… Don’t Forget the Contract, Part II

As pointed out in yesterday’s post, Contract Lifecycle Management (CLM) — which includes contract creation, management, analytics, and renewal — is becoming big and will likely get bigger still as organizations rely more and more on contracts to control price and mitigate risks. But, as we also pointed out yesterday, a contract lifecycle management system is not only useless without contracts to manage, but is also useless without good contracts to manage.

Poorly created contracts that don’t define anything more than a bulk price and a term don’t ensure defensible pricing, loss management, or risk control. To be more exact, they don’t even ensure that absence of a typo or careful insertion of a single word by a litigious lawyer that could negate and entire contract and make it totally useless.

So where do you start?

Define the need

What do you really need? (And what are the core requirements?) When? Where? How do you need it delivered? Who is responsible for the production, delivery, support, and return? Why does it need to be this way? What are the risks and how will they be mitigated? Split?

Create a Statement of Work

Clearly specify what is required, when, by who, in what quantity, how it is to be packaged, stored, delivered, supported, maintained, and recovered. Specify delivery dates for products if known or delivery timeframes if exact dates are not known but response or replenishment times are needed. If the contract revolves around the construction of a particular deliverable (system, machine, building, etc.) specify key milestones and acceptance criteria. If it revolves around ongoing services, specify delivery timeframes and required service levels. Specify as much detail as is known and where specifics can’t be specified up front, specify how the details will be worked out later and agreed to, as well as the procedure that will be followed in case of disagreement or conflict.

Make sure Milestones are Clearly Specified
… with Deliverables and Acceptance Criteria

Go so far as to explicitly number the milestones and make sure they are easy to index, track, and assign to buyers, supplier managers, and other organizational individuals who are affected by the contract. It should be easy for the CLM to auto-index these milestones and even auto-assign the milestones (and monitoring management responsibilities) to the most logical individuals in the organization (who can reassign if necessary).

Make sure the deliverables are clearly annotated, that precisely what they entail is defined, that the acceptance criteria that will be used are spelled out in sufficient detail to allow work products to be rejected if they are not up to requirements, and who has final determination of whether those criteria are met. Also, if there is a dispute, the process that will be used for resolution must be indicated.

Define the Payment Schedule
… and Tie it to the Milestones

Don’t just specify how much will be paid, but when it will be paid, and what the dependencies are on the milestones and deliverables. Also specify if there are any penalties for late or unsatisfactory delivery, precisely how they are calculated, and when the remaining payment(s) will be made. Also clearly specify how disputes will be filed, handled, and resolved and whether any payments will be made during the dispute, and in what amounts.

Define any SLAs and Warranties the Supplier Must Adhere to

Do so up front and in plain English. It’s critical that the supplier understand exactly what is being expected, how it will be measured, what guarantees the supplier is making, and what it will cost them if they are not adhered to. If the products are rejected, do they have to deliver replacements? Are they penalized? Is the contract terminated?

Then, and only then, start thinking about writing the contract. But don’t write it yet!

It’s Easy to Get Lost in CLM — But Don’t Forget the Contract! Part I

Contract Lifecycle Management — which includes contract creation, management, analytics, and renewal — is becoming big and will likely get bigger still as organizations rely more and more on contracts to control price and mitigate risks. And since no one can ever find a paper contract once it’s been sent to filing, the ability for anyone anywhere at anytime to access a relevant contract, compare deliverables and prices to negotiated deliverables and prices, track (evergreen) renewals, and determine which party is responsible for a loss is almost priceless.

That being said, a contract lifecycle management system is not only useless without contracts to manage, but is also useless without good contracts to manage. Poorly created contracts that don’t define anything more than a bulk price and a term don’t ensure defensible pricing, loss management, or risk control. Nor do they ensure termination, as evergreen status could be implied if orders are still made after termination and pricing is still honoured. Nor do they even imply that the supplier even has the right insurance or certifications to even produce or ship the products the supplier is selling to you.

In order to control risk, mitigate loss, and realize the expected benefits, a good contract is critical. This not only requires good negotiation, but good contract drafting that covers all of the necessary T’s and C’s, including those you never hope to need. All of them. And, more importantly, that spells out all of the requirements of both parties in terminology that cannot be easily misinterpreted or twisted by leeching litigious lawyers who will bleed both parties dry in legal fees before an agreement or decision is reached.

So how do you get a good contract? Well, as the legendary Dick Locke once wrote in our classic post on Blogging on International Contracting, not only should your contracts be in plain English, but they should be written with a high reading ease score (40 or more in Microsoft Word) and a grade level requirement of 11 or less. Especially since the contract is not likely to be in the supplier’s native language if the contract is with an international supplier.

After all, as Mr. Locke so keenly pointed out in a follow up piece on Simplified Contracts, Part 3, if you let a litigious lawyer write a contract from a supplier with a slimy sales team, he could easily insert just one word in a twenty page contract with an average sentence length of 73 words and paragraph length of half a page that negates the entire contract, and you’d never know.

So how do you write a good contract? We’ll explore that in this series.

