Tag Archives: cognitive technology

The Making of a Supply Chain Leader

What are the key skills  supply chain professionals should be developing in an AI-enabled future?

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“I’m a great believer in great passion,” says Ron Castro, Vice President, IBM Supply Chain. And it’s just as well given that Ron is responsible for all strategy, execution, and transformation of IBM’s US$70Bn global end-to-end supply chain, delivering to clients across more than 170 countries.

“Always be as bold and as fast as you can,” he says. “I’ve never looked back in a transformation and thought ‘Darn it! I wish I had gone slower.’ There’s always room to be bolder and to go faster.”

On Day Two of Career Boot Camp, Ron speaks to us about the greatest challenges and complexities of his role, the importance of leadership, and the key skills that supply chain professionals should be developing in an AI-enabled future.

Building a cognitive supply chain

“We’re at a point when new technologies are truly enabling us to take advantage of all kinds of data and giving us actionable insights close to real time,” Ron says.

“In our case, it all started several years ago when we built our transparent supply chain across [all] processes and systems, which gave us an excellent platform to apply advanced analytics and manage our business by exceptions. We set a very clear goal to become the first cognitive supply chain. This is based on our strong belief that with machine and human interaction we can truly augment supply chain professionals’ daily decision-making,” he says.

Ron points to several emerging technologies that provide incredible opportunity – AI (Watson, in IBM’s case), machine learning, blockchain, the Internet of Things, virtual reality, and 3D printing.

“Humans and machines always get a better answer than machine alone or human alone. With that principal we’re training Watson with our best supply chain experts [and] letting it observe our decision-making in digital resolution rooms,” Ron says. “Watson is learning in real time with us so it can help us to identify risks, predict issues and, as a trusted advisor, suggest our best course of action. How were similar problems tackled in the past? What are the risks or alternatives? Who should be involved or advise us on what actions we should be taking to manage the situation better and faster?”

“As we map the future of our supply chain it is crystal clear that we are getting the most value of our capabilities as we start to stack technologies together,” he says.

The challenge that’s keeping supply chain leaders up at night

“I have the pleasure of leading one of the most talented supply chain teams in the world,” Ron says. “I really love the adrenaline and all the variables that you need to be able to optimise it and the challenge of ensuring the right balance between demand and supply while [delivering] the highest quality and [focusing] on managing revenue cost.

“We are sensing and responding fast in the most intelligent way to any changes in the supply and demand equation, whether it be the introduction of new products, reacting to a natural disaster, geopolitical issues or supplier constraints,” he says.

But Ron also acknowledges that the tech industry is changing by the minute.

“[T]he challenge that keeps me up at night is are we transforming, are we moving fast enough and, more importantly, are we giving our team the tools they need to be successful?” he asks. “At the end of the day [are we building] an organisational culture that’s primed to leverage new technologies, unleash innovation, and challenge the status quo? Do we truly have the skills for the future?”

The making of a supply chain leader

 Ron always sees the need for strong leaders. “Some of the fundamentals [of leadership] don’t change; passion, perseverance, global and holistic thinking, collaboration and the value of diversity, [and] building a culture of feedback and continuous improvement,” he says.

Ron believes all these factors, indicative of a high-performance culture, will become even more critical in an AI-enabled future.

“We need leaders that take risks and drive a clear vision around digital supply chain and the need to be innovators; leaders that value experimentation over perfection [and] are willing to try new things and correct fast as needed,” he says.

Ron believes that leaders need a deep understanding of technology and where the trends are heading.“Disruptions are coming and they will hit us faster than ever so the ability to react becomes essential,” he says.

Ron advises aspiring supply chain professionals to take a step back and ensure that they are holistic, global, and horizontal thinkers. He encourages them to embrace new ways of working and collaborating with one another in order to become agile thinkers.

“In this new world the basics of supply chain are still critical so you can optimise a supply chain holistically from an end-to-end perspective. But you also need to be technically savvy,” he says. “The machine-human interaction will continue to increase and all these technologies will continue to become even more critical in supply chain.”

Data scientists will also be highly valuable, Ron says, as the ability to gather insights and ask the right questions will become critical for supply chain professionals.

Ron Castro is speaking on Day Two of Career Boot Camp 2018. Sign up here (it’s free) to listen to his podcast now.

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…

How to Prepare Your Organisation for the Cognitive Revolution

Everyone procurement team is talking about AI, cognitive technology and machine learning. But for these technologies to work at their best, your business needs to be prepared… 

Image: Zapp2Photo / Shutterstock

There is a lot of talk these days about Artificial Intelligence, Cognitive Sourcing, Machine Learning, and data-driven procurement.

