Tag Archives: tech implementation

The Dangers Of Dirty Data

Is your organisation working with ‘dirty data’? How would you know? And, what impact is it having? This article has everything you need to know about doing a quick spot check, spotting procurement problems, identifying savings, and more importantly, making sure your data has its COAT on.


We all think we know what dirty data is, but it can mean very different things depending on who you speak to.  At its most basic level, dirty data is anything incorrect.  In detail within procurement, it could be misspelled vendors, incorrect Invoice descriptions, missing product codes, lack of standard units of measure (e.g. ltr, L, litres), currency issues, duplicate invoices or incorrect/partially classified data.

Dirty data can affect the whole organisation, and we all have an impact on, and responsibility for the data we work with.  Accurate data should be everyone’s responsibility,  but currently across many organisations data is the sole responsibility of a person or department, and everyone trusts them to make sure the data is accurate.

But, they tend to be specialists in data, analytics and coding, not procurement.  They don’t have the experience to know when a hotel should be classified as accommodation or as venue hire, or what direct, indirect or tail spend is and its importance or priority.

How many times have you been working with a data set and noticed a small error but not said anything, or just manually corrected something from an automated report, just get it out the door on time?  It feels like too much of an inconvenience to find the right person to notify, so you just correct the error each time yourself, or you raise a ticket for the issue but never get round to checking if it’s resolved. 

These small errors that you think aren’t that important can filter all the way up to the top of an organisation through reports and dashboards where critical decisions are being made.  It happens almost every day.

How does this affect my organisation?

There are many ways, but one of the most widespread and noticeable impacts is around reporting and analytics.  If you’re in senior management, you will most likely receive a dashboard from your team that you could be using to review cost savings, supplier negotiations, rationalisation, forecasting or budgets.

What if within that dashboard was £25k of cleaning spend under IBM?  I can already hear you saying “that’s ridiculous” – well, it is obvious when pointed out, but I have seen with my own eyes IBM classified as cleaning.  It can happen easily and occurs more frequently than you might think.

Back to that dashboard that you are using to make decisions, you’ll see increased spend in your cleaning category, and a decrease in your IT spend, which could affect discounts with your supplier, your forecast for the year, monitoring of contract compliance etc…  It could even affect reporting of your inventory,  it appears you need more laptops, and unnecessary purchases are made. 

When there are tens or hundreds of thousands of rows of data, errors will occur multiple times across many suppliers.  And for the wider organisation, this could affect demand planning, sales, marketing and financial decisions.

And then there are technology implementations.  Rarely is data preparation considered before the implementation of any new software or systems, and there can even be the assumption that the software supplier will do this, which may not be the case, and if they do provide that service it might not be good enough.

It can be very far into the process of implementation before this is uncovered, by which time staff have lost faith in using the software, are disengaged, claim it doesn’t work, or they don’t trust it because “it’s wrong”.  

At this point, it either costs a lot of money to fix and you have to hope staff will engage again, or the project is abandoned.  In either case, this can take months and cost thousands, not millions of pounds/euros/dollars in abandoned software or reparation work.

You might also be considering using, or engaging with a 3rd party supplier that uses AI, machine learning or some form of automation.  I can’t emphasise enough the importance of cleansing and preparing your data before using any of these tools. 

Think back to the IBM example, each quarter the data is refreshed automatically with the cleaning classification, that £25k becomes £50k, then £75k the following quarter, it’s only when the value becomes significant that someone notices the issue.  By this stage, how many decisions have been based on this incorrect information?

How can this be resolved?

Truthfully, it’s with a lot of hard work.  There’s no magic bullet or miracle solution out there to improve the accuracy of your data: you have to use your team or an experienced professional to get the job done. Get your team to familiarise themselves with the data. If they are reviewing and maintaining it regularly they will soon be able to spot errors in the data quickly and efficiently.

If you think about data accuracy in terms of COAT, this will help to manage your data.

