2X eCommerce Podcast

Adii, welcome to the 2X eCommerce podcast. I've been looking forward to this convo.
Thank you so much for having me, Kunle.
Where are you dialing in from?
All the way down the south and sunny Cape Town, South Africa.
I will love to go there, my Mrs has, and she's been telling me to do it so I need to.
She came and she didn't pack you in her suitcase? I don’t understand this.
Not at all. It was many moons ago. It was a work thing. They did a lot of touring, sighting, and all that stuff, and she was like, “Kunle, you've got to go.” She did Brazil and I did Brazil eventually. Cape Town is still on the bucket list.
Do it. I'm a part-time tech founder over here and a part-time Cape Town enthusiast. I can highly recommend a visit.
Sounds good. You've got quite an illustrious career, which dates back to WooCommerce. Before we even get back to that, who is Adii? Give us a brief life autobiography of Adii to where you are now. A quick one, please.
I grew up in a vanilla-average environment, middle class, and went to a decent high school. The key part there was my dad was always an entrepreneur. Since I can remember, my dad had his own businesses, specifically computer hardware/accounting, that's what he specialized in. I can remember, in high school, I picked up a Richard Branson book for whatever reason and it inspired me and I got this idea in my head, “This is what I needed to do forever.”
By the time I got to university, I was already tinkering with little projects on the side and doing multiple things and doing everything to not study the course that I was doing. I majored in accounting and the plan was to become a chartered accountant. Looking back, I still have the knowledge, I never practiced, and I never had to intern. Post Varsity, I spent six weeks working for corporate and then started working on Woo full-time back then. Up until WooCommerce, that's the congested version of who I am and how I got to where I am today.
At WooCommerce, were you part of the founding team? What happened at WooCommerce?
The previous team with WooCommerce was with Themes. What happened was, during Varsity, I wanted a blog so I got stuck in WordPress, it was an obvious option at the time, they were beginning popular, and it was open source so I could teach myself. I was an okay coder. I could code a little bit of HTML and a little bit of CSS. I taught myself PHP at the time.
The first product became Woo Themes and then became WooCommerce, which I built in my final year at Varsity. I built the first product, that's how I met Magnus and Mark, who eventually became my co-founders in Woo Themes and Woo Commerce. If I remember correctly, the first product was in November 2007, Woo Commerce, we launched in late 2010 or maybe 2011.
How long were you there before your transition? A few more stints that led up to Cogsy, which is what we want to talk about.
I left Woo and stepped down as CEO at the end of 2013. In the following year, I started a new company. I got to a point where it was such a fascinating ride building WooCommerce and I wanted a new challenge. The biggest challenge that I wanted was, “Can I take all these lessons and experiences that I'd learned with Woo and reapply it and do it again?” That's like a little birdy in your head that says, “You got lucky.” Not every business is as lucky or as easy as this.
Not that everything about Woo was easy but it did sometimes feel like we got lucky. The right place and the right time. I started a new company called Receiptful, which eventually became Converge where we built email marketing automation for eCommerce brands. I sold out of that in August 2019. I spent some time with Campaign Monitor in 2020, in the COVID year effectively, and then to the backend of that, I got stuck into Cogsy. I mostly tell people that I'm a bit of a one-trick pony in that sense in the way that I've built a software for eCommerce brands for over sixteen years.
Specialization does yield results. Well done for sticking on this track. Speaking of Cogsy, why did you want to solve inventory management? Did you see any blatant problems? Have you spoken to a lot of operators to know that this was like an itch that they needed to scratch?
The honest answer is that I probably did everything that I would advise first-time founders not to do. Before starting to build the first version initially, I didn't speak to a single customer, for example. First-time founders don't do that, that's not the way to go. The real impetus for this was an intersection of two things. I mentioned I studied accounting. In my own businesses, I stay close to the bookkeeping function at least.