Almost every major procurement organisation in the world talks about how their organisation uses these tools to make decisions.

The direction of procurement is almost certainly towards data-driven decision-making.  This is a reality we all need to embrace.

I certainly subscribe to the notion that the best procurement decisions come from fact-based data-driven strategies and I firmly believe that over time, cognitive tools and technologies will become better and more effective than they are Today.

The truth is that we are not there yet.

As someone who’s industry is in the cross-hairs of cognitive technologies, I have been exposed to more than a few examples of how this technology works.

The category knowledge that these tools will draw from to generate their insights currently resides with guys and gals like me.  As such, we (the subject matter experts and category leaders) of the procurement space hold a special and specific set of keys that unlock these technologies.  It is with that focus that I would like to proceed.

In order for these technologies to work best there are certain fundamental elements that must be right in order for the tool to generate the best insights.

Good Data

Well organised and structured data is an essential foundation for cognitive technologies.

When it comes to any form of data analytics, the old adage “garbage in, garbage out” still holds .  Unfortunately, the vast majority of organisations simply have poor data.

Before you can point any cognitive tools at your data set, the data needs to be scrubbed and normalised.  This is still done manually by a team of people.  I’m sure one day this will be 100 per cent automated and perhaps technology will find a way to avoid these errors in the first place.  The fact is that whenever we receive data Today, it is highly flawed and requires weeks of work to make it usable.

Here is a good primer on data collections.

Be sure you allow sufficient time for your data to be cleansed before you deploy your cognitive tools.

Define your Benchmarks

The greatest value that AI and cognitive will bring is being able to benchmark your organisation in ways never before possible.

In a recent article I wrote on how to use bench-marking to develop cost estimates, but cost estimating is not the extent of how you can use bench-marking with AI.

Consider the value of bench-marking your organization against a competitor’s current performance.  Cognitive tools allow you to bring in publicly available information in real time.

Imagine that you are an electronics manufacturer and your closest rival releases their financial report.  Cognitive tools can seek out these reports and extract data from them to benchmark against your performance.  You can also combine cognitive tools with web crawlers that seek out competitor’s pricing information.  Without cognitive tools, this kind of information would require weeks or months of manually collecting data.  Cognitive tools allow this kind of analysis to be done instantly.

To take advantage of AI, take time to consider all the different ways you can measure your performance and see if you can come up with a few you never thought possible before.

Market Indices

All goods and services are affected by market forces. Staying on top of market indices is important for making strategy decisions.

An effective cognitive data strategy uses data from market indices.  Market Indices will enrich your own data and allow you to forecast into the future.  Adding this level of depth to your cognitive platform will reveal the actionable insights that cognitive data promises.

The Bureau of Labor Statistics is great resource for all kinds of indices.  If you are in construction, there are a number of private organizations that publish various indices to help forecast the future.  Look at the AIA, Dodge, and AGCjust to name a few.

Add market indices to your data set to enrich your analytics and strategise with forecasting.

Category Expertise

Cognitive technologies offer beautiful data outputs rich in data and content, on their own these outputs are just eye-candy.  The interpretation of that data and content must be made by skilled experienced subject matter experts.

Eventually we may get to the point where computers can read the data and a clear strategy will be automatically spit-out for anyone to act on.  Even then, how you act on the data will require some expertise.  Until such time, you must have your cognitive data interpreted by a human with category expertise.

It’s too easy for data to be misinterpreted and for an organisation to run-off in the wrong direction.  Even the most advanced Artificial Intelligence we have Today is unable to interpret the various human factors that go into strategy making and for that reason, Subject Matter Experts (SME’s) are still required.

Be sure you know that the person who will receive and interpret your data has the skills needed to execute a sound strategy.  After all the time and energy you invest in cognitive tools, you need to be sure your direction is sound.

Closing

The future of AI and cognitive is bright.  We are heading in a great new direction where information will rule.  Today there are a few trail-blazers paving the way for us all.  Those using these new technologies Today are sure to be better prepared Tomorrow as they find new and creative ways of using data to guide their business decisions.


This article was originally published on Luis Gile’s website. Check out more of his content here. 

Sign up for next week’s webinar: Clean Up Your Act! Category Management AI-Style. 

4 Reasons Why Your Organisation Isn’t Embracing Cognitive

In the battle for capital, how does procurement ensure its cognitive projects come out on top?

