Category Archives: Best Practices

Follow the Money to Find Future Opportunity — Which Will NOT Be Fully Found With Autonomous Sourcing!

Spend Matters has thrown caution to the wind and followed Gartner’s lead jumping onto the AI Hype Bus (with no steering and no brakes) that is still heading straight for the cliff and are wheeling out webinars on AI faster than a prairie fire with a tailwind. (Needless to say Sourcing Innovation does not think this is a good thing. There are valid uses for AI and automated processing, but fully handing over financial decisions is like wheeling in the Trojan Horse and leaving it unguarded in the server room with unrestricted access to your bank integration.)

Recently, The Maverick advertised yet another Spend Matters webinar on Autonomous and AI Sourcing where he said we should “follow the money”. Which we should, but there are a few things we need to clarify first.

1. No Money Changes Hands In Sourcing

It changes hands in Procurement … and it’s because most companies don’t follow the money after the contract is signed that 30 to 40 cents of negotiated savings never materialize in many companies, which The Maverick should remember from his AMR and Hackett days, as it was laid clear in Mickey North Rizza‘s famous 2009 “Reaching Sourcing Excellence” series, which we know is in his archives.

2. “Speed” is NOT a strategic edge if you don’t get it right!

If you don’t go out with the right strategy, don’t know the current market price, don’t know the reason for the current market price, and don’t have the knowledge to project if the trend is going to continue, stabilize or reverse, going to market is not a good decision … and it’s an even worse decision to automate the sourcing project and secure an award as fast as possible if you don’t know if it’s the best you could have done or the worst you could have done.

3. “Pecunia non olet”, but yet these vendors are asking you to treat it like it does!

They want you to automate spend analysis, sourcing, contracts, purchases, and everything else that involves money by turning over everything to their Agentric AI because, apparently, money stinks and you don’t want to touch it. (But they are quite happy to not only spend yours for you but takes as much of it as they can for their services.)

But here’s what they don’t tell you.

  • AI is NOT Intelligent.
    The level of intelligence in their “AI” is equivalent to the level of intelligence in a carpenter’s hammer. The level of effectiveness is entirely dependent on how skilled the person “training” the system and how skilled the person “using” the system is, just like the effectiveness of a hammer is dependent on how well the carpenter was trained and how experienced he is in it’s use.
  • AI Does Not Know What it Does Not Know.
    If the data is incomplete, the recommendation is very likely incorrect.
  • AI Cannot Do Better than the Best A Human Has Ever Done in Decision Making.
    So, if none of the situations it was trained on led to great results, neither will what it recommends for you.

You need to remember how Gen-AI does its work (or should we say does not work). It is large document search and summarization and chain of compute. Now, the more advanced players are trying to embed knowledge graphs into this, but these are not perfect either. With good training examples, and a very similar situation, the probability it will work well is very good, but it’s still only a probability. As a result, nothing should ever be fully automated where money is concerned. The tools should be used for their recommendations, and if the recommendations are good, and the risk is low, most of the tactical data processing and event management should be automated, but the decisions should ALWAYS be made by a human, who should be involved at every decision point. Even if that decision is verifying the system recommendation. It only takes one miscalculation due to an incomplete data source to project a wrong trend, rush an auction, lock in a price 3X what you are paying now, only for it to fall in a month later when a factory (which went offline temporarily due to a manmade or natural disaster) comes back online and the supply-demand balance returns to normal. And while you may have stocked out for two weeks, those losses will be orders of magnitude less than paying 3X at a contract you have to honour (unless you want to get dragged into court).

Now, if you really want to make money, forget all this Autonomous and Agentric AI BS, look for Augmented Intelligence solutions that make your staff two, three, five, and even ten times more efficient, purchase those, and, remembering that the US infrastructure is crumbling fast (and not going to get renewed under a Republican administration that is more interest in trickle-on economic tax cuts for its billionaires than ensuring you have running water), it’s time to remember how the smart made money in ancient Rome — public bathhouses and latrines. Time to invest in your own desalination facilities and be ready when the public wells run dry. After all, “Pecunia Non Olet“.

The Best Way to Survive the AI-Powered Apocalypse? Go Old School!

If you’ve been following along, you know that a great purge is coming on two fronts. All the pundits agree on that! On the first front, a large number of vendors are going bye bye, as we’ve been telling you since our first post on the Marketplace Madness. On the second front, they took ‘er jobs. Except it’s not they, it’s AI.