It should always be Consistent – everyone working to the same standards; Organised – categorised properly; and Accurate – correct.  And only when you have these things will it also be Trustworthy – you wouldn’t drive around in a car without a regular inspection would you?

How to spot procurement problems and identify savings

Accurate data is important, but in its raw state, it’s not the whole story.  As a procurement professional you’re tasked with ensuring the best prices for products or services, as well as ensuring contract compliance on those prices, along with cost reductions and monitoring any maverick spend … to name but a few!

Accurate data alone will not help achieve this, I strongly recommend supplier normalisation and spend data classification to help quickly and efficiently manage spend and suppliers, monitor pricing and spot any potential misuse of budgets.

How do I get started?

With a spreadsheet of spend transactions over a period of time such as 12 to 24 months, the first step should be Supplier Normalisation, where a new column is added to consolidate several versions of the same company to get a true picture of spend with that one supplier.  For example, I.B.M, IBM Ltd, I.B.M. would all be normalised to IBM.

Data can be classified using minimum information, such as Supplier Name, Invoice/PO line description and value. To get more from the data, other factors can then be added in, such as unit price. Where unit price information is not available, the quantity can be divided by the overall value.

A suitable taxonomy will then need to be found to classify the data.  It can be an off the shelf product such as ProClass, UNSPSC, PROC-HE, or a taxonomy can be customised so it’s specific to your organisation or industry.

This initial stage may take months if you are working with large volumes of data. It might be worth considering outsourcing this initial task to professionals experienced in this area, who will be able to complete the project in a shorter time, with greater accuracy.

Avoiding common pitfalls

There are a number of ways to classify the data> However, to get started, look for keywords in the Supplier Name and then the Description column.  The description of services could include ‘hotel, taxi, cleaning services, cleaning products, etc., however, it’s important to carefully check the descriptions before classifying, or errors could be introduced.  A classic example is “taxi from hotel to restaurant”, depending on which keyword you search for first, it could end up being misclassified as transport, or venue costs.

I wouldn’t advise classifying row by row, as it could take more than twice as long to complete the file using this method.  Start with keywords, followed by the highest value suppliers which you can get from a pivot table of the data if you’re working in Excel.

Identifying opportunities

Once classified, charts can be built to analyse the data.  The analysis could include, ‘top 80% of suppliers by spend’; ‘number of suppliers by category’; ‘unit price by product by month’;  ‘spend by category’; or ‘spend by month.’

Patterns should start to emerge which could reveal unusually high or low spend in a category, irregular pricing, higher than expected use of services, or a higher than expected number of suppliers within a category. 

Why you should strive for data accuracy and classification?

Data accuracy is an investment, not a cost.  Address the issues at the beginning: while it might seem like a costly exercise, you will undoubtedly spend less than if you have a to resolve an issue further down the line with a time-consuming and costly data clean-up operation.  And by involving the whole team or organisation, it will be much easier to manage and maintain the most accurate data possible.

Spend data classification shows you the whole picture, as long as it’s accurate.  You can get a true view of your spend, allowing improved cost savings, better contract compliance and possibly the most important – preventing costly mistakes before they happen.

So, does your data have its COAT on? What does ‘dirty data’ mean to you? Let me know below!

Susan Walsh is the founder of The Classification Guru, a specialist in spend data classification, supplier normalisation and taxonomies.  You can contact her at [email protected] https://www.procurious.com/professionals/susan-walsh

People Aren’t Adopting Your Tech: Now What?

How can you get your tech launch back on track if adoption is less than desired?


You’ve done your research, selected a new tech solution, secured buy-in from your C-Suite, and spent time setting it all up and testing that it works.  You have a detailed plan in place to measure success and everyone has attended training.  So, you press the button and ‘go live’, then sit back and watch the fruits of your labor grow.

Or maybe not.

After months of planning and integrating, user adoption is… underwhelming. In fact, the conversation at the water cooler is about how the new tech is a management fad and a waste of resources – and why the old ways are the best. And suppliers know they don’t have to make a change because they’re still getting paid in the old way.  All parties are still left wondering “What’s in it for me?” 