At last month’s London CPO roundtable; Amit Sharma, Global Procurement Practice Leader for Cognitive Process Services (CPS) –IBM led our attendees in a discussion on how procurement leaders can ensure their cognitive projects come out on top.

There is so much potential in cognitive technology to transform the role of procurement. It will allow professionals to do dynamic forecasting, telling you when to raise acquisition and awards contracts to a particular supplier based on a triage.

“For procurement, maintaining our relevance to the organisation beyond cost savings is imperative” said Amit.  “[Procurement pros] need to embed the latest in technology as best practise into the business as it will free up our time and help us to move from transactional to strategic management.”

“The logic is unquestionable.  We know the sophistication of AI is going to come. It’s a question of when, not if.”

But when it comes to making the leap to cognitive, which can do a world of good for analytical and predictive analysis, organisations are still hesitant.

Procurement needs to make the business case for how cognitive can add long-term value and, as Amit reminded us, “If you’re not convinced, you can’t convince someone else”

Throughout our discussion, four key reasons for an organisation’s reluctance to embrace cognitive tech became apparent.

1. Remaining skepticism at the value of cognitive

As Amit explained, cognitive technology like Watson can help procurement professionals to analyse reams of data. It would, for example, allow users to plot the price at which they are being charged for something by suppliers and analyse how the index has moved in past [x] years. Five years ago this process would have been extremely time consuming but with the index data, the system can quickly tell you exactly where you’ve been overcharged.

So it all sounds great. But in reality, business leaders are often skeptical about the actual cost savings brought about by this kind of analysis.

Do you genuinely make better decisions in the long term by having so much data at your fingertips? Or can you have just as much success through effective negotiations with your suppliers?

Amit’s response to this “If you’re not doing spend compliance – you don’t know if you’re compliant. If you’re not analysing this data, you don’t know the potential cost savings.”

“I spoke to a CPO who thought their processes were good. [But it was discovered that] there was a 40 per cent unit price difference across the company in the same category, simply because the left hand doesn’t know what the right hand is doing!”

2.  Spend within organisations is fragmented

One key problem for procurement, when it comes to implementing cognitive technology, is that the CPO doesn’t always have the authority to drive transformation. Perhaps they are reporting to a CFO who doesn’t see value in cognitive tech or the spend might simply be too fragmented across the business. When it depends on lots of other people, procurement are unable to drive change effectively.

As one of our roundtable attendees pointed out “there are organisations I know who can’t justify the need to implement Ariba to their CFO- let alone cognitive technology!”

3. Trouble looking at the bigger picture

Several of our roundtable attendees cited short-termism as a key reason for their organisation’s lack of cognitive adoption. “The mistake we make is that we look at opps in a tactical way and not at the bigger picture,” said one CPO.

“For example, we know that there will be headcount reduction in the coming years and we will benefit hugely from cognitive tech, but articulating that at a hollistic level to the CFO and explaining it as a 5-year journey is the challenge”

4. Confusion about AI

Remarkably, one of the biggest challenges remaining around  the uptake of cognitive technology is a universal lack of understanding of what it actually is and the distinctions between different terms.

“You can start talking to a group about AI and within a few minutes people are talking about blockchain, as if the two are interchangeable,” said one of our attendees. “People need to have a clearer understanding of the buzzwords ; AI, blockchain cognitive etc.”

Of course, there are people who know a little and people who know a lot. And that’s a challenge in itself.

Read more here on the insightful discussions had at our London CPO roundtable. 

Are You A Data Hunter Or A Gatherer?

Are you trying to stay afloat  in a huge “data lake”?  Trust us, there are better ways to manage and manipulate your data to make an impact. Are you a data hunter or a gatherer?

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There’s a whole lot more to data than simply having it…

If you’re one of those procurement professionals who’s anxiously sitting on an ever-growing mountain of data, wondering how on earth to make sense of it all; it’s time to shift your mind-set and your approach from gatherer to hunter….

Data on its own means very little unless it’s actually actionable.

But procurement professionals are so used to a deluge of data that it often ends up discarded in someone’s top drawer, never to be seen again! Perhaps it’s not fit for purpose but one thing’s for sure – nothing useful is done with it!

Can procurement teams do a better job in ensuring they get a decent ROI on their data?

Our latest webinar with IBM, which takes place on 28th March, will teach you how to become an astute data hunter!

We’ll be discussing…

  • Why every procurement team needs a Chief Data Officer
  • Unstructured data – How do you make sense of it all?
  • How to make sure your data is fit for purpose and get an ROI on your data investments
  • The biggest mistakes Procurement teams make when it comes to data and analytics?