I work with auditors. I effectively do everything except the tax advisory stuff, which I don't get involved in. Understanding financial statements or understanding accounting in general, all those things have been superpowers for my business. A couple of years ago, my wife ran a local eCommerce business, which she sold as well. Through that time, I was her tech and financial co-pilot in the business. I didn't actively work in the business but I was always there.
I can always see smaller teams that didn't have specialized roles and titles for everyone. Everyone is pretty much a generalist-ish on the team. I could see all these backend tools they were using. It was sophisticated and it was a hard lift for them to get your full power out of this. When it came to stuff like inventory management, I always felt that I could build something better and easier. That's where the impetus for Cogsy comes from.
If I take a step back and use the benefit of being in this greater industry for over fifteen-odd years, eCommerce has essentially had three phases of development. The first phase, which is part of that phase of which WooCommerce was part of, was all around, “Can we give businesses or online sellers the infrastructure, the payment processing, the order management, and all of that fundamental stuff that you need to sell online and make it more accessible for everyone across the world?” That was the first wave or first phase.
The second wave was all around the tools needed to find distribution, growth, and sales for those brands. What do you need to layer on top of that? You can the biggest companies today are email solutions like MailChimp, Klaviyo, etc, and Yotpo from a social proof standpoint. All of those companies came and that's the second phase. What happened with software development is newer technology was available. The interfaces, the user experience, and the capabilities, all these things are sexy.
That's not the only reason why you should or shouldn't use software but those solutions and that space saw a lot of investment. The bucket that didn't get investment was all these unsexy backend tools because nobody wanted to geek out about those things and build those things. If you look at most ERPs or your IMS, Information Management Systems, they look a little clunky, they're not fun to use, and they've lacked investment.
Even though they're highly powerful and functional, it's not the same interface as what you would get on Figma, for example. It's just not had that investment. I wanted to think through, “If I were to build something from scratch with new technology and with current knowledge and understanding of how brands currently sell online, i.e. not just through a single Shopify instance, multichannel, multiple energy locations, etc., how would I go about building an inventory management tool today?
Interestingly, you drew parallels with the user experience you get with modern tools such as Figma and tried to implement that or rewrite that story in the inventory management space, which tends to be clunky or SAP-like. They tend to be quite serious. Who's the intended audience for Cogsy? Is it specialists or generalists who are founders trying to figure stuff out? They want to sort out their excess inventory issues, they want to avoid stocking out and all of that stuff, and they need an easy-to-use interface to get stuff done. Does it also include the dedicated inventory management specialist or eCommerce manager who handles inventory?
It's both of those. Let me take a step back and I'll answer it in a better way. Let's go back to the Figma example. A key reason why Figma built the multi-billion dollar business that they've built where they had a massive incumbent in Adobe Photoshop is that it empowered collaboration. That's the key part. There are bits about Cogsy that does this. Cogsy is not on the same level as Figma. I want to make that clear. There were some fundamental parallels in terms of how I think about how this should work.
Firstly, when I think about the operational part of any retail brand, it has to be cross-functional. In my mind, it makes no sense if the demand or the growth team sits on one side of the office and the operational part of the business sits on the other part of the office and they never speak to each other. Figuring out how to combine the knowledge, skills, and processes for both those carry two functions. I know that splits off to your point and it specializes in different roles. That's a key part of what I think should be true here.
To directly answer your question, our direct buyer persona is generally 1 of 2. In smaller teams, it's the co-owner or co-founder of the business that leans towards the operational side that takes care of that. In that configuration, we often see one leads operationally and one leans more creative and demand-focused. We then sell to the operational persona there. Otherwise, it is the head or director of operation. It is more of a generalist role.
My vision for the tool ultimately is that the tool can automate more of the process and you probably need less specialist skills up until a certain point. When I say a certain point, our biggest customer does north of $100 million a year. The point is you can probably avoid having to build a team of only specialists and probably build more generalists depending on the nature of your business and that's what we want to achieve with Cogsy, nearer to the generalist tool.
