Tag Archives: procurement data

Is Data A Promise Or A Peril? 3 Things That Really Matter

Why do organisations and leaders face such a challenge in using data at all, much less using it effectively.

By red mango/ Shutterstock

It’s everywhere and it’s generated every second. Just texted someone? You created data. Just booked an Uber. You created data. Did some grocery shopping? You created data. And that’s before we even get to your professional context. Sending an email, making notes in a meeting, paying invoices, assessing your business strategy. It’s all data.

With ninety per cent of the world’s data having been created in the last two years, Domo’s recent report shares some staggering facts about the explosion of information; equivalent to approximately 2.5 quintillion bytes per day. Not quite sure what quintillion is? If I say a massive, it’s a huge understatement. But you get the idea.

So, with all of this data, why do organisations and leaders face such a challenge in using data at all, much less using it effectively. And with all the talk of digital transformation and the role of analytics driving new insights, why is it proving so hard to translate data into meaningful actions and outcomes? These three things really do matter:

1. Upgrade your business and your thinking

Historically, legacy systems, fragmented business models and poor documentation are all elements that contributed to the difficulty of accessing meaningful data. Historically, organisations would have to work for months to collate important data on every aspect of the business; customers, sales, financials, and forecasting to name a few. Data would often be incomplete, unclear, or in some instances, missing. If you weren’t looking for it, you would be working on cleansing it, a painful by-product of the adage of ‘garbage in, garbage out’. The paradox of the digital world is that this becomes so much easier and harder at the same time. Easier because the capabilities of technology allow analysis of data to be faster and more insightful than ever before. We can now find patterns in historical information, and create predictions that help businesses position resources where demand and customer expectations intersect. And prediction is the alchemy of organisational success. Studying classics at university, I understand that prophecy and prediction are all about enabling the competitive advantage. And technology can enable that with thankfully a lot more clarity than a Delphic oracle.

The flipside of this however is that systems, processes and models are not necessarily well positioned to take advantage of what is now possible.  Doing things the same way is not designed to deliver a different outcome and for many organisations looking for quick wins, the foundational and cultural changes required to achieve foundational transformation are too complex. It’s easier to implement a digital technology. While that will improve the current state, the absence of a more comprehensive improvement strategy means an organisation will only go so far. To capitalise on the real opportunity data must become part of the DNA.

2. Don’t tell me more, tell me what matters

Along with internal and market data, organisations are now able to access a new world of data. Social media, third party data including weather and GPS, IoT and devices. Today data is literally and metaphorically, Big. The opportunity for an organisation here is that they can learn and use so much information that was previously unavailable. The agriculture industry can use weather and IoT to identify optimal harvest time, and retailers can use their own loyalty and purchase data with social media to target customers with highly personalised promotions and offers. And so with the quantum of data being so big, leaders are faced with another well known conundrum; that of analysis-paralysis. Where the challenge previously may have been not knowing enough because it wasn’t available or feasible to access, leaders are now confronted with the proliferation of data that creates a risk around not knowing enough because there is likely more that should be known. The organisational problem this creates then is that leaders are unable or unwilling to make a decision because the breadth of information is just too confusing or because there is personal risk in making a decision that may be proven to be incorrect if more data presents itself. Another mindset shift is required here and that is for leaders to make a decision based on the best possible facts at the time, and be ready to adapt and course correct should new data provide a different option.

3. How you use it matters even more than what you have

Data and big tech companies present very interesting case studies for cross-industry insight on how data can be used, and misused.  Some companies, like Apple’s Tim Cook, have come out very publicly to discuss privacy and how consumer data should be used, and how it should be protected. Others, like Facebook, have been conspicuous in their silence and their absence on their use of data given it underpins their business model. The last two years have seen a significant change in sentiment on what we, as citizens and as consumers, are willing to accept and condone. And while the conversation is still being played out, and the resolution is unclear at this time, it does provide valuable insight for any organisation that is collecting data and contemplating options for how it can be used. Trust in brand, and trust in leaders cannot be separated from how an organisation conducts itself.