Webinar Speakers

 Edward D. O’Donnell, Chief Data Officer for Procurement – IBM

Edward is IBM’s Global Procurement Data Officer and charged with the mission to advance Business, Intelligence, Deep Analytics, and Cognitive functionality across the procurement portfolio.

Marco Romano, Procurement Chief Analytics Officer, Global Procurement, Transformation Technology – IBM

Marco applies more than 15 years of experience as a procurement practitioner and project manager to understand complex environments that separate the noise from real issues and determine near-term and strategic solutions in realising business value. He leads a team that has saved IBM Procurement a significant amount in third-party costs and efficiencies through analytics data solutions and innovative sourcing strategies over the past three years. His team is also developing commercial analytics and cognitive procurement offerings leveraging data and technology for IBM clients’ competitive advantage.

 Tania Seary, Founder – Procurious

A true procurement entrepreneur, Tania is the Founding Chairman of Procurious, The Faculty and The Source. Throughout her career, Tania has been wholly committed to raising the profile of the procurement profession and connecting its leaders.

After finishing her MBA at Pennsylvania State University, Tania became one of Alcoa’s first global commodity managers.

In 2016, Tania was recognised by IBM as a #NewWaytoEngage Futurist and named “Influencer of the Year” by Supply Chain Dive. She hosts regular procurement webinars, and presents at high-profile events around the world.

How do I register for the webinar?

Registering for our webinar couldn’t be easier (and, of course, it’s FREE!)

Click here to enter your details and confirm your attendance. We’ll send you a confirmation email with a link to the webinar platform and a handy reminder one hour before we go live!

I’m already a member of Procurious, do I still need to register?

Yes! If you are already a member of Procurious you must still register to access the webinar via this platform. We’ll send you a confirmation email with a link to the webinar platform and a handy reminder one hour before we go live!

When is it taking place?

The webinar will take place at 1pm BST on 28th March 2018

Help! I can’t make it to the live-stream

No problem! If you can’t make the live-stream you can catch up whenever it suits you. We’ll be making it available on Procurious soon after the event (and will be sure to send you a link) so you can listen at your leisure!

Can I ask a question?

If you’re listening live, our speakers would love to hear your questions and we’d love for you to pick their brains . Questions can be submitted throughout the live stream via the webinar platform.

If you think of a brilliant question after the event, feel free to submit your question via the Discussion Board on Procurious and we’ll do our very best to ensure it gets answered for you.

Our webinar,  Basic Instinct: Are You a Data Hunter or Gatherer takes place at 1pm BST on 28th March 2018. Register your attendance for FREE here. 

How To Avoid Transaction Automation Landmines

When it comes to implementing transaction automation, managing the trade-off between the speed of execution and the granularity of data is a challenge…

NikoNomad/Shutterstock.com

There are many factors that require careful consideration to bring about effective cognitive solutions.

It’s akin to conducting a group of musicians – it might be possible (easy even!) to attain a pleasant sound from a solo instrument… 

But, if expertly managed,  you could accomplish a symphony from the entire orchestra! 

This week, our podcast series will guide you through the five steps required to conduct a dazzling cognitive symphony. 

On Day 3 of Conducting a Cognitive Symphony Anna Madarasz, Analytics & Cognitive Lead , IBM Global Procurement discusses the importance of appropriately applied transaction automation, striking a balance between speed of execution and granularity of data and how to avoid landmines.

The importance of transaction automation

Marco Romano, Procurement Chief Analytics Officer, Global Procurement, Transformation Technology, IBM discusses  taxonomy in his white paper, “Transaction automation is a business necessity.

“We all want to spend less time doing repetitive lower-value work and use our skills to provide higher-value services to the business. However, as with many good things, badly applied transaction automation results in poor data and ultimately lost productivity and analytics effectiveness down the road.”

Transaction automation landmines

Procurement organisations are usually very well intentioned when it comes to the implementation of transaction automation but that’s not to say the process is without its challenges. We asked Anna to describe some of the landmines she’s seen procurement professionals hit.

Catalogs or other automation processes that allow the editing of item description and price can make the life of the client and the buyers easier.

As companies  see the positive effect of this they are likely to have a higher percentage of their transactions and spend going through catalogs.

The risk with this, as Anna points out, is  setting yourself unrealistic targets, “there is always a logical threshold, over which it is a risk to apply automation. Of course, you will not implement a catalog line if you  only have two purchase orders of the same nature in a year.