If anyone has followed me on LinkedIn or Twitter, I often speak about spreadsheets on steroids, for example. I've spoken to many demand planners and they've got insane knowledge and experience. I don't believe that the way to go for most brands is trying to build a spreadsheet or an interface that works like a spreadsheet where you're planning to the nth degree. Most brands can be better run operationally, do better planning, and do better inventory management by avoiding the complexity involved in building especially on steroids or a planning function to the nth degree.
That's a good point. I like your mention of the cross-functional importance of tools. Moving on to inventory management. When I log in as a marketer to my Shopify, Facebook, or Meta ads accounts, I look at key metrics such as conversion rates, traffic, average order value, and all of that good stuff from a marketing standpoint, from an operational standpoint, what are the north star metrics every reader should be paying attention to?
The things that we'll always call out is understanding your growth or at least your contribution margin and ideally understanding that on a per SKU and a per channel basis is critically important. Whatever the contribution margin is on an SKU, if you sell on Shopify versus Amazon, those things will be different. What you can spend on advertising will ultimately be influenced. That's the first part that I want to understand.
The second part that, in my mind, is a north star here is what I call return on working capital, deployed or employed. The two biggest risks with inventory are that you are stocking out or you're completely overstocked. If you're stocking out, you are directly losing revenue because you don't have stock to sell. If you are overstocked, you've got cash tied up in stock that has an opportunity cost, which has a negative influence somewhere else in the business. It's slightly harder to quantify what that impact is or where that impact is but there's an opportunity cost there because you don't have the cash. Assuming your cash constraints, which most of the best brands that I have worked with or have encountered are.
The metric that I would focus on there is the return on that working capital or the cash that you have in inventory at any given stage. You're essentially keeping two things in relation to each other, which is, “I've got X amount of cash tied up in capital at all times and this is how that is linked to my revenue or even better, my gross profit.” If that ratio is higher or that return is higher, it suggests that I am finding that optimal range where I know that I'm not stocking out but I'm also not overstocked significantly.
In an ideal world, for example, if you took away all lead times, we would all move to a just-in-time on-demand or print-on-demand. It's not print-on-demand because most products don’t work that way obviously. The closer you can get to just in time, the better because that's where you need the least amount of cash tied up into inventory. That's the metric that I would use to try and ascertain that part thereof.
One additional one that I'll throw out there and it feels like an artifact but this part of the first version we built with Cogsy was all about how to think about prioritizing the cash. If you've only got cash constraints, limited cash available, and you had to prioritize which SKUs to run out of, Cogsy calculates a single metric, which is LTV per product. The way we calculate that is for a first-time customer, if they buy product X first, what is their lifetime value? We then calculate that back.
The theory there is if your highest LTV products are not in stock, you're not just losing out on that single sale, that $50 sale. If those products are generally also $300 LTV over the span of 2 or 3 years, you are possibly losing out a bigger part of that. First-time customers don't come back because you didn't have the product that they were going to purchase and they never become repeat customers. All of those things, when you find those trends in your data, there are some interesting insights to be had there where you can then restructure your operations or reprioritize your decisions in terms of how you are buying and managing your inventory.
I like that point on LTV per product. Even your first point with regard to the gross contribution per product per SKU seems to be SKU-focused. What I didn't get was the return on working capital deployed or the return on inventory. What metric is that particularly?
In my mind, that's the all-in compassing metric to find the optimal range of how much money you should have and energy at any given stage. Let me explain it in a different way. The way to influence that is you wouldn't run out of stock, that's the one part, you're not overstocking. You might be going to your existing vendors to negotiate lower cogs that would influence kind of that number.
You might sell different SKUs on different channels or do some price optimization per SKU per channel, for example. All of those things would influence how you calculate the metric. The metric is calculated revenue over average working capital deployed. Working capital, I use it as a term but I only mean the cash deployed into inventory. All of those different levers you have available to get that return or that ratio as optimal as possible.
My next question is how would you define an operationally efficient D2C commerce brand?
