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AI for Business with BCN
AI for Business is the essential podcast for business leaders who want to stay ahead of the artificial intelligence curve. Hosted by BCN, each episode invites guests to share stories on how they’re using AI in their field and industry, with the goal to inspire you to bring this to your business.
We break down the biggest AI news, like major model releases, industry-wide shifts, and regulatory changes, translating them into practical strategies for the C-suite and business leaders. You’ll hear from guests, sector specialists, and our own AI consultants, all focused on helping you navigate disruption, seize new opportunities, and future-proof your organisation.
Make “AI for Business” your go-to source for staying informed, inspired, and ready to lead in a rapidly changing world.
AI for Business with BCN
Gain the visibility you need to cut costs and forecast for the future
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
We share how wholesalers and distributors turn fragmented systems into real-time visibility, trusted forecasts, and measurable ROI. Cutwel’s story shows how better access and governance speed decisions, while cautionary tales highlight the cost of poor forecasting and blind spots.
• The sprawl of ERP, spreadsheets, and cloud tools creating silos
• Wholesale challenges around real-time visibility and forecasting
• Success story transforming a fish supply chain with live data
• Proving ROI through small pilots and scaling wins
• What Cutwel changed to trust data and act faster
• How to appoint a data champion and set governance
• Quick wins with Power BI and dark data insight
• Roadmap from reporting automation to cultural adoption
• KPIs to measure impact like COGS, OTIF, turnover, forecast accuracy
• Linking forecasts with supplier lead times for fewer stockouts
• Using Microsoft funding and keeping security front and centre
If you're enjoying our content, make sure you hit like and subscribe so you don't miss an episode.
For more information about BCN, visit bcn.co.uk
Thanks for listening!
Setting The Data Agenda
SPEAKER_00Welcome to the BCM Podcast, keeping you up to date with Microsoft, IT trends, AI innovation, and business technology, always built around people and driven by expertise. We share practical insights and real stories to help you get the most from your tech so you can work smarter and achieve more. This episode will give you an overview of how wholesalers and distributors can overcome data silos, improve forecasting, and drive growth by leveraging real-time data, modern BI tools, and strong data governance. We talk through real-world examples and actionable strategies for building a data-driven culture, measuring ROI, and unlocking value from existing data. Our host, Emma Portlock, leads the conversation.
SPEAKER_01Thanks ever so much for joining us. Lovely to have you with us today. The points we're going to cover are, you know, what are we seeing now from over the years, from where we've seen data, what's the picture that we have now? And then what are some of the challenges we see, you know, in the wholesale industry in particular around data today? We're then going to um introduce one of our wonderful customers, Cutwell, who we're going to talk a little bit about how they've been using data to drive decisions. We're then going to talk through, you know, how can we get ready for the next steps? You know, what does this journey look like? And then therefore, you know, what does the roadmap look like for us? So I'm Emma Portlock. Uh, I head up new business here at BCN, and I also head up the Microsoft relationship. Microsoft are one of our kind of key vendors here. And I will hand over to Andy.
SPEAKER_04Thanks, Emma. Hi, everyone. I'm Andy. I work as a data slash at BCN. My role is basically working our customers to help them get the most value from their data in whatever way that that very broad area will cover. Rob, over to you.
SPEAKER_02Hi, everyone. My name is Rob Roberts. I'm the head of business transformation at Cotwell. Uh so my background is delivering transformation programs across various industries with a focus on using data and technology really to improve performance. Um, for those of you who don't know Cutwell, uh, so we serve quite a broad client base in engineering and manufacturing.
SPEAKER_01Amazing. Thanks, Rob. And uh, last but by no means least, over to you, Mark.
SPEAKER_03My name's Mark Mitchelson. I'm a principal at Frame Clark, providing instructional CIO services to our client-based my background very much in manufacturing, engineering, distribution, um, and business services.