Teeing Up For AI in Procurement: It’s All About One Thing…

The benefit of AI for procurement is clear – the question, then, is what will it take to effectively put it to use?

Over the last year, machine learning and artificial intelligence (AI) technologies have graduated from the class of “emerging tech” – they’re here now, they’re increasingly sophisticated, and their adoption will only continue to accelerate.

We’ve seen machine learning and AI go mainstream in consumer tech environments, and they are rapidly shifting from hype to reality in enterprise environments as well; however, enterprise executives are still working to understand how AI applications can move beyond specific product features to influence broader business functions and strategies.

Let’s take a look at the procurement department, for instance. Procurement and purchasing professionals have a lot to gain from leveraging AI. In fact, AI has the potential to completely transform how organisations manage their spend, from automating invoice coding based on learned criteria, to predicting potentially fraudulent transactions, and preventing rogue spending before it happens.

The benefit of AI for procurement is clear – the question, then, is what will it take to effectively put it to use?

Gartner’s report, “Start Preparing Now for the Impact of AI on Procurement,” states that “technologies’ need for data will force application leaders in procurement to ensure access to the necessary internal and external data sources.”

Essentially, the first step to getting predictions out of AI is to capture all data – internal data, external data and third-party, public data. Furthermore, procurement professionals should be asking themselves if they have the volume, the quality and the completeness of data needed to leverage AI within their department.

Ticking each of these boxes can feel like an arduous process, but a good starting point is to hone in on three particular sources of data that provide the greatest visibility into spend:

1. Supplier Data: This means capturing data from 100 per cent of suppliers in the procurement system. Not just the largest multi-national suppliers who use sophisticated EDI or XML formats, but the whole tail. This should include mid-tier suppliers that may be using online portals or emailing PDF invoices, all the way down to the smallest “mom and pop” businesses, who continue sending paper invoices. Using an open commerce network that accepts and supports all invoice formats and requires no changes on the supplier’s end enables 100 per cent supplier onboarding and captures all transactional data. To gain true visibility and power future platforms, procurement and finance leaders must aggregate as much financial data as possible beginning with supplier data.

2. User-Driven Data: The ability to capture user-driven data–specifically, buying insights that track 100 per cent of all purchasing requests that run through the system, is vital. Visibility into employee spend ultimately depends on how user-centric procurement tools, technologies, and processes are designed. The bottom line is: procurement systems shouldn’t be designed for the procurement department. They should be catered to potentially thousands of employees around the world that are buying things in their organisation.

Searching for orders, dynamic routing and approvals, and guided buying, for instance, should be easy to navigate and fit seamlessly into the way employees already work. The key is to create a system that users adhere to not because they have to, but because it’s the easiest way to get what they want from preferred vendors at the negotiated price, providing another layer of spend visibility.

3. Invoice Data. By nature, the accounts payable function is primed for intelligent automation. There is a huge opportunity to use AI for things like improving processing efficiencies and reducing costs, increasing discounts and eliminating late payment fees, for instance.

But, these enhancements can only be achieved if the invoice data feeding into AI is complete. That means procurement needs to capture 100 per cent of invoices, irrespective of format (paper, PDF, electronic) and irrespective of invoice type (PO-based, non-PO based, invoices for direct spend, for indirect spend, for facilities and utilities, etc) –  truly, any and all. Whatever the invoice, it should be captured.

These three particular sources of data can truly position a company to take advantage of all the benefits AI promises just over the horizon. Elements of machine learning, AI and predictive analytics already exist within procurement today. Forecasting budgets for approvers, alternative cost-effective suggestions during a user’s shopping experience and intelligently aggregating POs based on purchase trends are just a few commonplace applications. But to take advantage of any of these applications, and future opportunities to gain a competitive advantage, data is an absolute prerequisite. Only when armed with data – especially from suppliers, users and invoices – can procurement make the most of their investment in AI technology, enhance spend visibility and optimisation, and ultimately, boost the organisation’s bottom line.

Continue reading Teeing Up For AI in Procurement: It’s All About One Thing…