Part of that would be finding the optimal range of where to invest in inventory or how much to invest in inventory at least. The other things are, what are the systems and processes that you need to have in place internally that ultimately mean that your customers can buy your products whenever and where they want? The key part of that is having the inventory and the product available, that's the first part you need to clear.
From there, the operations extend closely to, “How do I fulfill this?” Whether you work with a third-party partner there, a 3PL, or otherwise to fulfill that or you have an internal team, how does that extend out to the post-purchase experience? If there are issues, how do I communicate those issues? How do I handle those issues? How do I handle returns?
All of those things are ultimately what influences your customer's general impression or happiness or experience of you, which ultimately becomes that flywheel. If they are happy, then they come back for a second purchase. If they are happy they tell others about you. If they are happy, they share something on social media. All of those, your key components for operations, in my mind, are chained or sequenced to some extent but they should all work off of the same data set.
I'll give you a simple example there. At Cogsy, we often work with brands that do have stockouts and we build a function called customer-centric backorders. Instead of having a generic pre-order button and you have to throw your credit card into a void and you don't know when you're going to ship this, because we have all of your operational data, inventory coming in, and as well as a forecast, we can tell a customer, “Kunle, this product is out of stock today. This will next ship onto June.” You know exactly when that is going to happen.
For a customer, that's a great experience. It converts much higher compared to generic pre-orders or some new waiting list, for example. We've got data on that. When I think about operational excellence, what is important is that information shouldn't just be available and we don't make that available just to our operations team. That is also available to the customer experience team.
A week later, you maybe didn't get the automated email and you ping the brand and say, “I ordered this product. I don’t know where it is or what the ETA is.” Whoever is on the other side of that conversation from a CX team can say, “Kunle, hold on. I will check quickly.” They can see, “This is what the data is for the stock.” They can reconfirm it for you. They can double-check your exact order. That's why I think about operational efficiency there. The systems need to be in place. Humans need to understand how to use those systems. Ultimately, you need to give everyone involved the right information so that they can have all these different interactions, whether with customers, whether with vendors, etc.
Over COVID, the issue is just not sufficient stock. The real big challenge is with regard to the supply chain and getting products into warehouses to sell to customers. Most warehouses seem to have an overstock problem. First, could you confirm if this is what you are seeing at Cogsy? Second is what tips do you have for people facing this success inventory problem at this point in time?
You're writing your observation there. Due to the initial constraints with regard to getting stock into a warehouse, many brands over-ordered and over-committed. For a period, they had excess stock in their warehouses and they were sitting on it. That's somewhat normalized now. Most of the brands we've worked with are back to a steadier cadence when they're placing purchase orders and how much stock they're holding. It's mostly normalized.
Broadly speaking, if you are overstocked, the way I would think about it is I would do some prioritization. Not all SKUs are created equally. I would try and sell off the lowest priority SKUs there. I would use an interesting metric like LTD per product. Another interesting thing that we often work with our customers on is to think about bundling in a smart way. There are two ways in which I like to bundle in terms of over-stockers. You take a slower-moving SKU and you attach that to a fast-moving SKU. You use the velocity of these best sellers and you tag that along.
The other way to do that is to think about margins. Take a fast-moving high-margin SKU and then you bundle that with a lower-margin skew so you don't screw up all of your economics. Most brands should discount cautiously at least. Consumers mostly either have discount fatigue or promotional fatigue or they wait. They know, “This brand is going to discount regularly. I need to wait for that discount.”
I'm not against it and I'm by no means an expert there but I'm conscious of that, which is also why I like the bundling part because at least you get AOV up and you probably get first-order profitability, which is what most brands are seeking to achieve these days. That's how I would think about overstock or excess stock. Prioritize firstly. If you are overstocked on your best-selling SKUs, you have to wait to ride it out and then you need to weigh that against a discount and the secondary effects of the discount. If you can prioritize that for the lower priorities, think about bundling, and getting rid of it and getting the cash back is what I would think.