The UX One Should Expect from Best-in-Class Spend Analysis … Part V

In this post we wrap up our deep dive into spend analysis and what is required for a great user experience. We take our vertical torpedo as far as it can go and wrap the series up with insights beyond what you’re likely to find anywhere else. We’ve described necessary capabilities that go well beyond the capabilities of many of the vendors on the market, and more will fall by the wayside today. But that’s okay. The best will get up, brush off the dirt, and keep moving forward. (And the rest will be eaten by the vultures.)

And forward momentum is absolutely necessary. One of the keys to Procurement’s survival (unless it really wants to meet it’s end in the Procurement Wasteland we described in bitter detail last week) is an ability to continually identify value in excess of 10% year-over-year. Regardless of what eventually comes to pass, the individuals who are capable of always identifying value will survive in the organizations of the future.

But if this level of value is to be identified, buyers are going to need powerful, usable, analytics — much more powerful and usable then what the average buyer has today. Much more.

As per our series to date, this requires over a dozen key useablity features, many of which are not found in your average first, and even second generation, “reporting” and “business intelligence” analytics tool. In our brief overview series to date here on SI (on The UX One Should Expect from Best-in-Class Spend Analysis … Part I, Part II, Part III, and Part IV) we’ve covered four key features:

  • real, true dynamic dashboards,
  • simultaneous support for multiple cubes,
  • real-time idiot-proof data categorization, and
  • descriptive, predictive, and prescriptive analytics

And deep details on each were provided in the linked posts. But even prescriptive analytics, which, for many vendors, is really pushing the envelope, is not enough. Great solutions really push the envelope. For example, the most advanced solutions will also offer permissive analytics. As the doctor has recently explained in his two-part series (Are We About to Enter the Age of Permissive Analytics and When Selecting Your Prescriptive, and Future, Permissive, Analytics System), a great spend analysis system goes beyond prescriptive and uses AR and a rules-engine to enable a permissive system that will not only prescribe opportunities to find value but initiate action on those opportunities.

For example, if the opportunity is a tail-spend opportunity that could best be captured by a spot-auction, approved products that meet the bill, and approved suppliers that can automatically be invited to an auction to provide them, the system will automatically set up the auction and invite the suppliers, and if the total spend is within an acceptable amount, automatically offer an award (subject to pre-defined standard terms and conditions).

And that’s just the tip of the iceberg. For more insight onto just how much a permissive analytics platform can offer, check out the doctor and the prophet‘s fifth and final instalment on “What To Expect from Best-in-Class Spend Analysis Technology and User Design” (Part V) over on Spend Matters Pro (membership required). It’s worth it. And maybe, just maybe, when you identify, and adopt, the right solution, you won’t end up wandering the Procurement Wasteland.

The UX One Should Expect from Best-in-Class Spend Analysis … Part IV

As per our last post, in this series we are diving into spend analysis. Deep into spend analysis. So deep that we’re taking a vertical torpedo to the bottom of the abyss. And if you think this series has been insightful so far, wait until we take you to the bottom. By the end of it, there will be more than a handful of vendors shaking and quaking in their boots when they realize just how far they have to go if they want to deliver on each and every promise of next generation opportunity identification they’ve been selling you on for years.

We’re giving you this series so that you can use it to make sure they deliver. Because, as we have repeatedly pointed out, you only have two technologies at your disposal to achieve year-over-year savings of 10% or more. Optimization (covered in our last four-part series, see Part I, Part II, Part III, and Part IV), which can capture the value, and spend analytics, which can identify the value.

But, as we will keep repeating, it has to be true spend analytics that goes well beyond the standard Top N report templates to allow a user to cube, slice, dice, and re-cube quickly and efficiently in meaningful ways and then visualize that data in a manner that allows the potential opportunities, or lack thereof, to be almost instantly identified.

But, as per our last two posts, this requires truly extreme usability. Since not everyone has an advanced computer science or quantitative analysis degree, not everyone can use the first generation tools. This means that, in organizations without highly trained analysts, the first generation tools would sit on the shelf, unused. And that is not how value is found.

However, creating the right UX is not easy. That’s why it takes a five part series just to outline the core requirements (and when we say core, we mean core — there are a lot more requirements to master to deliver the whole enchilada). But it’s needed because we are in a time where there seems to be a near universal playbook for spend analysis solution providers when it comes to positioning the capability they deliver and when many vendors sound interchangeable when, in fact, they are not.

In each part of the series to date (What To Expect from Best-in-Class Spend Analysis Technology and User Design Part I, Part II, and Part III), over on Spend Matters Pro [membership required], the doctor and the prophet have explored three to four key requirements of a best-in-class spend analytics system that are essential for a good user experience. Here on SI, we’ve covered three of these to whet your appetite for the knowledge that is being kept from you.

In The UX One Should Expect from Best-in-Class Spend Analysis … Part I we discussed the need for real, true, dynamic dashboards. Unlike the first generation dashboards that were dangerous, dysfunctional, and sometimes even deadly to the business, true next generation dynamic dashboards are actually useful and even beneficial. Their ability to provide quick entry points through integrated drill down to key, potentially problematic, data sets can make sharing and exploring data faster, and the customization capabilities that allow buyers to continually eliminate those green lights that lull one into a false sense of security is one of the keys to true analytics success.

