesn’t have the intelligence or perfect information to do and respond with I’m not programmed to make business decisions or return an answer that the current forecast for the next quarter’s demand for xTab for which we will need stock is 200K units, typically delivery times are 78 days, and based on this, the practice is to order one quarter’s units at a time. The buyer may not question the software and blindly place the order, but the buyer still has to make the decision to do that.

And no third party AI is going to blindly come up with the best recommendation as it has to know the category specifics, what forecasting algorithms are generally used, why, the typical delivery times, the organization’s preferred inventory levels and safety stock, and the best practices the organization should be employing.

AI is simply a tool that provides you with a possible (and often probable, but never certain) answer when you haven’t yet figured out a better one, and no AI model will ever beat the best human designed algorithm on the best data set for that algorithm.

At the end of the day, all these AI algorithms are doing is learning a) how to classify the data and then b) what the best model is to use on that data. This is why the best forecasting algorithms are still the classical ones developed 50 years ago, as all the best techniques do is get better and better and selecting the data for those algorithms and tuning the parameters of the classical model, and why a well designed, deterministic, algorithm by an intelligent human can always beat an ill designed one by an AI. (Although, with the sheer power of today’s machines, we may soon reach the point where we reverse engineer what the AI did to create that best algorithm versus spending years of research going down the wrong paths when massive, dumb, computation can do all that grunt work for us and get us close to the right answer faster).

Future Trend 34: Digital Transformation

How did SI miss this one in it’s two in-depth series on the future of procurement and it’s follow up future trends expose???

This anti-trend is as old as the internet!

But let’s back up. Recently, the procurement dynamo published a piece on the digital transformation of procurement where he asked if it was a good abuse of language. In this post he started off by noting that the digital transformation expression is an overused buzzword — which is an understatement.

Secondly, as the procurement dynamo notes, no one has a proper understanding of what it actually means. the procurement dynamo attempts to rectify this by giving a clear definition of the term with respect to the also overused digitization and digitalization terminology. According to the procurement dynamo

  • digitization is the conversion from analog to digital … atoms to bits …
  • digitalization is the process of using digital technology and the impact it has and
  • digital transformation is a digital-first approach that encompasses all aspects of business

… and, in particular, digital transformation is a digital-first approach to the extent that digital can be applied.

And this means that this is yet another anti-trend in Procurement as leading organizations have been doing this ever since the adoption of e-Auctions. The best organizations have been adopting, to the extent possible, new technologies since the e-auction hit the scene 20 years ago. RFX. True e-invoicing. Supplier Information Management. Contract Management. Decision Optimization. And so on. The leaders (which are very, very few) have pushed for, and embraced, digital transformation for the last two decades.

And, to be honest, when you get right down to it, the concept of digital transformation is, as a farmer would say, hogwash. You’re either continually adopting and using the best tools and processes available to you, or you are counting down to the days your doors close. The organizations that have survived decades have embraced multiple technological revolutions. They’ve went from carbon paper to copiers to digital transmission. Digital transformation is just the latest technological revolution, and may not be the last. (If quantum tech gets perfected, you’ll have to move to technology based on qubits … a blend of atoms and bits.)

So don’t fall for the latest fad — keep focussed on the goal. Better business building.

Procurement Trend #17. Talent

Fourteen anti-trends from the grey-beards’ glory days still remain, and as much as we’d like to provide more entertainment to LOLCat who is bored with our anti-trend coverage, we must make sure that no good deed goes unpunished and since the futurists’ advice is as good as it gets, we must break it all down until you can look past the shiny new paint job and realize that it’s a twenty year old Skoda you are being sold.

So why do so many historians keep pegging talent as a future trend? Besides the fact that they are, unfortunately, still cemented in the people-process-technology (and not the talent-technology-transition management) mindset, it is probably because, no matter where your organization is on its Supply Management journey:

  • more knowledge is required

    Supply Management professionals are currently climbing the Devil’s Staircase

  • more technology is required

    because most work is still tactical paper pushing work (even if it’s pushing scanned PDFs, it’s still paper pushing work)

  • more skills are required

    to transition to better processes, use new technology, and identify more value generation opportunities for the organization

So what does this mean?

Knowledge

As per our previous posts on inter-departmental collaboration and more stakeholder collaboration you need to implement knowledge management. You need to capture the knowledge you have. You need to capture the knowledge your partners bring you. And you definitely to capture the knowledge you generate before it walks out the door when your people move on to the next stage of their professional and/or personal life. It is a knowledge economy, and if you don’t have the knowledge required, you won’t be in the new economy much longer. C’est la vie dans le nouveau monde de l’enterprise.

Technology

As per our previous posts on increased accuracy in demand planning, process convergence into Supply Management, and e-Procurement System Adoption, you need to implement new and better technology solutions. These solutions need to automate the tactical, optimize the operations, and enable the strategic. Electronically pushing paper is not strategic. Monitoring dashboards is not strategic. Re-sourcing a category for the third time through an e-Auction for a measly 3% savings is not strategic. Doing detailed analyses that allow you to identify untapped opportunities, define new processes that will get marketing or legal on-board with spend management methodologies, or helping R&D design a product that is both more cost efficient to produce and more desirable to the market — that’s strategic.

Skills

It’s like we keep saying here at SI, a modern Supply Management professional needs to be a jack of all trades and a master of one. You need to continually enhance your soft skills, your tech skills, and your knowledge of different organizational disciplines, processes, and goals and learn to take advantage of the new technologies and opportunities that are continually being made available to you.