So doesn’t this mean that if you want to survive the days ahead that you should find the most advanced AI provider that isn’t going to get purged in the near future, adopt the tech, replace as much staff as you can with AI, find a way to survive the hardship, and come out ahead when everyone decides that what they have to do?

Well, for the vast majority of the analysts and pundits, it is exactly what you should do — and do it right now. It’s AI overload all the time. And just when most hype cycles start to die down, this one gets a second wind of hurricane proportions.

But, in fact, it’s the last thing you should do. In fact, you should implement a Gen-AI ban and Agentric AI ban immediately, and identify classic ML-powered AI augmented intelligence tech that can supercharge your team, acquire it, and train your team on that immediately. Because you can get the same results as any Agentric AI can get if you employ the right classic ML-powered human-driven AI technology with the right algorithms, analytics, optimization, etc. Sure, a human might be a little bit slower than an algorithm that can work 24/7/365 without a break, but human who is appropriately skilled and trained will make up for this with something the AI doesn’t have, true intelligence.

You see, the thing about Gen-AI and Agentric AI is that it works great until it doesn’t. As per our recent post, Gen-AI is full of problems. In a recent post, we noted that, Gen-AI can:

  • get you sued
  • increase the chance you will be hacked
  • result in Million/Billion-Plus processing errors
  • shut down your organization’s systems for days
  • help your employees commit fraud

And those are the good side effects from its hallucinations. There are much worse side effects that can happen. If you refer back to our posts on the valid uses for Gen AI and the valid uses for Gen AI in Procurement

  • the embedded biases, that you might not even be aware of, could result in decisions diametrically opposed to what you are expecting
  • when it computes two options that are equally likely to generate the same end result for the company relative to the KPI it is using, there’s no guarantee it will select the right option — and there’s always a right option, especially if one option for cost savings is a longer term contract so the supplier can upgrade equipment and the other option is forcing the supplier to cut an already razor thin margin 50%
  • the hallucinations eventually become real, as the systems get so advanced that they not only create super realistic evidence to back up their recommendations, but take over your entire systems in the background so that you don’t know that a web request to verify a claim is actually still being processed by the AI that is now running in the background
  • it starts negotiations and cutting contracts you haven’t even authorized yet
  • it becomes you … and you get blamed for all its mistakes

In other words, ignore the Gen-AI and Agentric-AI technologies that are not the miracle cures they are promised to be. The miracle cures are the last generation ML-based AI technology that was just about to transform your operations under the expert fingers of your leading practitioners, not some probabilistic monstrosity that requires an entire data center to run to generate an output no one verify using a system no one understands. Hone your chops on those and you’ll get the results you need, without having to deal with unexpected, possibly catastrophic, failures along the way.

After all, when we told you about all of the great advancements that were coming in Source To Pay in our classic series (indexed here), none of it required Gen-AI to achieve!

If you want productive supplier bees, maybe you should get a Hive!

Last decade there was a lot of messaging around supplier information management, relationship management, and even supplier diversity management but not much about risk and compliance, as COVID hadn’t hit yet, and very little about supplier performance management, as most organizations were still struggling just to get a handle on who their (active) suppliers were. However, while there has been a lot of talk about the value of relationship management for two decades, the reality is that there is no value in just relationship management. All relationship management does is ensure that there is communication around issues, contracts, etc.

The value of an SXM system comes from an improvement, and that requires performance management if the value is limited due to poor performance; risk management if the lack of value is due to multiple disruptions over the course of the relationship; and compliance, if lack thereof is resulting in unsaleable goods or unusable services. However, there is no value from your supplier being happy with the relationship. They might be easier to work with, but what’s the dollar value of that? Zero. 0. Moreover, are they happy because you are a good customer or are they happy because they’re charging you extortion prices and you are paying them while being blissfully unaware? (Now, that’s not the supplier’s problem, as it was your sourcing team’s problem for not doing their market research, but, again, it’s not indicative that you have a good, valuable, relationship.)