SPEAKER_01Excellent. Thank you. And thank you,
Why Data Silos Hurt Truth
SPEAKER_01team, for joining me today. Where are we now with data? What's kind of created the data problem? Clients, when you look sort of 20 years ago, there were emerging technologies like ERP systems, CRM, kind of basic CRM. So we started with those, and all of a sudden, you know, Microsoft had done its thing with its OS operating system, Word Excel came, so Excel then grew exponentially. So we saw that kind of 20 years ago. What's then happened as time has gone on? We've then added other data sources. So we we have the huge migration from Microsoft from kind of hosted solutions into 365, kind of that eight years ago, where we saw OneDrive SharePoint. That drives a whole load of data, more you know, the unstructured type data. We've then seen a huge cloud adoption, and we've got B2B, we've got e-commerce, you've got people accessing through mobile phones. That's created another data store. And then building on from that, we've then seen API integrations in order to kind of give predictive um analysis and the internet of things. So, you know, can I predict when my fridge is going to break so that I can repair it before it's actually broken? And then finally, you know, buzzword of the day. But actually, you know, when I started my career 25 years ago in IBM, we did AI then, but it just used to take 18 months to two years to do, even in just the last six months, the growth we've seen in AI and kind of real-time dashboards and really having that insight into your business. But again, that's produced data sources. So all of these things that we've done in the last 20 years, often for companies, have caused multiple different silos of data. And the problem we're now facing is how do you get insights across? You know, what we set up in those days was best to breed for each of those things, but how do we now get true insight across all those data sources to make sense of it, to move our business forward and to know that what we're actually saying about our business is the actual truth.
Wholesale Pain Points Explained
SPEAKER_01Moving on to kind of delve into that in a bit more, I'm going to hand over to Mark, who's going to talk us through some of the um challenges we're actually seeing, particularly in wholesale around data. Over to you, Mark.
SPEAKER_03So you're particularly here. We we started to group these by what we've been seeing in the marketplace, particularly over the last 18 months, and and some of these are a lot more recent, but trying to group these into themes. I mean, we've looked at the themes there of lack of the real-time data visibility, how we look at return on investment for addressing some of these challenges, and looking at the opportunities due to forecasting and what the impacts of them be. So I I take first the um lack of real-time data, working with a client UK arm of an international fish supply hack distribute business. The arm
The Fish Supply Visibility Story
SPEAKER_03being in this country, operating across Grimsby and London. They have two service lines. They deliver hacked fish to supermarkets, line number one, and line number two is local deliveries of fresh fish to food service businesses. So they have a common fish store, and the fish that they manage is a complex piece where it it is stored at minus 60 degrees, has to be thawed to minus 20 degrees to get into the production chain, and then obviously then is thawed further for the point of packing. So it's a complex process required. So we've got two service lines now operating almost entirely as independent businesses for all intents and purposes, with a common fish stock and no single visibility of what's going on. Two service business runs off Excel spreadsheets, emails, etc. etc. etc. Completely unstructured in the way they're approaching the supermarket business lines running from aged on-prem ERP and BI systems. So a great deal of challenge already in what's going on in each of the business lines, who's consuming stock, what stage the freeze process, the call processing needs to be at, and how we're managing that down into the service lines. Not having that full sight of what's going on leads to a huge number of challenges and issues for that business. Apart from the very obvious ones about managing stock, stock value, and how much stock is held. We get into then issues with a business that knows its demand very well, the supermarket business. It knows exactly what it needs to draw on a day-by-day basis to satisfy the supermarket demand. But the food service business is completely opposite. A sunny day tomorrow will generate a significant rise in sales, and that could be easily a 60 or 70% rise in sales on the day. Now, the inability to understand what's coming ahead, we haven't got sight of what's stock and what is available and what can be moved through the freeze process and the thought process in time to satisfy that demand. And all this is done because we can't see in real time what our holdings are across both businesses and act in a single calibrated way. We've worked with that business, we've gone live with some solutions for that and changed that dramatically. Still some way to go as we fine-tune, having gone live very recently. But that's a real success story of being able to change those platforms and address those challenges.
SPEAKER_01That's amazing. And so I guess then moving on to the second challenge that we're seeing, Mark, the difficulty improving that ROI, right? How do we actually prove the ROI on these types of things?