It looks like your implementation is reaching a state of emergency – so how do you convince people to take the new tech plunge?

1. Make Adopting Appealing and Achievable

Managing any big change is all about people and a tech adoption is no different.  It doesn’t matter how good the technology is if your end-users don’t embrace it.  Before you start out on your plan to get adoption underway, consider how well you know each user population and what could be their barriers to adopting?   

  • Have you been clear with users what the objective of the tech change is?

Take the time to ensure your end users clearly understand the case for change and why it’s necessary to implement the system.

  • Have you connected to their “why”?  What’s in it for them and their suppliers?

Making a connection with the emotional side of the brain is often critical in a period of change.

  • How well do you know their concerns/frustrations/fears for the impending change? 

Take the time to understand what may be your users greatest barriers to adopting.  Work together on finding solutions and let them ‘own’ the solutions you find. 

  • Are the steps toward adoption clear?  Do they understand the timeline?

Comprehensive plans, training and support are vital to keep things on track.

2. Keep It Simple

Don’t get trapped into the belief that just because this is the way it has always been done, that your process can’t be changed.  Too many organizations take cumbersome, complex processes and try to automate them.  They spent all this time shopping for an intuitive user experience for their employees and then they design/configure a solution that their users resist. 

Take a tip from the old US Navy design principle – Keep It Simple, Stupid (KISS) – to stop your potential state of emergency reaching a code red.

Configure your tech to first support most of your users and use cases. Don’t fixate on the complex or outliers. Based on our experience, when you adopt a critical mass of users the momentum will be restored, and your potential state of emergency will then pass.

Finally, as the Harvard Business Review advises, highlight anything that won’t be changing. Are there policies that will still be in place – for example, ‘no PO, no Pay’?  Reassure your users that it’s the ‘how’ not the ‘what’ that is changing. It helps to simplify people’s perception of the impending change.

3. Communicate and Make it Fun!

Don’t underestimate the need for a robust communication strategy from your executive leadership.  The higher in your organization the better. As Carol Kinsey Gorman stresses, talk about ‘what people want to hear and what they need to see’.  Think about how you want to present your message to drive adoption and then use all your powers of persuasion to generate excitement and buy in…so much so that they’ll want to start using it.

Remember, avoiding an impending state of emergency requires high-impact tactics to eliminate potential and real threats. When we communicate inside the business it is often boring and lacks appeal. We think that functional language and formats will suffice. Use change management and training teams to help craft fun and engaging messaging that will get your adoption points across.

All people are different and learn in different ways. Build training resources that use a range of different forms of media. Try video and audio alongside the written word. Onboard key people within teams to provide that personal connection and testimonial. They’ll become great champions to speed adoption throughout your organisation And if suppliers are part of your tech adoption process, communicate early and often with what is expected.   Then make sure you keep your message consistent no matter who is delivering it from your organisation. 

4. Plot a Clear Path to Code Green

Once your people know what’s expected of them and can buy into the change, the right support and a road map is all they need. Make sure you’re measuring the things you need to monitor progress with adoption, and that any risk can be mitigated.

Create metrics that identify individual progress on the adoption path, whether by users or suppliers, so you know exactly where they are. Be sure to monitor key influencers in the team, highlight quick wins and celebrate victories.  Target reluctant adopters for training or support. Using a continuous improvement approach, ensure users know that feedback is addressed.  Keep in mind that metrics can serve to reward as well as a means to course correct.

So, if your tech adoption process is starting to feel like a state of emergency there is plenty you can do to avoid reaching a code red. Focus on effective communication that engages your users where they are to take action, stay focused on meeting the needs of the masses, identify and address challenges early, and your new solution will become the talk of the company. 

To go deeper on the perfect tech implementation, tune in to our series ‘Major Tech Fails.’