“With wrongly defined targets, a catalog isn’t going to decide action and then, of course, you spend more time on creating and maintaining your catalogs than creating your purchase orders.

Bulk Purchases

Anna also advises avoiding the catalog lines that allow bulk purchases.

“Many times it is really not easy to identify the purchase in a fixed line. Let’s say you are buying server configurations [or] storage configurations. Those are made up of multiple parts, so you  have hardware, software and services elements in it.

“A configuration can be made up of 50, 100 lines. If you allow your clients and your buyers to raise purchase orders simply as a one line item, this server [could cost] one million US dollars!”

“Of course, it’s a really sensitive balance because you also want to avoid the workload of raising incredibly granular purchase orders, so it is really your call at what level you would like to analyse [a given category.]”

“If this is a category which is your main area of focus, then try to go granular, try to get the data. If it’s not, then it’s your call if you are allowing these bulk purchases.”

The trade off

“There is always going to be a trade-off between speed of execution and granularity of data” says Marco

“Finding the right balance again takes us back to developing an understanding of what data we need to achieve our desired cognitive and analytics state. There is no doubt that teaming with the right technology and innovation provider, and selecting the right tools, is critical to that balance”

Striving to conduct a cognitive symphony but in need of some expert guidance? Our podcast series runs throughout this week and will have your orchestrating cognitive success in no time! Register here.

Is Your Taxonomy Flexible and Multidimensional?

For a taxonomy to be effective, and feed a cognitive engine, it needs to be multidimensional, flexible, and situation based…

There are many factors that require careful consideration to bring about effective cognitive solutions.

It’s akin to conducting a group of musicians – it might be possible (easy even!) to attain a pleasant sound from a solo instrument… 

But, if expertly managed,  you could accomplish a symphony from the entire orchestra! 

This week, our podcast series will guide you through the five steps required to conduct a dazzling cognitive symphony. 

On Day 2 of the series, Anna Madarasz, Analytics & Cognitive Lead , IBM Global Procurement discusses how procurement pros are using taxonomy today, assesses homegrown taxonomy versus industry standards and explains why an effective taxonomy needs to be flexible, multidimensional and situation based.

What is taxonomy?

Marco Romano, Procurement Chief Analytics Officer, Global Procurement, Transformation Technology, IBM defines taxonomy in his white paper, as follows “Simply put, taxonomy is a hierarchical representation of data, products and services into logical groupings through the application of an alphanumeric scheme of sorts.

“Sometimes, these are industry standards and sometimes, they are locally-devised schemes to meet individual needs. These conventions are useful for purposes of reporting spend or segregating categories into lower-level components.

“However, the world in which we operate is not hierarchical; it is more like a network of many disparate parts of an ecosystem that is constantly interacting and evolving, and that it needs to be intertwined together to drive value

“for a taxonomy to be effective, and to feed a cognitive engine, the taxonomy actually needs to be multidimensional, flexible, and situation based.”

What does this mean?

1. Flexible

“There’s a level of flexibility you have to have, and usually if you do have a homegrown taxonomy, then it is there by nature” explains Anna.

Problems can arise within organisations when there is no global standard and different regions adopt different practices. “Let’s say one of your geographies breaks down their software license spend into accounting software or project management software. Whilst another geography chooses to break down their software spend into whether that software license is delivered electronically or non-electronically.”

Of course, you can’t take much global insight from this. So it is important to enforce some level of standard taxonomy. “But, depending on the industry, depending on the geography, you have to allow a little bit of flexibility.”

2. Multidimensional

There are many dimensions of taxonomy. And, multidimensional means that you really have to define what you need that taxonomy for.  Sometimes it will be sufficient to have your homegrown taxonomy, other times it might be preferable to have an industry standard such as UNSPSC. If, for example, you want to monitor the price trend of a certain product, then you will definitely need an OEM part number.”

“Multidimensional means that you really have to define what you need that taxonomy for.”

An OEM part number, for example, clearly defines a certain product or a certain service. If you have a notebook in front of you, and you type the OEM part number into a browser, your search will return exactly the same notebook.

You might however,  want to go down to the component level and ask what characterises that notebook?

“Is it the screen size, it is the memory, and so on, and so on? If you want to look for a comparable product in your catalog then  you need ontology.”

“If your business challenge is to note which supplier is providing a certain model of notebook cheaper then it won’t be enough for you to have an eight-digit UNSPSC code defining the notebook.”