SPEAKER_03I think the next example I would use as a business that I've been working with in the last 12 months that um international manufacturer of fixings and fittings, and I suspect might even be a Cutwell customer, in the Midlands, HQ in Birmingham, 12 manufacturing sites globally. They've grown quickly through a number of acquisitions. Some of those laterally have been PE based, and obviously the drive verbal on ROI has been that much more acute than anywhere else. We looked at the challenge they had about managing the stock globally through acquired businesses, all on different platforms, different systems, different ways of working and different nomenclature in their product lines. And what we started to look at was designing, we did a quick study on what the underlying data structures were, the locations, etc., and focused on three of those locations that were running similar product lines, had similar sector challenges, etc. So we had some commonality that were able to look at those designs and built out a platform that was able to aggregate that information, use some of the data tools and the AI tools sitting in product, and in
Proving ROI With A Pilot
SPEAKER_03this particular case, it was a demo product to begin to create a proof of concept and a proof of value. And in doing that, we learned a lot about what the challenges were in the data inside the organization, what was happening in the market, how we could efficiently service that finance teams at one end of the business and the sales teams at the other so they could actually go for the growth that they do a lot of tuning that model as we went over over a period of time. We then built out a very effective platform for addressing their needs in lieu of trying to boil the ocean and change all the ERPs across the organization. Operational gains there, the jumping OTIF was just astonishing. It was a significant step forward to the point where they were starting to win awards in what they've managed to achieve. The PE house that was backing this was so absolutely delighted with the results that we were able to go back and seek further investments and roll out further. I think that was the message I want to get across. Having designed that and improved it on a smaller scale with a scale out plan, we were able to go back and justify with quantified ROI to gain investment achievements. And the big news from that is that the growth in that business has allowed them to make two subsequent acquisitions that have fallen into the same model. So it's a real success story just by looking at things in a slightly different way.
SPEAKER_01Excellent. Thank you. That's really good um insight. And and I guess just finally, just to kind of quickly round off then, Mark, if we're looking for missed opportunities due to poor forecasting, if you've got an example of someone you've worked with on that.
SPEAKER_03Yeah, I absolutely yeah. I was working with an international manufacturer and distribution of steel products grown through acquisition, both a number of distress assets across Europe and Australia. Again, all on varying platforms, um, no consolidated strategy, no attempt to bring those businesses together and have a common data platform, just trading as independent entities very successful in doing that. As the market started to change, some of which was caused by nation states playing politics and starting to try and manipulate markets for game change. And all of a sudden, from being a cash-generating business that was very profitable, they started to suffer and things got tight. And therefore, the work that was going on on commonality and sharing and visibility started to be canned. They got to a point where some big contracts with clients were coming from renewal, and a particular contract was worth several hundred million pounds of euros a year, was predicated on supply of steel on a just-in-time basis to a very well-known manufacturer of diggers, earth movers, and similar heavy plants, mostly in yellow. Um I'll leave it to your imagination who that might be. And that contract was just lost. Resulting in one of the steel assets closing and the loss of 1,500 jobs, which was very disappointing. But it was generated simply because the demand, the just-in-time demand, needed the visibility of stock through EDI to be able to progress that contract. And it was a a game changer, and it was as simple as that. The inability to see
Forecasting Failures And Lost Deals
SPEAKER_03stock down the supply chain prevented hundreds of millions of pounds of business in that organization.
SPEAKER_01Thank you. Really brings it um home, doesn't it? Um great, thank you ever so much for that, Mark. So moving on, um, we introduced at the beginning one of our fabulous customers, Cutwell. Rob is with us today. And Rob's going to um talk us through. We're just gonna ask him a few questions around what Cutwell have done regarding sort of data and visualizations and things. And just as a little bit of background, Cutwell is is all about precision and cutting tools. So um lovely for you to join us today, Rob. Thank you so much. Would you mind just repeating like who you are, your role, and a and an overview of the company? Would that be okay?
SPEAKER_02Yeah, yeah. So uh I'm Rob Roberts, I'm head of business transformation at Cutwell. As Emma mentioned, we're precision tool manufacturer and the precision tool supplier. I've worked in in kind of transformation across multiple industries now with a focus on data and technology to improve performance. So Cotwell serves quite a broad client base in engineering and manufacturing.
SPEAKER_01Amazing, thank you. And I guess um, for those of us that maybe don't know your sector that well, what what kind of things are we seeing happening? Are you seeing any key trends, challenges, or shifts in priorities, those types of things?
SPEAKER_02Yes, from a sector perspective, I I think it's clear to me, not just with some of our competitors, but some of our customers as well, that data and visibility are becoming critical. I think everyone's realizing that the value of the data that they hold. Everybody holds it, everybody produces it, but I think everyone's realising the value of it. But clients are expecting us and other suppliers not just to provide products, but to kind of work collaboratively with them now and bring insight and to support them in a way that goes beyond kind of a traditional customer and supplier relationship. So sharing insights, they'll have insight on us, we'll have insight on them. And I think because data is becoming more readily available to people, people are more willing to share it.