In The UX One Should Expect from Best-in-Class Spend Analysis, Part II, we pointed out that one cube will NEVER be enough. NEVER, NEVER, NEVER! And that’s why procurement users need the ability to create as many cubes as necessary, on the fly, in real time. This is required to test any and every hypothesis until the user gets to the one that yields the value generation gold mine. Unless every hypothesis can be tested, it is likely that the best opportunity will never be identified. If we knew where the biggest opportunity was, we’d source it. But the best opportunities are, by definition, hidden, and we don’t know where. Success required cubes, cubes, and more cubes with views, views, and more views. But this is just the foundation.

Then, in The UX One Should Expect from Best-in-Class Spend Analysis, Part III, we indicated that success requires appropriately classified and categorized data. But good data categorization is not always easy, especially for the average user. That’s why the third key requirement is real-time idiot-proof data categorization, which, while a mouthful, is a lot easier to say than it is done. (For details, check out the articles.)

But, as you’ve probably guessed by now, more is required. Much more. In “What To Expect from Best-in-Class Spend Analysis Technology and User Design” (Part IV) over on Spend Matters Pro [membership required], the doctor and the prophet dive deep into a couple of additional key requirements for a best-in-class spend analytics solution. And, like the previous requirements, these are intensive. Quite intensive.

The one we are focussing on today is support for descriptive, predictive, and predictive analytics. First generation solutions stopped at descriptive. They simply reported on what happened in the past, and stopped there. And usually the description of the past was so far behind that the reports were not always that useful. So next generation moved onto predictive, and computed trends, taking into account historical sales data and current market data to describe opportunities so that, even if the data was a bit outdated, at least the analyst had a good idea of direction.

And as platforms got faster, and more powerful, and more real-time, the predictive power got better, and more useful. And organizations realized more value … but not nearly what they should realize. Because it’s not always enough to know that there may be an opportunity, to realize that opportunity, one needs an idea on how to capture it. And if one’s not a category or market expert, one can be completely lost. But if the system supports prescriptive analytics, then the analyst has an idea where to start. And that is key to a great user experience.

But is that everything the system needs for a great user experience. Nope. And we’ll continue our overview in the next, and final, part of this initial series. (We’ve written the first few chapters, but believe us when we say the book has not been written yet.)

The University is Still Here Because …

A couple of years ago TechCrunch wrote an article that asked Why is the University Still Here? In a time where information is universally accessible, knowledge can be compiled by experts and shared in a reviewed and verified form far and wide, and intelligence can be conveyed direct from an expert in Oxford (England) to an able learner in Liberal (Kansas) if both are ready, willing, and able thanks to virtual classrooms with audio-visual conferencing and screen sharing.

Then, earlier this decade, we saw the launch of massive open online courses (MOOCs) where anyone can register for a course from a leading professor, get the lectures, complete assignments, send them to TAs (teaching assistants) half a world away, get graded (automatically for multiple choice and by a human for essay or problem solving questions), and work towards what is supposed to be the equivalent of a University degree. But is it?

First of all, universities, even with remote learning aspects, have always been based on classroom learning. Secondly, advanced programs have always been based on one-on-one instruction between teacher and student. Thirdly, they have always been based on carefully structured curriculums that are designed to ensure a student gets an appropriate depth and breadth of knowledge. Fourth, the testing is always done in a manner that makes cheating or plagiarism difficult.

MOOCs are the antitheticals of University. They are trying to abolish classrooms. There is no personal one-on-one instruction between a recorded lecture and a semi-engaged viewer. The student can design their own haphazard curriculum that ensures neither depth nor breadth in the appropriate subject matter. And anyone can submit a document created by anyone else and there is no way to know.

But the failure of MOOCs to displace universities is not an argument for the continued existence of universities. Just because X does not displace Y, that doesn’t mean that Y is superior. It just means that the masses do not believe that X is superior. In our case, it’s not enough of a case for universities.

To make the case, we look at where MOOCs failed. As per the techcrunch article, they failed in keeping a user’s interest. Most people who registered for and even started a course, never completed. Most who completed didn’t come back. They weren’t motivated. The reasoning in the article is that because, for the majority of learners, it was part time, on their own time, it never got primacy and without primacy, efforts get abandoned.

And that’s part of the reason MOOCs failed and part of the reason we still need Universities. When you go to University, you make education a primary focus of your life. But the other reason is that a real, established, prestigious University provides something no other form of education can — a well-rounded full-featured educational experience with primacy, one-on-one instruction from an expert, great curriculums, and, most important, a community to share the experience with. This last aspect is key — you are part of a dedicated group of people there to learn and share the experience of learning and better each other in the process. And while that group shrinks a bit over the years, by the end, you have your own support group, and possibly a few colleagues for life, that got you there and take you further. That’s something you’ll never get from a MOOC.

And that’s why Universities still exist and need to continue to exist.