Setting the context
Over the last decade organizational contracting has largely seen gradual movement from being a legal and compliance dominated activity to a more business process activity managed by professionals specializing in contracting. Maximizing business performance and minimizing risks though contract management are, if not outdated, normally accepted advantages and benefits of contract management. As we enter the new decade, contract life-cycle management (CLM) is transforming into cloud-based software as a service that is driven by automation, may it be workflow, creating a supplier specific agreement draft or abstraction and analysis of contract data. Data scientist and software engineers, along with contract professionals are the new generation professionals leading this wave of transformation.
With every newer version of CLM platform (be it any provider in the market), I see a movement closer towards an improved automation functionality, influx, and introduction of automation in CLM steps –
(1) Contract Request, (2) Contract Negotiation (review and redlining), (3) Contract Approval Workflow, (4) Contract Execution, (5) Contract Repository/Archival, (6) Contract Record Management, (7) Contract Search and Information Retrieval, (8) Contract Audit and Reporting, (9) Contract Renewal and Closure.
Recognized and manifest benefits of CLM automation
Plethora of literature is available on benefits of CLM, primarily focusing on benefits like improved functional efficiency, supplier visibility, and compliance. Additional supporting causes for implementing an enterprise wide CLM are reducing costs and time involved in contract administration thus preventing contract attorneys and managers from functioning as contract administrators.
Inadequate or poorly implemented CLM can result in uncertain and varied contracting terms and inefficient contracting processes which can prove detrimental to the organization's brand equity and prove to be pricey in the long term due to the unpleasant user experience, it creates.
I would like to sum up the common knowledge on first and foremost benefits that organizations derive from an organized and properly implemented CLM system, which are: (1) Ability to establish objective timelines for each step in the contract lifecycle leading to setting up the right stage for increasing functional efficiency and properly allocating staff to workload, (2) Ability to create an audit trail for contracting workflow and approvals for each executed contract, (3) Ability to effectively implement organizational policies and contracting rules for each executed contract, and, (4) Ability to manage compliance, deliverables and performance on contracts with suppliers.
Undiscussed benefits of contract life-cycle management automation
As the enterprise CLM process and system matures with technology penetration, in the long run, organizations become well set to leverage the CLM for greater good.
In this article, I am going to explain the beneficial outcome that organizations can realize in long term (say a period over 2 years) by adapting and implementing enterprise-wide contract life-cycle management automation.
An agile roadmap for the organization
Today's businesses are faced with ever-changing business environment, rapidly evolving customer demands, dynamic regulatory and compliance requirements, uncertain and unpredictable near future. For running a business in this ambivalent ecosystem, and more so for building a resilient and future-ready organization, speed and agility are imperative. Adept start-ups and digitally native companies that are disrupting traditional markets with digital offerings, are implementing agile in legacy businesses. We need to note that Agile adaptation in these nimble start-ups is at an organization level, which is over and above their IT departments.
Implementing a CLM platform can be the most relevant Agile adaptation initiative for digital transformation of a business process on an enterprise-wide scale. What makes CLM implementation the ideal start-point for organizational Agile adaption is the unique inflection of human and machine effort touching every vantage point in the organization, required for a successful CLM adaption.
If implemented on a large scale, CLM will touch each core and non-core function in the organization that include, business functions, finance, accounts, procurement, sourcing, legal, compliance, contracting. An Agile approach for an enterprise-wide roadmap for implementing CLM platform can be the first great move toward introduction of Agile to a non-IT, traditional top-bottom organizational structure.
CLM implementation is necessarily not like other digital transformation initiative for the fact that it requires focused human intervention on a technological base, to get the CLM to flight. For example, pile-load of legacy contracts which may or may not be digitized to a uniform machine-readable quality certainly require manual review.
I propose to present more detailed arguments for organizational Agile implementation with CLM implementation in a subsequent article.
Hand offs integration from sourcing to Accounts Payable (AP)
An integrated procure-to-pay function (P2P) is need of the hour not only for giant global organizations procuring billions of dollars worth of goods and services annually but also for relatively smaller companies with ambitious growth and expansion plans.