SPEAKER_01Yeah, and I guess that really then helps push towards things like efficiency, that digital optimization, managing your stock, all of those types of things, yeah.
SPEAKER_02Yeah, absolutely. Yeah.
SPEAKER_01So I guess if we're then bringing it into, you know, really what happened with you guys, like, you know, why you engaged um us, what kinds of things were you looking at? What was the challenge that you were actually struggling with at the time?
SPEAKER_02Our biggest challenge was realizing how much data we had, but not having any
Meet Cutwell And Sector Trends
SPEAKER_02kind of real access to it or to action it efficiently. As I said before, we've always had strong operational capability, but access to information wasn't always fast and it definitely wasn't consistent. Which meant that we'd we'd delay decisions or opportunities for growth. I think sometimes with having data now and insight now, delays that you didn't realise were there, you've realized how how much time you've wasted by not having this at your fingertips.
SPEAKER_01Excellent. So what did you what did you do to approach that problem?
SPEAKER_02First and most importantly, we engaged BCN.
SPEAKER_01Well answered, Rob. Well answered.
SPEAKER_02Well, I I think what BCN brought was just structure to it. We all kind of knew what what was required, but the structured approach to it and the fact that you know we need to build a reliable data foundation, that was key to it for us.
SPEAKER_01Yeah, I hear that, I hear that a lot, you know, getting those foundations right so that you're actually reporting on the right kind of data in the first place. So after we'd done that, what what changed? What what have you seen as the outcome?
SPEAKER_02Well, definitely faster access to accurate data. Accurate data being being the main thing. I think everybody trusts the data now. I think we've gone through, you know, we've produced reports and dashboards and stuff, and I think there's some, you know, some of the adoption requires a bit of work sometimes, but once everyone's in, I think everyone's everyone trusts that the data's correct and then can obviously action or take appropriate action on the back of that.
SPEAKER_01Brilliant. And I guess, you know, as other customers will be listening on this, what kind of strategic advice could you give? You know, what what should others in your sector be thinking about?
SPEAKER_02Firstly, take a real look at where your data is now. So it has to be sound before you start this. And if it's not, then that's where you start, I imagine, the journey with BCN. If it's not already sound, start there. Then know your problem statement, kind of know what you're you're trying to achieve. Stay out of solution mode. I think you've got to stay on the other side of the table sometimes. We definitely did. We had ideas on a solution, but I think sometimes
Fixing Access And Trust In Data
SPEAKER_02just knowing what we want to achieve and allowing the solutions to kind of come to us and then us to choose was key to that. And then involving the right people, so kind of a broad spectrum in the business. So we've had some salespeople, some warehouse people all the way up to the CFO involved, because you know, people have different nuggets of information across the business and they know how to use certain bits of information. You know, a CFO might not know all the intricacies of the warehouse data and and vice versa. And then really just make sure that you know how to measure what you're doing. So sometimes that means you know, doing in sections, but really understand ROI and and what you're getting from it.
SPEAKER_01Excellent. Thank you ever so much, Rob. That's been really insightful. Really appreciate you taking the time out to talk us through that. So I'm going to hand over to Andy.