After A Slow Start, AI Is Starting To Make Its Mark

Procurement has traditionally lagged behind when it comes to technology, but does AI offer an opportunity for things to change?

By GreenCam1/ Shutterstock

Artificial intelligence (AI) is going to make business better, at least that is what the solutions providers would have us believe. Businesses will be more agile, more efficient and, importantly, more profitable. Yet it still feels procurement is behind the curve when it comes to AI adoption, despite those that have implemented things, such as machine-learning and AI-driven data analysis, seeing the benefits.

Simon Geale, vice president of client solutions at transformation procurement services provider Proxima, says: “It is early days. On the procurement side of things, we are seduced by the hype over practicality. Most of what we are seeing is either aggregating data or speeding up a process, so far.”

That is not to say that businesses are shunning AI. A recent survey by McKinsey found 47 per cent of companies have embedded at least one AI function in their business processes, up from 20 per cent in 2017.

McKinsey’s research showed that while most companies were adopting AI in areas such as service operations, marketing and product development, a significant number have started to use the technology in managing their supply chains.

Some sectors, such as retail, are adopting the technology far more rapidly in supply chain management than others.

It may be time for those businesses on the long tail of adoption to speed things up. Of those that have adopted AI in supply chain management, McKinsey reports 76 per cent have seen moderate or significant benefits.

AI Focus on Efficiencies and Productivity

So how are companies using AI? A survey by RELX Group late last year shows a focus on using AI and machine-learning principally to increase efficiencies or worker productivity (51 per cent), to inform future business decisions (41 per cent) and to streamline processes (39 per cent).

There are those in procurement who believe AI will destroy their jobs. Yet not all are convinced of this nightmare scenario.

Trudy Salandiak of the Chartered Institute of Procurement & Supply says: “Unlike many professionals, we think procurement will be future-proofed from being completely taken over by technology due to the human interaction and relationship management required.

“What it will do is provide much more visibility over supply chains to manage risk and seek out opportunities for innovation. It will also take away the process back-office side of the role to allow procurement teams to focus on more strategic areas.”

Ms Salandiak sees a role for AI in quicker and more accurate fraud detection, intelligent invoice matching and categorising vendors to rank their strategic importance in the supply chain.

Chatbots for Procurement?

AI chatbots have started to be used to help businesses articulate their needs with procurement, instead of completing lengthy requests on enterprise resource planning (ERP) systems. This echoes the voice experience consumers get through the likes of Amazon Alexa and Google Assistant.

Turkish telecoms company Turkcell has implemented a procurement chatbot, which learns continuously and simulates interactive procurement professionals’ conversations with business partners and vendors by using key pre-calculated user phrases and auditory or text-based signals. The chatbot interfaces with the company’s ERP system and it has enabled procurement professionals to cut out non-value-added activities and allocate their time to more strategic topics.

Meanwhile, Ireland’s Moyee Coffee has been working on a project in Ethiopia where farmers, roasters and consumers can access data as beans are moved from farm to cup. Consumers are able to use QR codes on the back of coffee packs to see where the beans have been sourced and how much the farmers have been paid, bringing unprecedented transparency to the supply chain. The project uses Bext360’s Bext-to-Brew platform with AI, blockchain and internet of things technology.

AI Procurement Policy

As consumers demand more authenticity and transparency, this trend is likely to continue.

The forecast value of AI to the global economy is being recognised by the World Economic Forum (WEF). In September, the WEF’s Centre for the Fourth Industrial Revolution unveiled a plan to develop the first AI procurement policy.

The work is being done in conjunction with the UK government’s Department for Digital, Culture, Media and Sport. A pilot starts in July and it is hoped it will be rolled out in December. This will include high-level guidelines as well as an explanatory workbook for procurement professionals. A further eight countries have expressed interest in extending the pilot globally.

The reason for putting together a policy now is that “regulation tends to be too slow”, says Kay Firth-Butterfield, WEF’s head of AI.