Bundling works particularly with low-velocity SKUs and bundling them up with high-velocity SKUs. It's a good point. Where are you guys with regard to demand forecasting? No one could predict COVID. When you take these black swan events, there is predictability with demand forecasting, particularly if it's linked with marketing activity. How well does Cogsy connect with predictability on the effectiveness of your ad campaigns and seasonality and all of those other factors toward seeing trends and determining what to put in stock in order to meet customers' expectations and not run out of stock?
At the core of what we do, one of the hardest challenges we had to solve was to first build the data layer to allow us to ingest order and SKU data from anywhere that you have that data. The simplest example would be selling directly on Shopify. You've got a separate Shopify instance for your wholesale stuff and then you also sell on Amazon. We will essentially take all of that order data and we feed that into our demand forecasting functionality, which then gives you what we call a baseline programmatic forecast.
The reason I say that is any forecast, it doesn't matter if they throw hype words AI and ML out there, it is still based on your data, and it's only a partial predictor of the future. The way we think about it is a baseline programmatic forecast. Baseline means that you, as the human with intimate knowledge about how the business works, should probably add some of your intuition and assumptions on top of that. The way we've built that into it is you can either do what we call growth planning, which is on a revenue basis and shape that out that would influence the programmatic forecast.
If you are doing your ad hoc once-off marketing things or marketing changes that weren't true in the previous 12 to 18 months. The baseline programmatic forecast is good at picking up seasonality and good at picking up patterns. For example, you are suddenly launching a whole new nationwide TV campaign that you've never run before. You should probably input that into the system as a leading indicator of what demand is going to be. Those things are there.
The key thing that I can share is that I've been in software for long enough to not overhype things like artificial intelligence and machine learning, which are often used in this realm. The goal with Cogsy is not to try and increase your forecasting accuracy by 2%, 3%, or 4%. What I instead want to do is I want to make you 10% or 10 times, whatever the case is, more agile, more flexible, and more proactive. The system can only guide you.
The system can't predict the future perfectly. The system, because it's always on, can tell you, “Kunle, that sales spike there that's brewing, today, it looks tiny and it doesn't look like you're going to run out of stock.” When extrapolated, that's where a system can be great in saying, “This year, you thought that purchase order that was going to come in mid-July is going to be able to cover if you have enough stock for you to cover all of this. The trends have now changed and you should probably phone that vendor and figure out how you can get that into the warehouse two weeks sooner to avoid a stockout.” That's where the value is more than trying to get a perfect forecast. I don't think a perfect forecast exists.
You're absolutely right. That's agility, the real-time updates, and information you are getting and feeding the system particularly. For instance, if you're doing a Shark Tank or Dragon’s Den, there are going to be overwhelming demands. Can you weigh the effects? Are they different ways in terms of effects and potential predictabilities, which you feed Cogsy? Does Cogsy figure that out?
We figure out all of that once it becomes real data. The algorithm takes care of all of that. We look at multiple Metadata points for every order, whether acquisition channel, etc. By no means, I'm not a data scientist. The way any programmatic forecast works is it goes and finds the correlation or some pattern that it can extrapolate. That's why once it becomes real data, the algorithm discerns and spot trends or patterns that are not as visible to the human eye and then extrapolates or calculates outwards from there.
Speaking for myself or for our company, we run an Amazon-first business. We're now transitioning to a D2C model. It's a slow transition but it's happening. We have our inventory management system for Amazon. They're skewed toward Amazon. It's like eDesk for instance. eDesk’s purpose is built for Amazon and then all the other platforms in which it serves are second. There are second thoughts for developers. With regards to our eCommerce enablement tools, which we'll be using on Shopify, I'm speaking to the founder of Cogsy, would you suggest that we get Cogsy for our Shopify so it works with our Shopify while being cognizant of what we are doing on other channels like Amazon and eventually retail?