SPEAKER_04Great, thanks, Emlet. So um, when it comes to looking at where we can get started with data and how we can start to make make the most of these opportunities, you you can think let's start by looking at the technology and figuring out that solutions. And I think it's um that's that's not the best place to start. It's you have to look at it from um ignore the technology, let's look at it from the people and strategy side of it first and make sure those are right. And that's how we we kind of started this area and let those uh lead what we're what we're gonna be focusing on. So from the the data ownership and leadership side of things, we first need to start off with identifying who can be the champion, who's gonna drive these initiatives within the organization. Some companies they've started to appoint chief data officers. I actually saw a stat that um Forbes estimates uh of the Fortune 1000 companies, up to 70% of those now have got a chief data officer in place, um which really just shows the the importance of having this role and and and what they can help to deliver. It doesn't have to be someone with that formal chief data officer title, though, as long as it's someone that's identified who they are the person who is responsible for this, they're going to be the person who is really waking up and their focus is going to be on driving that initiative to leverage data for growth and efficiency. In tandem with that, it it really helps drive that cultural shift within the business. So from the top down, they need to be pushing that um we're actively promoting, making decisions based on the data. So this could be simple, it's quite simple habits. So starting any regular management meetings by reviewing key data dashboards that show performance against um KPIs and metrics. It could be praising managers who are bringing insights to the wider business that are supported by data. Um it could be pushing back on people who are bringing in assertions that aren't uh backed up by evidence, backed up by data. Really, it's just got to be that from the top down it's showing that data matters to us, as ultimately, if that message is coming from the top down, the the rest of the organization is gonna follow. Hand in hand with this, we need to also make sure that data governance is considered and factored in um as as we we start on this journey. And data governance can sound a bit technical, but ultimately it's making sure that we have the rules for how the data is going to be used. So who owns what data, who is responsible for making sure that the data quality is there and the uh and the data is is correct and shown what we want it to, who is responsible for having access to what data,
Advice: Foundations, People, ROI
SPEAKER_04ultimately making sure that those um those rules of engagement are in place for how an organization is using its data. So that could be that uh a head of sales is responsible for the customer data, head of supply chain owns the inventory data, whatever that looks like. Ultimately, they're the people who are responsible for that data quality and that data usability. Um some organizations they actually form a data governance committee that are a mix of both uh the business people and the IT people. Ultimately, they're the ones that set these policies and are responsible for making sure that people across the organisation know who is responsible for what. When these are put in place and driven forward, it leads to increased data quality and consistency, which then leads to good things with whatever we're doing with our data. Um, the final point on from the data ownership and leadership side is making sure that the ultimate the leadership is there, setting that clear vision of what we're wanting to do with data. So outside of just a broad aim of making better use, it's setting a vision that is clear and it speaks to what we're trying to do. So that could be something like real-time dashboards that show all of our critical metrics as accessible to all of our managers. It can be trying to get the 12-month rolling forecast accuracy to be uh within a X percentage error, whatever it is, it's just stating that goal to let the team know this is what we're working towards, this is what we're trying to do when we say we're making better use of our data, and it allows you to measure and track that progress and eventually use that to justify further investment in new tools, new processes, um, just doing more stuff with that data that we have.
SPEAKER_01Yeah, that sounds great, Addy. And I think you know, one of the things we see across all of our customers, if you've really got that person that's owning the project, that's driving it, that is the champion, that's excited, you know, as a as a partner, it really then helps us, right, all the way through that the project.
SPEAKER_04And the key thing I want to drive there is it doesn't have to be an IT person. IT uh data can be thought of as an IT domain. It's not. It's it's it very much sits across business and IT, and and business are of the area that are benefiting from using this stuff properly.
SPEAKER_01Yeah, amazing.
Start With People And Governance
SPEAKER_01And then obviously you're then going to talk around kind of surfacing that that value in existing data as another kind of critical piece.
