Digitization is the way forward in Procurement

There’s a reason robots are given human-like names. Because they are meant to fit in, and they may replace us. Let’s talk about procurement in particular. Procurement management is one of the major skills to learn in the project management process.

People know about it, but not everyone has mastered it. In today’s world, knowing a skill simply does not cut it. You have to move forward with the time, and digital procurement is the future.

Divisions in Procurement

Transactional Procurement

This subset of the procurement process includes processing deliveries, creating and validating invoices, inventory management, initiating and completing payments. For such rule-based, procedural tasks, businesses are already leveraging the benefits of Robotic Process Automation (RPA) solutions. In layman’s terms, RPA software is a digitalization tool that aids in the creation of programs (bots) that can execute simple, repetitive, stepwise procedures. RPA software can utilize added support from Natural Language Processing APIs and Optical Character Recognition(OCR) engines to add a layer of basic intelligence. Automating this subset of procurement is beneficial as it saves time, effort and also reduces manual error. It is also cost-effective as the organization saves up on the cost of human mishaps and cost of staff payments. The processes are done on time, and any possible future delays can be predicted via simulation.

Strategic Procurement

Processes under this subset include manipulating a large amount of data present to come up with various analyses keeping numerous constraints in place. Data analysis is used for planning efficient supply chain management. Actions, such as choosing the best picks of suppliers, drawing cost estimates, choosing the optimal price and value for the services are performed. The key tool for digitizing these is Artificial Intelligence. AI and Machine Learning can be utilized for making future predictions and doing trend analysis. AI is a collective term for a set of software technologies and techniques that use computing power to mimic the human brain and intelligence. The results of an AI model improve over time as it ‘learns’ better and is exposed to more and more data over time. There is a lot of scope for using the prowess of AI and saving time and effort. The processes are complex with a lot at stake and need some amount of human supervision as of now.

Another technology that can be utilized in this domain of processes is 3D printing for prototyping and scaling it to calculate fair estimates of costs and time.

Supplier Relationship Management

This includes building supplier associations, metric formations for evaluating profitable suppliers, and eliminating low contributors. There was a time when everything was streamlined based on ‘word of mouth’ deals or trust-based deals. But given the high competition in every field today, it becomes vital to ensure not just selecting the finest of all suppliers but also building and maintaining trustful relationships with them. Softwares for digitizing SRM come in the form of blockchain for securing payment gateways and avoiding contractual frauds, crowdsourced supplier audits for increased confidence in supplier’s capacity for delivery, and monitoring system for performance tracking.

Challenges in Digital Procurement

Digital Procurement has promising growth, but like every other opportunity, it has its own set of challenges and unanswered questions. The prime hurdle is the huge technological gap that is encountered while transforming legacy to digital methodologies. It is not a transformation that can be brought about overnight; organizations need technical and field expertise to navigate successfully through this change. Organizations need both monetary and human resources for this change.

As these are upcoming trends, people who possess the knowledge and skills for operating digital tools are a small subset and are in high demand. Expertise is mandatory as simply employing RPA services isn’t enough; optimizing it for best results is key otherwise, it will create more problems than it solves.

Now about the processes which need intelligent decision making a.k.a strategizing- Various options need to be evaluated, various constraints need to be considered, and that’s where AI comes into play. It can deliver the output, but can it be trusted 100%? We trust humans because we have insight into their thought processes; we know how they arrived at the decision. The whole challenge with AI comes with the fact that we don’t know the internal working of those black-box models.


Apart from these challenges, numerous others are unique to the organization. But leaders all over the industries have identified the ever-growing potential of digital technologies and are jumping on the digitization train sooner than later, with the pandemic fast-forwarding the trend.

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