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EFFECTIVE ACCOUNTS PAYABLE AUTOMATION: 3 PILLARS TO SUCCESS

AUTOMATION

By Kyle McNabb, SVP of product marketing

 

Ineffective accounts payable (A/P) processes are costing UK—and global—businesses considerably. According to the US’ Institute of Finance & Management (IOFM) each payment costs an organisation twice as much to process in an organisation with less effective A/P functions than it does in best-in-class companies.

With a dogged focus on cutting wasteful spend in many organisations, A/P should not be overlooked. Automation is one way leading organisations are finding points of savings in A/P, as doing so can significantly improve effectiveness and efficiency, reduce human errors and missed payments and ultimately boosts satisfaction ratings thanks to faster payment processing.

When done right, automation is also embraced by A/P staff, as it allows them to cut down the time spent on manual processing and instead gives them more bandwidth to focus on managing exceptions, developing relationships with suppliers and taking on new tasks.

Deploying the right software solution is a first step in a successful A/P automation project, but that effort must also take into account best practices in order to realise the greatest results.

 

AUTOMATION

Kyle McNabb

Centralisation

Centralisation and organisation are key to any effective accounting process. But in many organisations, the data leveraged by A/P comes from disparate sources. The company’s enterprise resource planning (ERP) system usually serves as the main source, but there are countless others. Consider, for example, the systems that reside with sales staff, external vendors, customers or other points along the supply chain, such as transportation carriers and manufacturing and warehouse facilities.

If the information needed to streamline the management of exceptions is not centralised—with data from different source systems connected via unique identifiers such as vendor ID, account code and customer name—then it cannot be leveraged seamlessly to automate payment processing.

Furthermore, a lot of content is available only as paper, PDF, image, etc. That content must be scanned to have critical data elements—such as the date, account number or amount—electronically captured and metadata created. Then, and only then, the content can be indexed and stored in a repository and database. From there, the invoice and associated supporting content can be linked and processed via workflow.

Some automated A/P solutions can integrate myriad information and content formats with their data repository. It’s important to confirm the solution you select can, in fact, cover formats such as Microsoft Word and Excel, PDF, email, video, scanned capture documents—and uses a variety of standardised methods to exchange information in electronic formats (e.g., XML, JSON and EDI). They should also intelligently index, archive and organise this content so that users can easily find and access necessary information. An effective automated A/P platform also includes auditing and reconciliation capabilities, which alert users to errors such as duplicate, short or delayed payments.

 

Integration

Centralisation entails storing all critical accounting documents related to A/P in a single place. However, in even the most streamlined enterprises, these documents still touch several different systems. Some documents are stored in an ERP system or a content-collaboration platform, but other crucial information often resides on paper, in sales contracts, on inspection certificates or elsewhere. Disparate systems that function independently and without effective integration only prolong accounting processes.

To be most effective, the payables software solution must be able to communicate with all core systems that house relevant documents. If it can’t, records can become “lost in the loop” and put the organisation at risk. To prevent this, any A/P automation solution should integrate with the company’s content services platform (CSP) and ERP systems. Integrating systems and federating content across them leads to substantially reduced processing times.

 

Unification

A/P-related systems aren’t the only software in the company that contains information relevant to A/P processes. Marketing, customer service, operations, manufacturing and legal, among other major departments, have some bottom-line impact on business operations.

Because A/P staff spend most of their time dealing with transactions that are not PO-based or with PO exceptions like mistakes in amount, quantity, price, payment terms, etc., having this information is critical to their effectiveness. And although this information exists in other departments, it is rarely made readily available to A/P to use when resolving exceptions.

Automated A/P solutions can centralise enterprise content beyond the documentation that is typically considered central to payables processes. When evaluating solutions, assess if the system uses standards-based REST APIs, low-code web-hook enabled content-centric workflows and content federation to access content stored in repositories used in other parts of the organisation. This approach will improve transparency and yield improved cost savings within A/P and the broader supply chain.

 

Reaping the Rewards

When a company is able to tighten its A/P processes, the entire business reaps the rewards. It eliminates the processing delays that result in inaccurate reporting, poor financial visibility, delayed business decisions, costly reruns and wasted money. It also allows money to flow into and out of an organisation faster. According to IOFM, organisations that apply A/P automation best practices can pay their non-PO invoices on time 96% of the time, compared to only 13% of those that are less automated.

The key to enabling that is to capture, manage, federate and audit content across the entire organisation and ensure systems work in concert across different departments and applications. Only with that centralisation, integration and unification can a company make more-informed business decisions and improve cash flow for the near and long term.

 

Technology

USING ARTIFICIAL INTELLIGENCE TO ACHIEVE CIRCULAR ECONOMY

By Professor Terence Tse, ESCP Business School

 

It is really only a matter of time before the two main trends, artificial intelligence (AI) and circular economy, would come together. A milestone of this convergence was the white paper “Artificial intelligence and the circular economy”: AI as a tool to accelerate the transition, jointly published by The Ellen MacArthur Foundation and Google earlier this year. It has kick-started the discussion on how AI can be used as a tool to help accelerate and scale our transition to a circular economy. This can be achieved by unlocking new opportunities through improving product and material design, enhancing circularity-based business models, and optimising circular infrastructure. The paper draws on the food and consumer electronics industries to illustrate the circular benefits driven by AI. The forecasted value that can emerge from these is encouraging: up to $127 billion and $90 billion a year in 2030, respectively.

 

The pace will be slow

No doubt these are very good news. It also shows how innovative technologies can take circular economy to the next level. Yet, I believe the path leading there will be full of challenges, not least because, contrary to what general media would like to get us to believe, the development of AI is, in reality, really slow.