SPEAKER_04Yeah, it's it's where we start with making the most use of data, and it's from the strategy side. It's identifying where are the quick wins, where what can we do more of with what we've currently got. So a lot of customers there, they're sitting on a lot of data. The general perception is that maybe the data is not that clean, it's not that great, it's not that accessible. Maybe the case, I guarantee you there's going to be some um gold in there that we can quickly access, some insight we can gain that's um just helps to get started and deliver that quick return on value. As a starting point, I always recommend um starting with a short brainstorm of each business area to try and identify where we can start. So a good question to ask is what's a decisional cost that if we have better access to data, better insight from that data, we could we can improve now. That can be around unlocking working capital if we identify slow-moving products and do something to speed that up. Um, it could be analysing the inventory data to identify where's a better place to put that stock across our distribution network, uh where it could be um running some sort of promotion to try and um do some sort of clearance there and release capital that's tied up there. It's very much just trying to identify where's where's something we can quickly do now that will unlock that data. A key thing to consider as well is dark data. So what I mean by this is unstructured data that is um sitting across the organization. I did see a stat in Forbes that estimated that of all enterprise data, they think 80% of that is going to be the unstructured stuff. So this is things like um customer service emails and chat logs, call transcripts, things that don't um necessarily sit within a traditional data warehouse, a traditional ERP system, but are still a lot of insight and a lot of value in there in what it's showing. So as an example of that, it could have customers that are frequently complaining about a particular product's availability. This can can flag is the is there something we've we're not doing around stock level availability? Do we need to work with our suppliers to get this to us quicker, whatever that may be. The idea of it ultimately is just to take that unstructured data, understand what uh insight it's showing, and and try to identify where we can start to either save money, grow revenue, unlock value, whatever that may be. Um a key part of this is uh is making sure that we rather than just just telling the business, telling people this is what it what we're seeing, actually show them that. That can be just spinning up a quick BI dashboard to show we've combined a lot of different data, so say sales, inventory, delivery times. When we've got that dashboard and we take that to an exec meeting, it's showing people here's what we're seeing in our current data, here's where we think the opportunity points are, here's areas of concern. It really brings it to life and helps the execs and the top-level people see when we talk about data and when we talk about getting better data, here's what that means, here's here's bringing that to life and moving it from that abstract idea into something they can see and believe. Final point to consider as well is that with the data we've got and the insights we're unlocking, are the potentials here to monetize that data to um either unlock new revenue streams or try to drive improved margins somewhere else. So that could be if we're feeding back data to to our suppliers around and customer demand. Um, it can help them with planning how do we do this better? What do we do basically to be able to meet that rise in customer demand? Doing that could potentially give you a negotiation point to get better rates from that client. We can then look at do we potentially give our key customers a portal that lets them see their purchase history, consumption trends, all
Surface Value In Dark Data
SPEAKER_04powered by your data, to be able to then strengthen that relationship and just be able to do more from just a customer relationship perspective. Ultimately, it's it's all around treating data as an asset and uh create value, not just as a as a thing that just naturally comes from from the transactions and over time. All of these are about setting the stage to have the right people owning the data and driving that value from what you've got to be able to then identify what's the technology we can start to look at to scale these these benefits accordingly.
SPEAKER_01Amazing. Thank you. Um kind of moving on from that then, Andy, like roadmap. Where do people start? Where do we start these these projects? Because you think you don't know what you don't know, people might be somewhere along this journey. So what does that roadmap look like? What would you recommend?
SPEAKER_04So I guess the first thing I'd say is that um whilst these projects and anything to do with making better use of data, better tooling, it can sound like it's a really chunky project. It's gonna take a long time before we start to see that value. That's not always the case. There are things you can do that are quick wins whilst you um keep the eye on that longer term, medium-term strategy and whatever it is you're trying to do. So absolute starting point though, you need to um goes back to my previous point, establish that strong data ownership and strategy. So who's gonna be accountable for driving this? If that's not yourself, is it a direct report? Whoever that may be, um, identifying that key champion and then starting to look at and set measurable objectives. So commit to something like we're gonna improve forecast accuracy by 10% in the next year, or reduce working capital we've got held up in inventory by however much by the end of the of next year. The goals they they can be ambitious, but it is important to have that defined measurable goal that we can then start to push and ultimately start to drive and infuse into the company's culture as we we start to um talk about using data in meetings, backing up things that people are saying with the data behind it, and really just setting that tone from the top down. From there, starting to look at what those quick wins are. So one area that we see is usually a quick win when customers start to begin this journey is around um reporting and being able to speed that up, automate that where we can start to get that greater insight. Typical one we normally see is around moving from a if you're if you're used to doing your reports heavily in Excel, um start to use a more modern BI tool that can automate that step, give the deeper level of insight, and really just start to lay that groundwork. One reason this is usually a good starting point in the in the Microsoft world at least is that um a lot of enterprise licenses include Microsoft's BI tool, Power BI as part of there. So it could be you already have
Make Insight Visual And Actionable