3. Situations-based

In his white paper Marco states “It is not about how you buy, but rather what you buy. I would argue that an appropriate taxonomy is about identifying how you resolve a business problem through products or services.”

“Try to use taxonomy for future transactions. Trying to predict what your prices will be, trying to evaluate whether the quotations, whether the bill of material in front of you is competitive enough. Or use it for risk evaluation. There are endless opportunities, but it really all depends on setting up the proper categories.”

“What you should keep in your mind” advises Anna “is that you have to come up with a powerful combination of these taxonomy characteristics.”

Striving to conduct a cognitive symphony but in need of some expert guidance? Our podcast series runs throughout this week and will have your orchestrating cognitive success in no time! Register here. 

Is Your Procurement Data Fit For Purpose?

How do you know when your data is fit for purpose? Start by putting the why before the what!

Robyn Mackenzie/Shutterstock.com

There are many factors that require careful consideration to bring about effective cognitive solutions.

It’s akin to conducting a group of musicians – it might be possible (easy even!) to attain a pleasant sound from a solo instrument… 

But, if expertly managed,  you could accomplish a symphony from the entire orchestra! 

This week, our podcast series will guide you through the five steps required to conduct a dazzling cognitive symphony. 

On Day 1 of the series, Marco Romano – Procurement Chief Analytics Officer, Global Procurement, Transformation Technology, IBM, talks about the development of data strategy, how to determine if a data source is fit for purpose and understanding the data that you want to see.

“To me the cognitive and analytic strategy really starts with the data strategy” explains Marco, “how we acquire, enrich, store and curate our data. Then it really becomes about what you do to that data to bring business value and actionable insights.

“I’d argue anything’s possible quite honestly, limited only by our imagination and one very important point, which is the quality and quantity of the data that’s available to us.”

The orchestra analogy

So where did the orchestra analogy come from?

“When you sit there at the start of a performance invariably you’re hearing these individual members tuning their instruments – warming up.

“It’s very melodic and you really get to hear the class of the instrument and the performer. But it’s really when the conductor walks on stage and all of those instruments are played together in harmony, that’s when it really becomes incredible.

That’s when the goosebumps come in and you hear the power of the sound.”

So how does this translate into data and insights? “One good piece of data is absolutely valuable and can really help you make better business decisions” says Marco. “But like an orchestra, a collection of this transformed data, properly orchestrated to provide these varied and powerful insights at the right time and in the right format for the intended audience really gives you that competitive advantage and operational efficiency.”

“You really need everyone playing from the same sheet of music, or the same hymn sheet!”

Putting the why before the what!

If the foundation to cognitive strategy is the acquisition of data, what kind of data should we be seeking to acquire? It’s easy to think about it in a one dimensional way, only considering one or two sources of data. But in reality data is coming from multiple sources. So where should we be looking for it?

“I think before you even answer the question of what data is it that you need, you really need to address the question of why you need it” explains Marco.

“What is the business outcome that you’re trying to drive? What is it that you want to achieve by acquiring this data? Then I think you can start to determine what data you need, and how you go about acquiring it and enriching it.

“I’ve seen an awful lot of effort go into acquiring data that never results in a business action. Not because it was bad data but it was just not fit for purpose. I think the importance here is that it is fit for purpose at the time that it’s needed and of course for the intended recipient.”

How do you know when your data is fit for purpose?

What are some of the things that you do to determine if a data source or a potential data source is fit for purpose, before you go down the road of actually trying to acquire and cleanse and build it into your models?

Marco firmly believes that you have to start with establishing what the intended outcome is that you want.

Secondly, “there is a point, which we of course have to consider, and that’s ROI. We can’t afford to throw manual resources off to fully invested activities. Some data is extremely difficult to come by, or extremely difficult to get to the level of quality that we need.

“I think you need to have a clear line of sight, of how these insights are going to allow you to change business course or alter business strategy and effect an outcome. Then you can start to also establish to what degree this data will help you achieve that?”

Ask yourself “how much impact is that data going to have, and in turn you can start to then make sensible decisions about ROI and the type of data that you need.”

Striving to conduct a cognitive symphony but in need of some expert guidance? Our podcast series starts today! Register here.

Buying Social, Expressing Yourself Online and Other Procurement Challenges…

Does it pay to buy social? Can I build greater trust online? And how do I prepare my team for AI developments? We answer some of the questions and challenges on the minds of procurement leaders…

Olga Savina/Shutterstock.com

The Procurious London CPO Roundtable was sponsored by Basware

How do you evolve your organisation from the mindset of  “we’re not doing anything bad” to actually “doing something good” ?