Fortunately, there are a (select) few providers that offer performance management, and one in particular is SupplyHive, which, unlike many of it’s peers, ONLY does Supplier Performance Management (as that’s where they see the largest market need, and they can easily integrate with other systems for those organizations that want a more holistic supplier management solution). Founded five years ago by ex-CVM founders (who basically defined the SaaS-driven supplier diversity space before it was a thing), they now have 25 Fortune 1000 customers across multiple industries (including a number of really big names whose products you likely use or consume regularly). They have these customers because they not only support customizable performance analysis down to the supplier plant level or service level on a role or project basis, but can do holistic performance analysis across products, ESG, risk, compliance, personnel, and any other factor you want to consider and have the data for. (Which can come from existing systems they will integrate with, third party feeds, or supplier surveys … but it’s really best to use third party or measured, objective, data and keep the surveys for supplier 360 surveys where you ask your team to rate the more subjective aspects of the relationship and you ask the supplier to rate how well they think they are doing on more subjective factors, or metrics translated to a 1 to 100 percentage, and see how their view of performance differs from your organization’s.)

Furthermore, and this is not surprising if you are familiar with the niche supplier management specialists in the SXM space, the majority of their clients and prospects have (SAP) Ariba, Coupa, Jaggaer, or another major suite and not a single one of these use their supplier management modules (because, while it’s important to know who all your active suppliers are, and have this information in one common location, there is no value paying six figures a year for a supplier information database when you can literally get one for 99£ per user per month). The value comes in being able to do something with that data. (So you need to add risk modules, compliance modules, ESG modules, etc. etc. etc. This can greatly inflate a suite price, and often you only get last generation modules in many cases. (Remember that Ariba was built around Procurement. Coupa was built around Procurement and its next strongest modules are Advanced Sourcing [Trade Extensions acquisition], Spend Analysis [Spend360 acquistion], etc. Jaggaer, formally SciQuest, was built around Procurement and acquired a number of companies in the early days to flesh out its solution, and eventually BravoSolution for Spend Analysis and Sourcing [in Indirect, Services, Projects, etc.] and Pool4Tool for Direct Procurement. While many of these have fairly extensive SXM offerings if you buy all the modules, none of these started in SXM and definitely not in SPM/SUM.)

On the flip side, SupplyHive, which is a best-in-class information management solution (because you need information for performance), was built for performance. And it was built with four goals in mind, which they have now achieved:

  1. meaningful scores that convey (relative) supplier performance at a glance with drill down to raw data
  2. drillable performance scorecards that go right down to the individual plant, and project, level if you desire
  3. meaningful, AI-summarized, feedback and auto-generated reports that can be sent to the supplier as a basis for discussions
  4. embedded action plans, which are auto-suggested and can be kicked off automatically upon a score falling below a threshold or a supplier discussion

as they saw the following problems with every traditional SRM, solution, including those that had single-level survey “performance”

  1. a random score on a random scorecard is meaningless; the score needs to cover the representative dimensions across meaningful scorecards with appropriate weightings; and while a company may have the expertise to build a scorecard across some dimensions, they will need best practice guidance across others
  2. a high level score hides the truth; you’ll have exceptional plants/projects and dismal ones, but they will cancel out and you’ll be left with an average, which you will think signals all things fine [but it’s even worse than that, a score is not a score is not a score as there will always be differences by location, product, and project and unless you have all the data and all the details, you’ll never get the full picture of where there is the most opportunity for improvement, where there is the least, when a supplier is one you want to consider consolidating too, and when a supplier is one you want to take business away from until they get matters under control]
  3. while a scorecard may be meaningful to a buyer, except for the 360-view (which summarizes the gap between the supplier’s viewpoint on their performance versus the buyer), it’s not meaningful to the supplier — they need plain english and focus on key areas they need to improve
  4. just like relationship management doesn’t actually increase value, performance doesn’t increase value unless you do something to improve that performance

Thus, SupplyHive built a platform that has four main parts:

  • Your Hive (MyHive): which centralizes access to your (open) surveys, action plans, and scorecards
  • Suppliers: which centralizes access to your suppliers, their profiles, and the high-level matrix with the supplier’s hive score
  • Hive Analytics: where you can drill into supplier scorecards (by area), benchmarks, the Hive360° breakdown, and the quadrant view (which is good for sourcerers)
  • Configuration: the administration section that allows everything to be configured to the needs of the organization

Let’s start with your Suppliers.