SPEAKER_04access to this tooling that you're just just not using. So it's it's um avoids that uh additional outlay to get started. Whilst you're getting started with this, though, you need to make sure that uh we have a look at the data quality and the consistency. Whilst it may not be great, this probably is stuff we can still do, but we just need to make sure that whatever that first use case is we're starting with, what we're servicing to the wider businesses is going to be accurate and correct. This could be um making sure that we started to look at the master data as well. So if we have um things like a customer list, product catalogue, just make sure we have a look at that and try to get it as accurate, as up to date as we can so that we're not servicing the the wrong insights, the wrong data at that early stage. Key part from there is making sure that as we roll these projects out, we're empowering and educating the end users and the wider team. This can be formal training and in how to use the tools, but it can also be making sure that you have your um your enthusiasts and your evangelists on the ground who are helping the wider team to do this stuff, building that community, building Understanding and the insight and the value of what this can bring across your business. Some companies hold uh internal hack funds, things like that to try and empower their end users to try and see the best insights they can get from the data, spark that interest. It's it's ultimately just driving that and um that empowerment across the business and making sure that it becomes part of the daily DNA of what the teams are doing. When we're doing this as well, it's important to make sure that we're we're tracking the value and the the impact of whatever it is we're doing and where we've got those wins shouting about it and broadcasting it to the wider business. It could be that time saved in creating reports, that's a good one. But it's it's when we're then looking at um if we've managed to reduce the capital tied up in inventory, we shout about that and just just really making sure that anything we're doing here, if we've got an ROI that we're we're driving and we're improving, we've got to make sure that that's known about as all as at the end of the day. If we're doing this stuff, it's got to be for a reason and it's got to drive that value. One area that is worth considering as well is is is using external help when needed. So fully appreciate that a lot of teams there they're being kept incredibly busy just doing that day-to-day and having the time to dedicate to looking at ways of doing things differently, doing things better is it can be a challenge. So working with Microsoft partners to do that is is always gonna help. It's gonna speed things up. A lot of partners there, BCN uh included, we have accelerators and things we can do to get you started in this quicker, as well as accessing funding from Microsoft to offset some of those costs of
Roadmap: Quick Wins To Scale
SPEAKER_04getting started. Ultimately, though, it's we we've got to make sure that whatever we're doing, um it's understanding that it's it's an iterative and innovative process. So data and technology moves quickly, uh, whatever we're building, we've got to keep coming back and making sure that it's still delivering that value, it's still delivering what the business needs it to effectively. Again, just to reiterate it, um got to be the champions of your own success here. So where we have the wins, we have the success. We should be shouting about it, we should be celebrating it and making sure that the wider business knows that these initiatives we're doing, here's the value it's bringing, and here's why it's making your life and your jobs easier.
SPEAKER_01Excellent. Thank you, Andy. And I think, you know, the key kind of learning from me when I've been involved in these areas is that it isn't just done, it's not a project that you deliver, it's something that you're constantly refining, as you say, you know, a process might change, or you might bring in a new company or new people, or the tech might change. So these things are constantly refined and and updated, and I think an underpinning everything that's being done is you talked about data governance um earlier on quite a lot, but it's also obviously making sure everything's wrapped in security and making sure that the data is completely secure. We've all seen the the news in recent months, so you know security obviously goes hand in hand. Right, so just kind of final then, you know, how how do we measure success, Andy? What are the things we're going to look at to go, right? We've we've identified we've got a data problem, we want to bring all our data sources together, we want to do some quick wins, we want to shout about them, we've got a champion, we know our vision, and we've monetized it. How do we actually measure that that's been successful?
SPEAKER_04Um, so some of the core metrics that um I believe a data project should be helping to drive, helping to improve. Um, so cost of goods sold is the for me the most obvious one, as this is obviously it directly affects the gross profit of everything that wholesalers are doing. By using data to drive those procurement decisions, manage suppliers, identify and reduce wastage, each one of those is going to shave a few points off the cost of goods sold as a percentage of the sales. So whilst each one of those is just going to be an incremental gain, it's not going to be a huge change. All of these over time, though, um they start to add up. It's going to be significant and really help to drive that profit and that improvement across the business. Looking at things like inventory turnover, um, it's all about how you can efficiently manage that inventory. So making sure that the safety stock levels are at the right level, you're not stocking out, your your products are in the right place at the right time. All of it is about driving that better demand forecasting and just-in-time practices to make sure that you're able to get this as lean as you can and you're you're maximizing what you're selling and and keeping inventory held and that capital is tied up in that stock to a to a minimum. Flip side of