What happens when people who don’t know what they’re talking about start talking online, what does that mean for society’s leaders?

With the development of RPA and AI, are we all out of a job, and when?!

How should organisations go about developing existing talent to prepare them for leadership roles?

These are just some the questions we answered at last week’s  Procurious CPO London Roundtable, sponsored by BaswareWant to know the answers? Look no further…

The Buy Social Corporate Challenge

Charlie Wigglesworth, Deputy CEO – Social Enterprise UK (SEUK) gave a fascinating insight to the great work social enterprises are doing across the UK.

SEUK was established in 2002 as the national body for social enterprise. Now, with over 1200 members they strive to support social enterprises and develop the evidence base to showcase their benefits, as well as influencing policy and political agendas within UK government.

Social enterprises sit comfortably in between a charity and a private sector company. They have a clear social mission and  look to make profits to further that social mission – they are “businesses which trade for a social purpose.” 

“Businesses and governments can support social enterprise in lots of ways but the best way to do good is to buy from them,” explains Charlie.

They are much more likely to be better represented or minority led or based in the most deprived areas. They are more likely to employ people that wouldn’t have work otherwise had work or give money where people wouldn’t otherwise have had it.

Supporting these companies is good for your business because they are likely to be cheaper, more innovative and doing so gives corporations the opportunity to overlap and integrate CSR with normal business, rather than have it exist as a separate entity.

Buying social doesn’t cost more money or change the procurement process  but it has significant strategic and ongoing value for communities and your business.

Of course, as Charlie admits, it can seem hard to make changes and switch your mentality from “not doing anything bad” to “doing something good”. Charlie’s advice is to “find opportunities locally- they may seem tiny but there can be significant opportunities. Look at where you can do things directly.”

SEUK is working with a number of businesses for The Buy Social Corporate Challenge with the challenge to achieve $1 billion of procurement spend with social enterprises by 2020. Follow their progress here.   

The Conversation Century

Elizabeth Linder, Founder and CEO of The Conversational Century joined Youtube in 2007 and often thinks back to that year, a significant time for Youtube, in order to understand the social media space.

It was an exciting and life-changing time for skilled amateurs. A time that had millions of people singing in their bedrooms or racking  up millions of video views for a commentary on something they would never otherwise have been considered an expert in. Youtube ultimately offered them the opportunity to be heard.

Elizabeth is a strong believer that the internet is the best place to build trust. “The people” ( i.e. you and me) have already got this all figured out. But the reason so many people still believe the internet is destroying trust is that our leaders are still so far from getting it right! We simply don’t have leaders at a political level that have invested in a voice on social media.

Some key things to remember when trying to start conversations online:

  • Most leaders fear that they have to move at an increased pace because of today’s internet culture. You don’t. Go at your own pace but keep people informed as you do it. It’s ok to communicate to people that “the discussions are still in progress” or “we don’t have information on this yet” so long as you’re communicating something!
  • Believe in the power of primary sources because the public certainly do. Hearing directly from the source rather than a paper adds a lot of value to your communication. If you’ve ever been quoted in an article, blog or feature you’ll know the producer of that piece never quite gets to the meat of what you were trying to say because you don’t own the conversation or drive the discussion – they do!
  • Embracing in the hacker culture, i.e. making it up as you go along, is key. EU politicians, for example, only see social media as a tool for outbound communications and not for their inbound policy making. Hacker culture dictates that they need to consider the latter.

Elizabeth’s take away advice on owning the social media space? “Be yourself online and talk to people in a way that lets them in but not in a way so casual that you’re treating them like family.”

RPA and AI – Are We All Out of A Job?

Where are we at in terms of Robotic Process Automation (RPA) and Artificial Intelligence (AI) ?  Paul Clayton, Head of New Service Development, Basware outlined the current threats and challenges.

RPA essentially replicates things that aren’t easily automated; the things a human would do. Its skills lie in coding systems and inserting data. The downside to RPA is that there is no intelligence or decision making process, which means it can go very wrong!

There are four levels to AI:

  • Level 1:  This is the simplest form of AI and is quite prevalent today.  It’s reactive and rule-based with no memory or recollection and decides what to do based on a set of rules.
  • Level 2:  Limited, but not long-term, memory with decisions based on recent experience. It will react to data from the things it sees.
  • Level 3:  These are computers that learn and have memory. They  can re-formulate their view on the world so they can make decisions and remember actions. Whilst there are Level 3 computers out there, other than C3P0 (!),  it hasn’t been applied in procurement except in the areas of fraud and risk management.
  • Level 4:  This, fortunately, does not exist…yet! These are machines that are self aware and can form their own view on anything, redevelop their own software and change their behaviour entirely.