“From the procurement perspective, it’s drawing a line in the sand, saying this is how we expect AI to be produced in our country and we will not accept AI products that do not meet these criteria. It is agile governance,” says Ms Firth-Butterfield.

Reorganising Time for Strategic Tasks

The technology will also allow public sector employees to do more strategic work. “In government, there are back-office gains to be had to free up civil servants to do more,” she says, adding that work on AI procurement in the public sector is expected to transfer to the private sector.

“Governments want their citizens to be at forefront of developing and using this tech, and benefiting from the economic gains,” says Ms Firth-Butterfield. “Governments’ significant buying power can drive private sector adoption of these standards, even for products that are sold beyond government.”

The 53 per cent of companies that have not started implementing AI may like to start thinking about it now.

This article, edited by Peter Archer, was taken from the Raconteur Future of Procurement report, as featured in The Times.  


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4 Realities of a Cloud Spend Management Implementation

Implementing new tools and systems is enough to make the bravest of procurement pros shudder with dread. So what are the four biggest risks associated with cloud spend management implementation…

With a wide array of cloud-based applications on the market, many organisations are saying goodbye to out-dated, legacy systems and adopting new Software as a Service (SaaS) solutions. These tools are changing the game in spend management, providing companies with increased visibility across all areas of spending and identifying new opportunities to drive cost savings.

However, despite all of the obvious benefits associated with these cloud systems, implementing a new tool across an enterprise can still be very challenging. For example, change resistance is often problematic when it comes to encouraging end users to utilise new systems. Without proper planning, you risk running into multiple issues that could derail the process and prevent a successful implementation.

Below are the top four risks associated with implementing cloud-based spend management solution:

  1. Getting Suppliers On Board

To successfully implement a new spend management solution, supplier enablement is imperative. The amount of work that’s necessary to get all of your suppliers on board with the implementation is commonly underestimated. In order to get it right, you should develop a supplier enablement strategy that carefully outlines each step of the process. Make sure you clearly communicate all of the changes that will take place, what your expectations are for suppliers, and how implementing the new tool will improve day-to-day workflows.

  1. Navigating the Integration

Don’t believe all the hype that you hear during sales demo—take everything with a grain of salt and follow up with questions about the integration process. Even if the integration sounds simple, remember that somebody has to do the work. There are several things to address regarding integration: Who is doing the mapping and file transformation? Which Enterprise Resource Planning (ERP) system will be used? Whose standard is being adopted?. You will also want to learn the integration method and inquire about any limitations per integration object. Make sure the vendor spells out all of these details before you sign a contract. This will guarantee you aren’t met with any unwelcome surprises down the road.

  1. Achieving End-User Adoption

Although it has become much easier with SaaS-based source-to-pay (S2P) and procure-to-pay (P2P) systems, achieving end-user adoption is still one of the biggest challenges that organisations face when implementing a new tool. The resistance to adoption typically begins when specific use cases are overlooked or not addressed appropriately. Lack of support from senior leadership, poor communication, and inadequate training can also be roadblocks to end-user adoption. You can avoid these roadblocks by considering all applicable use cases and crafting a detailed communications plan that includes all key stakeholders.

  1. Addressing All Use Cases

To avoid resistance and ensure your new spend management tool is meeting your needs, make sure you have selected a solution that will address each unique use case. Ask yourself: Who will be using the tool and for what purpose? Simply having an assortment of features and functions isn’t enough. In order for the implementation to be a success, you need to make sure you understand how the tool’s features and functions specifically address all of the use cases to ensure the solution meets your business needs.

Although it’s certainly important to keep these major risk factors in mind, don’t let these challenges get in the way of implementing a cloud-based SaaS solution at your organisation. Creating a carefully outlined implementation plan will help mitigate risks and ensure the process goes smoothly for everyone involved.

Are you having trouble selecting a new spend management system or navigating a complex integration? Contact RiseNow today for a free supply chain consultation to help get you started.

This article, written by Matt Stewart, was originally published on Rise Now