that, this of course is managing the stock outright. So making sure that um you're not stocking out too soon, not losing that revenue and in lost orders and customer dissatisfaction. So being able to improve that forecasting again. So knowing the inventory levels and the demand in real time across all your product lines, this is the sort of thing where when you've got your data all in one place, you've got the analytical capability built on top of that. You're really able to look at that with a much more granular level and start to you can use AI to have that at a SKU level across your product line. These sort of things that you can really drive the revenue that you've got here and drive the crack results. Um next one, uh again, which I've alluded to, is around forecast accuracy. So being able to use the uh understand the data and and being able to use that to drive the forecast to get a much more accurate level, um, spending less time um creating those forecasts as
Metrics That Prove Success
SPEAKER_04well, really just making sure that they are driving what the decisions are you make off the back of those forecasts at a much uh much greater level. Last couple of ones, so reporting efficiency, um, looking at the internal process for how long you're spending and the effort involved with creating these reports. Emma mentioned earlier around uh using Excel, it's heavily manual, but it can take a lot of time each period, each month to create those reports. If you're able to automate this and reduce the time it takes to do that, you can free up your team's time to add value elsewhere. So rather than doing the same manual things each period, they're adding that value and being able to drive what they do with those decisions, spending less time creating the reports, more time actually doing stuff with them. And the final one to focus on is the uh on-time and full delivery. So making sure that um we're using the data to help make sure that the right products are in the right place at the right time and ultimately you're spending less time rectifying those uh those issues that that can occur leads to higher customer satisfaction, reduced shipping costs and all the rest of it. All of these kind of things are uh what you can improve and what you can help drive once you've got your data in uh in the right place. You you you understand what that data's showing and you're able to spend more time then focusing on the driving those further insights, driving those analytics and understandings from it.
SPEAKER_01Okay, amazing. Thank thanks ever so much, Andy. So um we've had a question in um how easy fast is it to move from Excel to a to a BI tool? And you know that the concepts are really similar, it's a very smooth transition, but as we have highlighted, you know, doing that kind of proof of concept pilot and maybe some training interlinked with that is always critical. Is there anything you'd like to add, Rob, from a kind of customer experience of having done that?
SPEAKER_02Just just far, far easier than you'd imagine. I think uh Microsoft aren't aren't daft and and it's it's very much a continuation of, you know, if you've got Excel and you've got Excel reporting, Power BI is very much a continuation of that and it fits quite seamlessly into that. And as Amber said, once you understand what it's capable of, I think your requirements and as a business, what you're asking of your data just increases. Like we have a a saying in here now, but it most people that didn't know it before they now come to us and say, Wouldn't it be good if, wouldn't it be good if? And most of the time you can do it, you know? So it it's really changed how we look at things and what we're capable of.
SPEAKER_03Um I was working with a client that had actually quite good structure in their data, so they were one step on, but they weren't able to visualize and get that information, and they were using a lot better on reporting. It took us longer to acquire the Power BI license than to drop the reporting extension into Microsoft PC and expose everything that was happening on the manufacturing floor of that particular business. It was literally instantaneous. And the moment the license was realized, the ops manager had information on the dashboard that they were using uh and able to manage the business effectively and instantaneously, and it was that quick that they were at a slightly different place because the data was in good order.
SPEAKER_01Amazing. Thanks for that insight. We've had a couple more questions come through. So, guys, is there a way to link our forecasting with supplier lead times to avoid stock out? I'm gonna put you on the spot, Andy, for that one. Can you are you able to help answer that?
SPEAKER_04So that's absolutely something that is possible. So as long as we've got the um data that shows what the supplier lead times, that can either be data to provided by the suppliers or we look at the historical data of um over the past period, whatever that may be. Um they've said it'll take X time to get here. It actually took Y. We started to look at that and and figure out. So, based on what we've seen before and what and what we've seen in the past, um, here's how we expect the lead time to be and how that's going to then affect forecasting and the rest of it. As long as we have access to that data, we can bring it into a dashboard and understand what it is that's that's shown in there as a start to be a bit more predictive and forward-looking with um with what we're doing there.
SPEAKER_01And that's the kind of thing, correct me if I'm wrong, that we could use funding for. So that's the type of thing Microsoft
Moving From Excel To Power BI
SPEAKER_01would fund if you're looking to bring a particular data source in and then do something clever with it. It's that type of thing we can unlock funding from Microsoft. Yeah.
SPEAKER_04That's right, yeah.
SPEAKER_01Huge thanks to my panel, to Andy, Rob, and Mark. Much appreciated. If you do have any further questions, you know, please do get in touch and good luck on your data journey. Many thanks, everyone. Have a good day.
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