SupplyHive has an Open API, so it is easy to pull suppliers from another system or push them in if your current supplier master has configurable API-driven pull or push capabilities. If not, or you don’t want to deal with IT or the implementation lag, it’s very easy to load the database of suppliers from a flat file (which all of your systems should be able to generate) and then do the integration later. (And, finally, for ongoing supplier maintenance, it does support new supplier profile creation through form-based entry like every SXM system on the market.)

The primary entry point in SupplyHive is the supplier matrix where you see a quick snapshot of your suppliers and their overall hive score; performance and relationship indexes; quality, value, customer service, and CSAT stores; as well as the number of (completed) project reviews and associated supplier spend (which needs to either be pulled in from the ERP/AP or manually entered).

The search tab allows you to search suppliers by name, location, or other detail in their profile. Selecting a supplier brings up their scorecard summary by default (as the platform is focussed on performance), which can be configured to include an overall AI generated summary or a customized performance dashboard, and from there you can click into the scores and drill into the Hive Analytics or drill into the supplier profile. The profile has everything you would expect out of the box including, but not limited to:

  • basic company details (including, but not limited to, categories, client accounts, divisions, regions, etc.)
  • location details
  • contracts & identified risks
  • diversity profile
  • digital QBRs
  • sustainability
  • safety
  • SRM framework
  • issue trackers
  • innovation hub

and if that’s not enough, the buying organization can add as many tabs as it wants (and hide or remove tabs it doesn’t) as well as adding as many fields as it wants to existing tabs) in the configuration section, where each tab can include as many standardized attributes (also defined in the configuration section) as desired.

Now let’s move onto the Hive Analytics, starting with the scorecards. Scorecards work as you would expect, they have a number of dimensions, scored on a scale (that can be converted to a quantitative number), that can be weighted to compute a total score. The default scale is out of 100, but any scale can be configured. The big difference with Hive Analytics is that they are not supplier level — they are fine grained down to the project at the plant / location level, and then rolled up to the plant / project, to the region, to the supplier (or to the plant, to the country, to the region, to the category, to the brand, to the supplier, etc. — depending on how granular the organization wants to measure performance). They are based on either survey data (filled out by organizational stakeholders, supplier stakeholders, or both) or imported third party risk/compliance/metric data (as the platform is not a risk, compliance, or [financial] metric platform).

Out of the box, the platform can be configured to include a number of survey templates for each industry and major category, but SupplyHive prefers to work with its clients on configuration to customize the templates based on the primary categories and projects the client is addressing in its initial performance projects, that start with the top 60% to 80% of spend and the top 10% to 20% of active suppliers.

In addition to scorecards, which are associated with a date, and which can be filled out by multiple individuals, there is a trend view that allows the organization to see how the supplier’s performance score changes over time.

As noted above, the platform supports Hive360° where the supplier can be invited to self-score, and then the platform will show the difference between the buyer score and the supplier score. It’s not just your view of performance that is important, it’s the supplier’s view. If the supplier believes they are performing a lot better than you think they are, then their performance review should likely take priority over others, especially if they are considered a strategic supplier while the other suppliers with a similar performance score are providing commodities or non-strategic products and services where you can live with mediocre performance (as long as the supplier recognizes that’s the level of performance they are providing you with).

Benchmarks allow you to compare supplier performance to an organizational defined baseline which can be based on average supplier performance for the category or industry or a snapshot of past supplier performance.

When it comes to action plans, they work as you would expect, with a bit of a twist. There are three ways to generate action plans:

  1. fully manual
  2. platform recommendation of existing templates (with titles, goals, and action steps) using the metrics, trends, and user feedback that can then be customized
  3. AI-generated from uploaded documents — which can include call transcripts, project specifications, issue documentation, etc. — context, and goals

In each instance, you can accept or modify the steps, define due dates and owners and approvers for each of the steps, launch it, and track the progress over time.

We’ll quickly mention the new innovation hub where buyers can issues challenges and suppliers can submit ideas, and which allows the buyers to manage those submissions through an intake to execute process that organizes ideas by category and type and tracks the status of each one.

Finally, the Quadrant View, which can be used to plot any two dimensions or supplier KPIs against each other, can be used to plot the (overall) supplier score by supplier spend (with drill down capability) to help those organizations identify high spend suppliers with low performance that may need immediate action relative to performance; or to identify high performance suppliers with low spend that an organization may want to move business to; or to identify low-performance low-spend supplies which could simply be eliminated from the organization’s supply base in an optimization project. (Optimization, not rationalization, as it’s not always the fewest suppliers, it’s the right number by region and category that deliver the right value and performance. The right number for a category could be 2 suppliers or it could be 22 suppliers.)