 

There are several reasons attributable to this sluggish pace

First, there is a general shortage of AI-proficient graduates. Training up AI researchers takes time. Universities are not churning out data scientists fast enough to meet the job market demand. For those who are graduating, they will most likely be snapped up by the technology giants. Indeed, it has been estimated that some 60% of AI talent are in the employment of technology and financial services companies, leading to a ‘brain drain’ in academia, which in turn, slows down the production of qualified graduates. Small circular economy-based companies (as well as AI start-ups) will struggle to have the same hiring power, as they often lack the ability to match the levels of salaries and prestige offered by large organisations.

Another reason why circular economy-aimed companies, large or small, will struggle to deploy AI is that the technology remains a very expensive investment. AI is, at the moment, far from a plug-and-play technology. Arguably, there are off-the-shelf AI applications available in the market. But what this one size fits-all technology solutions can really do is often very limited and their effectiveness low. Inevitably, for AI to work at an acceptable, value-creating level, it is necessary to integrate it into the existing wider IT system. Customising AI applications to be embedded in the system architecture is very complex and hence very costly.

To make matters worse, the market is seemingly inundated with self-proclaimed AI companies. A recent report has suggested that 40 percent of start-ups in Europe that are classified as AI companies do not actually use artificial intelligence technologies in a way that is “material” to their businesses. As someone who researches and works in the business of AI, I can readily observe this phenomenon has already eroded the trust of many companies, making them increasingly cautious when proceeding with investment and deployment of AI.

 

Gradual developments, not quantum jump

For these reasons above, the adoption of AI, and by extension, in the area of circular economy, will be slow. This, however, does not mean there will be no advancement. Instead of “big bang” new business model creations, AI will most likely produce circular advantages through baby steps in operational enhancement gradually. For instance, one of the important elements in achieving circular economy is better asset management. In a recent research project for the European Defence Agency, my colleagues and I have discovered that there is a wide spectrum of operations for ministries of defence to save money and practise circular economy, from refurbishing and repurposing small military equipment items to reduce waste and minimise the use of virgin materials to extending the service years of capital assets. Unquestionably, the same may be applied to civilian activities. For example, combining the power of AI and drones can extend the longevity of major infrastructure such as reactors and bridges.

Advancements in drone technologies have allowed them to be deployed to take pictures at heights that are dangerous for inspectors to reach. The contributions of AI come from its ability to analyse and identify cracks as well as defects on assets that are not always visible to human eyes from captured images. Consequently, problems are detected before the assets become irreparable, thereby lengthening their lifetime.

A seemingly insignificant but potentially huge possibility of waste reduction would be saving on paper use. In the insurance industry, for instance, there is still a huge reliance on actual paper, with the communications between various stakeholders, including the underwriters, brokers and insured, passing on a large number of physical documents. AI techniques, in particular natural language processing, can help speed up the digitalisation of documents as they can go beyond the point of just reading and processing text to recognising and recording signatures and rubber stamp marks. Little by little, it will be possible to lower paper consumption.

 

The future is now

Both AI and circular economy are by themselves breakthrough ideas that are set to change the world dramatically. Combined, it can be a very powerful force of good. But this can only be achieved if we can synthesise them. For AI and circular economy to work together, it is necessary to educate AI developers to be more familiar with the idea of circular economy as well as making circularity practitioners and researchers more AI-savvy. Holding just half of the equation, we risk missing out on most of the intelligence. After all, no matter how smart machines can be, ultimately, it is the human intelligence – or stupidity – that determines the kind of future that we will be having.

 

Extract of “The AI Republic: Building the Nexus Between Humans and Intelligent Automation”

 

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IS BITCOIN SET TO HAVE A 2017-STYLE MINI BOOM THIS YEAR?

Bitcoin’s price is set to “surge before the end of 2020” with investors keen not to “sleepwalk” through a 2017-style mini-boom, says the CEO of one of the world’s largest independent financial advisory and fintech organizations.

The prediction from Nigel Green, the deVere Group CEO and founder, which has $12bn under advisement, comes as Bitcoin – already one of the best-performing assets this year – appears to be on the brink of a bullish breakout.

In recent days, Square, which is owned by the billionaire founders of Twitter, has allocated 1% of its cash reserves to the cryptocurrency, whilst a former Goldman Sachs hedge fund chief says the price of Bitcoin will jump to $1m in five years.

Mr Green comments: “There’s been something of an avalanche of interest in Bitcoin in recent weeks from household-name investors.

“Investor activity is picking up considerably with various on-chain metrics and ongoing – and heightening – global political, economic and social turbulence suggesting that there will be a price surge before the end of the year.

“Like gold, Bitcoin can be expected to retain its value or even grow in value when other assets fall, therefore enabling investors to reduce their exposure to losses.
“Investors will increase exposure to decentralised, non-sovereign, secure digital currencies, such as Bitcoin, to help shield them from the potential issues in traditional markets”.

He continues: “There’s a growing sense that we’re set to experience a mini-boom similar to that at the end of 2017.

“Prices are yet to catch-up with investor interest – but this is only a matter of time as investors will not want to sleepwalk towards perhaps year-high prices in the run-up to the end of 2020.”

The late 2017 bull run saw the Bitcoin price reach its all-time high of $20,089.

The deVere CEO concludes: “There’s been a notable ramping-up of interest in Bitcoin amongst investors since the end of summer. Indeed, it has been the best performing week for one of the year’s best-performing assets since July.

“I can see no reason why this upward trajectory will not continue between now and the end of the year.”

 

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