The key thing there for me is that any system that does data analysis is more valuable if it has all the data. I don't think it's safe to say, “I don't have 5% of the data.” That only means my decision-making is going to be 5% off. That 5% blind spot that you have could be material. How that payment plays out here and an outcome that Cogsy strives to help operators achieve there is I would fully advocate that you understand what your demand is on both those channels directly on Shopify and Amazon. The system can calculate and consolidate all of that numbers in the forecast and help you figure out, like, “What is the optimal purchase order that I need to place?” No business operates with the goal of placing separate purchase orders for Shopify and Amazon.
Separate channels.
Especially when you consider minimum order quantities or some volume discount or some economy of scale that are included in bigger purchase orders. That's what I would advocate for. Without making this a pitch about Cogsy but we doubled down on that setup, multichannel and multi-location, and we fully operationalized that. It's not just about the demand forecast but we now have the ability to know. If you have a simple setup and you only have a single warehouse for your direct sales and need to send stock to Amazon for FBA, for example, we will help you calculate that purchase order to serve both locations.
If it makes more economic sense, you can even split the shipments. From there, on the purchase order, ask your vendor to send part of the PO to one location directly to Amazon. All of those things are possible and we’ll help you track that all the way to your 3PL and Amazon as well. That's the thinking there. I'm a big believer in consolidating the data because the insights are better and as well as the workflows because the execution of those workflows is easier and more efficient as well. The last thing I'll say about this is you can have the best software solutions in place. If the humans that are supposed to use it don't use it, the software is worthless.
The reason I'm asking is I like the user interface of Cogsy. We ran a virtual conference called Commerce Accel. It was a Q4-focused virtual conference. Jason Wong spoke to inventory management. He normally speaks about markets and influencer marketing and all the good stuff he's doing on his brand. That exposed me to Cogsy.
The one thing I noticed there and the reason why I wanted to catch up with you given the fact that you’re the founder is how easy it is to read in terms of stock levels, color coding, user interface, and the way how modular the interface is. It is certainly something that I will be trying. I'll be integrating it. I see that you have Amazon integration and you also have ShipBob integration. I'm going to even speak to third-party 3PLs fairly soon.
Given that you have Amazon, I'm going to try and connect it to our Amazon, connect it to our Shopify, and see the output it spits out, particularly from a strategic and operational standpoint. Jason Wong also spoke about inventory audits and the importance of creating cadence on that. I resonate with that, using an easy-to-use tool to get those audits out and to make decisions. We have inventory audit meetings every week in our company, every Wednesday, to see what needs to be ordered, what doesn't, and all that stuff. It would be interesting to see. I'll let you guys know, the audience, how I get along with Cogsy.
For sure, Jason has been one of the early customers and has been a long-time user of Cogsy. You asked me about our ideal user. Without alienating all of the operators that I so love dearly out there, there is a future here. For many brands, the operational part is, “How do I know when and how much inventory to order for my vendors?” It should probably be done by brand managers. Brand managers greatly influence the demand for your inventory. That's where they're operating and hustling.
The system can do a lot of the operational bits. I don't mean to suggest that you can remove full operational teams. Some products are pretty complex and there are roles there. I suspect that, at least in some teams or some businesses, the shift that might happen is the brand manager or the person in charge of growth has a tool to elevate their operational or supply side skills.
It’s interesting that you mentioned that. I don't know if you recall the last iPhone, maybe the last two iPhones, I'm not quite sure, I've lost count, they led the ad campaign for Q4. They normally release it in September. From September through to Jan the next year, they led the campaign with the new color purple iPhone 13 Promax or 14 Promax. That particular unit, that particular color, kept selling up. You couldn't get your hands on that one because it was front and center. It was a new color. It caught people's attention. People wanted to find out more. Guess what? When you are about to order direct from Apple, what's the color you want to naturally adapt to?
If that integrates pretty well with your inventory management and operations, then it will work. You maximize your sales. People don't get frustrated with getting out of stock. Although there is an appeal for wanting to buy something that you can't get your hands on like Prime. I don’t know whether you've heard about this Prime drink by Logan Paul and KSI. My son got his first bottle and was savoring the moment. I digress. There's also an appeal of scarcity. You could all just adjust that. It's interesting you mentioned the front end and the back end and trying to marry what's happening in the front lines with availability and ammunition on the backend.