The most unique aspect of the performance application is the supplier performance summary which is not just a roll up of the scorecards, but an AI-generated supplier snapshot that includes an overall performance summary in plain english, suggested supplier action plans, the story behind each score (key issues in plain english), suggested action plans tailored to improving that sub-score, and a gap analysis on the Hive360°. The platform also allows the user to output a PDF report with all of the information to send to the supplier before a supplier performance review to help both parties get on the same page. Also, it’s single click for a buyer to kick off an action plan with a supplier with the goal of helping the supplier improve their performance.

In terms of the Roadmap, they are working on three major enhancements:

  • Anonymized Community Performance Direction Data: where they use anonymized community data to enhance common supplier profiles with directional performance data (to help buyers understand which suppliers are improving when doing discovery and which suppliers are not, or might be in trouble, when considering renewals)
  • Automated “Boost your Hive Score” Recommendations and action plans where they let a supplier know that if they can do actions / action plan X by date Y, it will increase their score for a buyer
  • Detailed Performance Insights where, going back to where the doctor said a score is not a score is not a score bubble up the best and worst performance across a supplier’s categories, locations, and projects and, over time, identify what a supplier is consistently good at (and improving) and not good (and worsening); for example, they did an analysis across one of the Big X consultancies and pretty much discovered something leading analysts in the space already know (but most won’t write about, but, as you know, the doctor, who told you NOT to hire a F6ckw@d from a Big X for an Analytics project, will), that the certain Big X consultancy in question only consistently performed well on:
    • high dollar projects (which get the attention of the few, talented, high paid team leaders)
    • quick hit projects (that they can complete quickly with the few high performing assets they have and then reassign the team to another overpriced project)

With respect to implementation, most of their customers are up and fully running on the platform in 30 to 60 days, which includes the creation/import of all starting supplier profiles, the selection and customization of attributes, scorecards, organizational categories and hierarchies, users, training, and initial project creation. Implementations that require IT or a third party might take longer, but if the connection points have Open APIs, those are typically configured in days.

So, if you are a larger organization where supplier performance is a serious concern, and an even more serious manual effort (where your team is breaking under spreadsheets), consider checking out SupplyHive at your earliest convenience. (Especially if your QBRs are taking an average of 45 days of prep time, as SupplyHive will reduce that to less than 5 days of prep time, a 90% savings! Most of their clients are currently seeing a 6X to 10X ROI from the manual effort reductions alone, which also allows them to put more than just the top 100 suppliers under management, with many organizations quickly progressing to 500 to 1000 suppliers under ongoing performance management and monitoring.)

Just like CVM took off over a decade ago, this next phase of specialized supplier management application is about to take off again because organizations need value from their suppliers, and relationship management alone is not enough. (You should consider checking them out sooner than later. Once the market realizes how critical supplier performance management is to cost management in the new age of supply chain cost unpredictability, given how few supplier performance management solutions are on the market, we expect that you’ll go from getting their attention to waiting in a queue.)

Your Upteenth Reminder That Every Dollar Saved By Procurement Goes Straight to the Bottom Line!

… while 10 cents from every additional sale might make it, if you’re lucky!

A week or so ago, Joël Collin-Demers said COVID was the instigating event that pushed Procurement front and center in a comment to yet another post about the tariff crisis (to which, as I keep saying, the only solution is BTCHaaS), when it was really the (fist) elevating event in over a decade.

The first event that really put ProcureTech on the map was the 2008 financial crisis. This is because companies had to stop the bleeding, fast, and charged Procurement to get ‘er done. But once the markets settled, and the provider base stabilized, and companies willing to spend the money they needed to implement proper tech and get more efficient did so, Procurement kind of faded into the background again. That’s because, when markets rise, and sales rise, the C-Suite focusses entirely on revenue, almost to the point of irrationality, because the faster that revenue rises, the higher the valuation, and the more money they can make on the markets and trades.

