by Britney Joseph (jennibirchwrites@gmail.com)
Contract management is essential for a lot of modern businesses. It helps to establish legal protections, save money, streamline operations, and, as noted in our article on ‘Contract Management Benefits’, improve functional efficiency. These benefits speak for themselves and make it clear why any modern business that deals in contracts should partake in a comprehensive management plan. However, that last perk — improving functional efficiency — is only really a factor if the contract management practice itself is made efficient. This is where data analytics comes into play. Typically, we tend to think of data analytics as being particularly important to a few specific industries. We consider the role of data in retail; we understand how it has transformed shipping and logistics; increasingly, it’s even been connected to healthcare and the coronavirus! An analysis by a University of Michigan associate professor suggested quite logically that retail-style analytics could help with testing (and now, we’d add vaccine distribution). These indeed represent some of the most well-understood and newsworthy applications of data analytics. But rest assured, it plays a role in contract management as well.
What this role looks like can vary from one business to the next. A large company working with B2B contracts will operate differently from a school system negotiating with suppliers, which will, in turn, work differently from a small startup doing B2C contracts, and so on. Generally speaking though, there are a number of things that data analytics in contract management can help with:
Sorting the success of different contracts. How many were negotiated? How many led to successful business relationships? How many were breached or dropped?
Identifying success patterns. Among contracts that led to a cost-effectiveness successful business, was there a common framework?
Identifying missed opportunities. Among failed or dropped contracts, are there clear explanations? Do those explanations match or form trends?
Gaining insight on timing. How long has it taken to negotiate contracts? Are certain types of contracts completed more efficiently? And if so, are there clear reasons why?
Determining cost-effectiveness. Did high-value contracts require significantly more resource investment than low-value ones? If so, was business from the low-value contracts ultimately worth the effort?
These are all subjects and questions that can best be addressed via the compilation and analysis of data. And ultimately, that analysis (and the answers to the questions above) can help to streamline a contract management operation and lead to more efficient and effective practices moving forward. But how exactly do you implement data analysis in your contract management efforts? Two main options come to mind.
One is to contract or employ a data professional. Not long ago this was a challenge; data analytics was an emerging field, and experts were few and far between (and expensive). More recently though, as the field has continued to expand, so too have programs churning out people with the ability to work in data. This has happened on college campuses around the country, but also through online institutions offering advanced data education to working professionals — such that even those who may have started other careers can circle back to get qualified in data science. As a result of this combination of demand and training opportunity, growth in data analytics is now projected to be explosive — to the tune of a CAGR of 13.2% through 2022, according to the online business data analytics degree page on Maryville University.
The other option is to pursue methods for automating data collection and analysis. Automation is actually something that is already a part of many modern contact management operations. As stated in a Business-2-Community piece on contract management, automation can streamline all three standard phases: pre-execution, execution, and fulfillment and reporting. This is perfectly accurate when contract management software is applied to the process, but we would also add analysis as a sort of fourth phase (and one requiring different software). Once contracts are executed and logged, the right program can help to translate results into actionable data. Whatever the chosen method is in the end, it’s clear that a strong data analytics practice can help any modern organization dealing with contract management. It’s simply a matter of getting it all set up.
Specially written for opensourceinc.com
by Britney Joseph
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API (application processes interface) uses to connect to company applications, added a secured Deal-Room/Data-room, bidding system, and allow external users to log in to their dedicated data-room.
Now the company can have (BI) Business Intelligence processes with Reports and AI (artificial Intelligence) integration for document analysis and data extraction processes.
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opensourceCM is a cloud-based SaaS (software-as-a-service) solution. When uploading a text or MS Excel document the application performs OCR, indexing and then recreates each document as an HTML document allowing easy document comparisons (e.g., between MS Word and scanned PDF docs). It also has the capacity to find words, values, phrases, terms of art, or specific legal language within documents that are hyperlinked to the actual highlighted location in each document. This can be accomplished across document data sets that may comprise tens of thousands of documents. Furthermore, opensourceCM provides a contract authoring workflow, calendar and notifications workflow, support SSO (single sign-on), and encrypted secured access. The application offers the ability to simply create Negotiation Deal-Rooms and Users Data-Rooms (internal/External) or Flexible Bidding System with Advance Q&A. We offer an API (Application Processes Interface) Library like office 365, BOX.COM, Salesforce, MS-Dynamics, NetSuite, OKTA, Dropbox, DocuSign to mention just a few.
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