No one reading should take this as a hot take from this guy that knows a little bit about eCommerce. I'm referring to myself here. This is what's happening already. If I look at these smaller teams and how they scale up on the operational, it's all growth-first. The mentality is, “How do I find growth? How do I find distribution? How do I get creative in terms of my customer acquisition?” Everything else follows. With the right tools, you can probably get further along that way without having to build a whole operational team of individual specialists.
You can have someone fully leading operations but you can probably have a slightly smaller operational team and they can be generalists. There's stuff that you don't have to do. For example, knowing that this batch of inventory has left the vendor and it's going to ShipBob. A system can let you know, “Your shipment has now arrived. ShipBob has received it.” Inventory levels are updated everywhere. Cogsy gets that number and it tells you, “You're good. Your next out-of-stock date for the SKU is three months down the line.” All of that needs minimal human involvement, which means that the biggest influencer that operational tools don't yet replace is how you drive more demand for your product.
What should take on 3PLs? Is there a point of maturity where you need to grow up, screw 3PLs, and start self-fulfilling in your opinion?
I'm no expert. With my fundamental perspective here, the question should be, “Should I fulfill myself or not?” The second question in my mind is, “Should this be the core competency for my business or not?” I'll give you an analogy in terms of how I would think through that. There's been a lot in the eCommerce space around going headless if you're using Shopify or another platform. I've always argued that to do so, if you're going to build technical core competencies in your business, otherwise, it never makes sense.
I would argue that your ability to manufacture your source, create your product, and sell them, that's a core competency. No business can have core competencies across every functional part of the business. Some things you outsource to the partners, some you outsource to systems or software, and others you don't do. The way I would think through it is it needs to be compelling for you to do fulfillment yourself.
It either means you've got a specialized product or customer experience that you want to honor and that has some additional benefit to you. You can charge a higher price for that, etc. Maybe you do those things. The flip side is maybe you go with 3PL, “I want to run a lean business and I don't want to have the headaches of dealing with boxes and duct tape running out.” That can also be the case. For me, it comes down to, does this need to be a core competency for your business. If not, find the most economical solution with your partner with an expert in the space.
Start with the right question on core competencies. Wrapping up, I would like to take you on our lightning round. I'm going to ask you about 6 or so questions and if we could use a single sentence to answer each of them, you'll be okay.
Perfect. Let's go.
What advice would you give yourself five years ago?
Chill out.
Who has been the most meaningful business contact in the last five years?
My co-founder, Stefano.
Are you a morning person?
Yes. I've got young kids in the house.
What does your morning routine look like?
At the moment, it's all kids. It feels like it's herding getting them ready to get to school.
Are you into sports? Do you play any sports?
Yes. I play a bit of social football. I'm a big Manchester United fan.
Who's your favorite athlete or favorite sports team?
Manchester United, that's the one that I love. A little bit of a love-hate relationship but I've always been a massive fan of Cristiano Ronaldo. I don't think he's the most talented footballer ever but I think he's been one of the most hardworking athletes in the modern-day era.
Discipline and respect for self. What two things can't you live without?
My family and red wine.
What book are you currently reading or listening to?
Outlive by Dr. Peter Attia.
Longevity is a big thing for us. Adii, it's been a pleasure having you on the 2X eCommerce podcast. For people who want to find out more about Cogsy, it's Cogsy.com. They have a fourteen-day trial, which you could try yourselves. Are you active on any social media platforms?
Anyone can find me on Twitter, @adii, or the team if they want to, which is @getcogsy. Everyone can also email me directly, Adii@Cogsy.com. I am pretty responsive when my inbox isn't fully blown up every other day. If you want to chat, reach out. I’m happy to chat via any medium.
Adii, thank you for coming on the 2X eCommerce podcast. That's a nice handle, by the way.
That's what you get from being an early adopter, Kunle. That's the early claim, right place, and right time.
Cheers.