However, the 2008 financial crisis is why the M&A and PE activity started to ramp up in ProcureTech in the early teens, because of the importance placed on cost cutting as a result of the 2008 financial crisis. And why, if something else had happened sooner, Procurement would have risen up the organizational chart faster, instead of falling back into obscurity at many organizations who returned undue focus to Sales and Marketing.

This, of course, belies the sad, sorry, state of affairs of North American business that still sees marketing and sales as the key to growth in a shrinking economy (and yes, with birth rates declining in almost all first world countries, it is a shrinking economy) when the real key is cost management. Remember your business 101 equation: Profit = Revenue – Expenses.

This says that every dollar of revenue you add is eaten up by the total cost to acquire that dollar — the total cost of that good or service, which is usually at least 90 cents of that dollar.

However, every dollar of expense you cut is gone in its entirety. Every dollar saved goes straight to the bottom line.

Thus, Procurement is 10 times as valuable as sales! But yet, the marketing madmen will try to hide that from you to protect their multi-million budgets!

So if you want to survive the crisis of the day, whatever that crisis may be, it’s not sales, it’s not marketing, it’s not finance, it’s not executive leadership or vision, it’s Procurement. Plain and simple. Maximize every dollar spent while eliminating those that don’t need to be.

Unless, of course, you are a ProcureTech vendor, in which case, as per a previous post, skip the fairy dust and buzzwords, focuses on your customers pain, and put together some educational materials (marketing and training) that will help them ease the bleeding. If you’ve forgotten how to do that, or never learned, there are those of us who can help you!

With Great Data Comes Great Opportunity!

In fact, it can quadruple your ROI from a major suite.

Not long ago, Stephany Lapierre posted that your team may only be realizing <50% of the ROI from your Ariba or Coupa investment, to which, of course, my response was:

50% of value on average? WOW!

Let’s break some things down.

A suite will typically cost 4X a leaner mid-market offering which is often enough even for an enterprise just starting it’s Best in Class journey (that will take at least 8 years, as per Hackett group research in the 2000s).

Moreover, even if the enterprise can make full use of the suite it buys for 4X, at least 80% of the “opportunity” comes from just having a good process, technology, baseline capability and automation behind it. That says you’re paying 4X to squeeze an additional 20% worth of opportunity in the best case.

On average, it takes 2 to 3 years to implement a suite (on a 3 to 5 year deal). So maybe you’re seeing an average of 66% functionality over the contract duration.

As Stephany pointed out, bad data leads to

  • increased supplier discovery and management times
  • invoice processing delays and errors
  • increased risk and decreased performance insight

As well as an

  • inability to take advantage of advanced (spend) analytics
  • inability to build detailed optimization models
  • decreased accuracy in cost modelling and market prediction

This is even more problematic! Why? These are the only technologies found to deliver year-over-year 10%+ savings! (This is where the extra value a suite can offer comes from, but only with good data. Otherwise, at most half of the opportunity will be realized.)

Thus, one can argue an average organization is only getting 66% of 25% of 80% of its investment against peers (based on 2/3rd functionality, the 4X suite cost, and the baseline savings available from a basic mid-market application that instills good process and cost intelligence) and 50% of 20% (as it is able to take advantage of at most half of the advanced functionality offered by the suite due to poor and incomplete data). In other words, at the end of the day, we’d argue an average company is only realizing 23% of the potential value from an opportunity perspective!

However, as one should rightly point out, the true value of a suite is not the value you get on the base, it’s the ROI on that extra spend that allows for 20% more opportunity than a customer can get from lesser peer ProcureTech solutions.

For example, let’s say you are a company with 1B of spend with a 100M opportunity.

If tackling 20M of that opportunity requires advanced analytics, optimization, and extensive end-to-end data, it’s likely that you’ll never see that with an average mid-market solution with limited analytics, no optimization, and only baseline transactional data. If the company paid an extra 1.5M over 3 years for this enhanced functionality, then the ROI on that is 13X, which is definitely worth it.

Moreover, if the suite supports the creation of enhanced automations, you could get more throughput per employee and realize the base 80M with half or one quarter of the workforce, which would lead to a lowering of the HR budget that more than covers the baseline cost.

However, ALL of this requires great data, advanced capability, and the in-house knowledge to use both. This is only the case in the market leaders. As a result, we’d argue that the majority of clients are only realizing about 25% of the suite’s potential — when sometimes the only thing standing in their way of realizing the rest is good data.