We need understand the critical integrator role that an automated CLM platform can play in the P2P function. While the absence of an integrated P2P function adds costs and lengthens end-to-end cycle times, it also fails to address higher objectives of focused sourcing capability to leverage scale and managing fragmented business spend categories in large organizations. Most organizations tend to separate procurement and AP, with AP typically reporting into finance due to the accruals and procurement which may report into various functions.
The contracting function sits somewhere in the middle of these two separators, procurement on left hand side and AP on the right, with interactions that at best can be described as need-based and fragmented. Most of the organizations are just starting to realize how an upstream and downstream integration of an automated CLM in the P2P function is critical for transactional and strategic outcome of a harmonized and automated global P2P process.
A P2P workflow integrated CLM platform can upfront deal with some of the specific challenges reported by procurement and AP like matching to incorrect PO lines, routing invoices seeking resolution without proper research, resolutions not acted in time and POs with incorrect or mismatching payment terms caused by failure to link PO to contract, all leading to high invoice processing TAT.
On the contrary, organizations with P2P integrated with CLM have reported higher contract coverage and contract compliance, leading to improved ability to leverage contract management tool for savings & taking advantage of tiered pricing, tying of savings to annual operating plan, to name a few.
Use of AI/ML for larger purpose
The underlying platform for effective use of Artificial Intelligence (AI) and Machine Learning (ML) is data.
As CLM system continues to generate structured and/or unstructured enterprise data that can be leveraged by the AI/ML systems, organizations that have CLM deployed along with having in place a well-defined contracting process, are in the long run, well set to reap the benefits from AI/ML.
Most CLMs these days come equipped with powerful pre-trained and tuned Narrow AI applications which provide much higher precision and recall values than what we had a few years back. To process data and achieve desired results, AL/ML systems are based on algorithms or combination of algorithms like neural networks, decision trees, Bayesian belief networks, K-Nearest Neighbors, case-based reasoning, instance-based learning, hidden Markov models, regression techniques. Newer and additional data sets provide 'new fuel' to these algorithms or combination of algorithms to optimize their results each time and thus become more 'learned' with the passage of time. A more real-world analogy can be our new iPhone which comes pre-loaded with digital assistant 'Siri'. Siri is quite good with the instructions as we start with it, however its 'performance' curve continue to improve as we stay with it for more and more time.
While AI/ML is used to build learning systems to process information, Natural Language Processing (NLP) is kind of AI that involves language, and by combining ML, computational linguistic, NLP allows a machine to understand language. NLP's ability is to identify subjective information in text, which in case of contracts, includes contract terms. Approaches in NLP, may it be symbolic or statistical, need training data in the form of labelled text, to learn and provide desired outputs.
While most of us understand that AI/ML has made great advancements in automating review and extraction of relevant information from documents, including contracts, the ability to return search results in contracts that are not exactly the search phrases, by identifying and creating conjunction is the next level of ML is known as Latent Semantic Indexing (LSI). Its like me looking for termination for convenience in a contract set and the algorithm can dissociate termination for cause from convenience and throw out only the relevant results. LSI helps systems understand the essence and implication from various combinations of words, even across various locations in a document.
The point that I am trying to drive here is, more and varied data is key to superior performance of these technological advancements in AI/ML that come bundled with CLM systems today. Automated workflows in contracting cycle, precedence-based negotiation and redlining assistance, building most relevant agreement drafts from clause libraries, extraction of contract information from a set of contracts, etc are kind of CLM functionalities that provide amplified and superior results in the long run.
Summing it up
The Forrester Report1 notes that, CLM has become a strategic software product for executives, in short, the C-suites are just starting to realize that CLM is the missing piece in their strategy for future. The onset and continuance of the pandemic has augmented the importance of CLM as key to business preparedness and continuity.
Be it accelerated digital transformation, pandemic response, best utilization of AI/ML, data privacy compliances, secure information sharing in a 'no-travel' world, improving the end-user (supplier, customer, or employee) experience or climate aware contracting, adapting, and staying with an automated CLM in the long run is the answer.
Footnote
1. The Forrester Wave": Contract Lifecycle Management For All Contracts, Q1 2021
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