Levels 1 and 2 cover most of the repetitive tasks in procurement and finance. Not before long, 90 per cent of the people in this sphere wont be required.

So yes, as Paul admits, the jobs we have today won’t be here tomorrow and people won’t have careers in the way that we currently define “a career”. But the workforce coming in today is used to their environment changing every 30 seconds,  they already expect instantaneous change and they’re able to adapt quickly to something different.

Barclays’ leadership development process

Jonathan Harvey – Global Head of Talent & Culture, Barclays PLC, gave us a high level overview of Barclays leadership development framework and how it compares or contrasts with other leading companies.

When Jonathan joined Barclays two years ago he was tasked with assessing whether Barclays were doing enough to embed a common set of values and to measure their progress in embedding them.

He evaluated how they were developing existing talent in preparation for leadership roles and eventually established a set of criteria for potential leaders at Barclays. This criteria demands they live by Barclays’ values and inspire others to live by them and that they have leadership critical experience such as experience managing more than 1000 people, across different geographies and through different business cycles.

The most successful leaders of organisations will be those who can think the most adaptively and creatively, and that comes down to experience!

Procurious are hosting CPO roundtables on 30th May, 19th September and 14th November. If you’re a CPO and would like to attend one of our roundtables in person please contact Olga Luscombe via [email protected] to request an invitation.

Taking The Heat Out Of The Resolution Room

If you can’t take the heat get out of the resolution room! Or invite Watson! 

VladisChern/Shutterstock.com

We’ve all been there. Something’s gone terribly wrong with a major customer delivery. Emails are flying around and there are rumours from HQ that “heads are going to roll”.  Everyone concerned has been summoned to “THE meeting” in order to resolve the supply chain issue.

We know what happens next; fists slamming, red faces, an embarrassing lack of data and a lot of verbal ping, pong. Eventually, a resolution is found.

But what happens when Watson is in the resolution room? Could this take the heat out of your supply chain disputes?

 What is a Resolution Room?

A Resolution Room provides the organisation the ability to collaborate quickly to resolve supply disruptions. Users can discuss and resolve issues with other colleagues, business partners, or their suppliers. What distinguishes Resolution Rooms from all other collaboration platforms is Watson.

What does it mean to have Watson in the resolution room?

The big benefit of Watson being in the resolution room is that it recommends experts, provides insight from all data and actionable advice based on learned best practices.  Over time, it leverages Watson’s capability to develop a body of knowledge by learning how issues were best addressed in the past.  This enables greater speed and accuracy in responding to future events.

“Watson provides the opportunity to deliver business value and insights from all of these data insights – structured and unstructured, data from weather patterns, news, D&B and supplier IQ,” explains Joanne Wright, Chief Supply Chain Officer, IBM.

“It does this with speed and accuracy. No more are we saying ‘OK…let’s get the data and meet again tomorrow’ because Watson takes my team’s input and incorporates that into the next iteration as we go.”

Watson In The Resolution Room: A Case Study

IBM Watson is always a room participant, so you can draw on Watson’s expertise using natural language to ask a question, for example: @Watson what is the status of order ABC123?

Imagine the following scenario; A Late Shipment alert in the Ops Center reveals that orders of your most popular drone are in jeopardy because the shortage of the entire supply of a critical part, a lithium battery, has been delayed. You create a Resolution Room to manage the incident collectively.

Watson is in the room.

Whilst your team discusses how best to manage the problem you have the ease of asking Watson questions such as:

  • Which customer has the most sales dollars that will be late?
  • What are the financial impacts of any late orders?
  • Have we experienced this problem before? Who are the experts who have worked on these similar issues in the past?
  • Are there any alternate suppliers for part number 46001?
  • Why is there a shortage of lithium batteries?

Watson can provide answers to questions such as these based on the data available in the data model and in other Resolution Rooms. Learning over time, it becomes smarter and able to provide better insights about your supply chain.

Click here to try a Resolution Room demo. 

Got a big idea you want to push through a big company or simply want to learn more about Watson and the Resolution Room?

Sign up for next week’s procurement webinar, How IBM Built the Cognitive Supply Chain of the Future. hosted by Tania Seary and featuring IBM’s Chief Supply Chain Officer Joanne Wright.