Joaquin Villalba is the CEO and co-founder of Nextail, a smart platform for retail merchandising.
A retail industry veteran, Joaquin has almost two decades of experience in innovation, retail and operations.
Prior to Nextail, Joaquin was Head of European Logistics for Zara-Inditex, the world’s largest fashion retailer. In that capacity, he oversaw more than a thousand retail stores with over $10 billion in annual sales. He also led technical innovation for the company, creating new solutions to manage product flow in high-volume flagship stores.
Joaquin is a frequent speaker at retail industry events and a lecturer in operations executive programs. He is an Industrial Engineer and holds an MBA from INSEAD. Joaquin and his wife, Rocio are raising their three children, all under the age of three! Rocio is also Nextail’s most prolific headhunter.
The Fashion Retailer: What is Nextail?
Joaquín Villalba: Nextail is a smart platform for retail merchandising. Developed by retail experts, it delivers agile data-driven decisions to meet increasing consumer demands. Using Nextail’s AI and advanced analytics, global retailers like Pepe Jeans, Twinset and Neck and Neck are automating dynamic buying and merchandising. Within weeks, sales and margins increase while stock levels are reduced.
TFR: What is the entrepreneur story that inspired the launch of the company?
J.Villalba: My background in engineering means a lifelong fascination with improving the way things work. On entering the world of retail, I often saw frustrated customers not finding what they wanted, and it’s because retailers had very static processes in place meaning they couldn’t act fast enough to meet customer demand.
During my time at Zara, I reflected on what moved the founder of Inditex, Amancio Ortega, to pursue a more innovative retail concept. The operational inefficiencies and inaccessibility of retail at that time drove his innovation. His dissatisfaction with the existing retail model inspired him to create something new, which is exactly how I felt with Nextail.
We want to change commerce by transforming how retailers buy new collections and distribute products, using an agile approach based on bottom-up decisions and automation. Essentially, I wanted to fix the frustrations of those customers I’d seen early on in my retail career.
My co-founder, Carlos Miragall, and I met whilst studying engineering together in Valencia. He was Senior Manager of A.T. Kearney, working on strategic and operational projects across several industries including retail.
He didn’t hesitate in joining the Nextail adventure which was just starting in an accelerator in Miami. I’m thankful he did – not only is it important to have people you trust around you, it’s more fun to celebrate the successes with those who have shared the journey!
TFR: Retail is facing new challenges in every phase of the value chain. Retailers are struggling to sell at full price and have difficulties to optimize their stocks (e.g. manage the right stock turns, calculating in-season forecast). What are the main challenges regarding inventory management?
J.Villalba: These days much of the merchandising function is impacted by the shortening of product life cycles. At the same time as the shift in product life cycle, retailers are now having to deal with how inventory moves through a more complex, multichannel customer journey – like consumers buying online to return in store, or the unexpectedly high returns rates after sales events.
Traditional top-down decision-making designed for seasonal cycles no longer suits the need for speed in today’s industry. Retailers bound to these methods are finding they have too much stock, which results in year-round discounting, as well as missing out on sales they could have captured.
Regardless of a retailer’s market, from fast fashion through to luxury, today’s agile retailers have to reorganize their collections and their decision-making processes to suit this pace. Restructuring the way customer feedback is acted upon means an increase in capsules, or “drops” where the first allocation to stores is smaller, and a search for shorter production times. Today’s retailers need to upgrade their capabilities to use data in order to predict which products will need reallocating, reordering or promoting.
Without advanced systems built especially for these challenges, this can result in misallocation of stock, leading to overstocks and lost sales. Traditional decision-making methods, like using only past sales to calculate future demand, statically clustering stores and relying on intuition, do not stand up to the pressures of retail today.
TFR: Making supply meet demand in an uncertain global economy, when trends and weather are also volatile, is very difficult. How is Nextail helping retailers to reduce those risks?
J.Villalba: Today retailers must make more decisions in a shorter window of time. We develop solutions which help automate those decisions, enabling agility in the retailers’ business.
Nextail’s machine learning allows for improved demand prediction, powering the decisions behind each store in a retailers’ network and each SKU in its assortment according to its own expected behavior. Nextail’s algorithms use historical sales and stock data to learn about the behavior of different product attributes in different stores, model seasonality and promotional factors at store and family level or calculate size curves to account for the demographics of each store. The result is an incredibly granular forecast that estimates probabilistically how products will perform in the future.
Nextail Transfers – Click to watch
Even when historical data is not rich enough, for example when a retailer is launching a new product, or opening a new location, the algorithms can dynamically cluster by store and product attributes, extracted by computer vision, to create a robust forecast.
But the work does not stop at the forecast, Nextail delivers the actual decision that will maximize the sales of the retailer, for example dynamically ranking the stores at product, color and sku level based on their sales probability in the case of warehouse scarcity. As of now, Nextail can help retailers in taking better decisions around buying, allocation and replenishment and stock rebalancing.
TFR: Could you briefly explain a business case from the fashion apparel industry where Nextail participated? What was the need of your client and how did you solve it?
J.Villalba: A leading Italian brand decided to undergo a transformation regarding their merchandising decisions. Having previously relied on a nearly manual Excel database for inventory management, they had an unstructured approach to stock allocation.
As a result of the Nextail integration, the brand saw a 10% uplift in sell-through in Spring/Summer 2018, compared to the previous season. The company culture has become more agile with old static habits being broken.
There has also been a significant decrease in human error, due to less human intervention. This has freed up employees’ time so they can focus on more strategic tasks, such as providing better service in-store and maintaining support service across all stores, rather than only in the high-volume stores.
With Nextail, the retailer was able to lower stock levels in stores and yet still increase sales by having the right merchandise in the right stores.
TFR: There is a big demand for Data scientists. How do you manage to find these profiles and keep them happy?
J.Villalba: When people across the business are working on something they know is transforming an industry, it’s hugely rewarding. Being a part of that change is really motivating for our team. We’re working on state-of-the-art technology – machine learning and artificial intelligence to automate decision making that is ground-breaking for any industry, as well as entirely new for retail.
It’s also crucial for us to be visible and engaged in the community, especially through events. Jose Luis, our VP of Data Science and Analytics speaks frequently at events such as Big Data Spain, and IE Exponential Learning events and we have team members who we met through the IE Data Science Bootcamp they run throughout the year. Word of mouth recommendations from existing team members are also valuable.
We know that personal/professional development is massively important for both talent acquisition and retention. That’s why we’re recently introduced our Head of Talent. They’re promoting the accelerated and scalable growth of talent, and reinforcing the company values and organizational culture that will allow us to keep attracting and developing top talent.
We currently have more than 90 professionals from the world of retail, technology and operations, based between Spain, Italy, the United Kingdom, Russia and the USA.
TFR: Do you feel fashion is becoming more science than art?
J.Villalba: There needs to be a balance. At Nextail, we are passionate about how data and technology can transform the fashion retail industry. This doesn’t mean that there is no space for art in fashion. Some roles, such as buying, will always require a degree of intuition, and product design is a creative art – neither can be replaced by science alone. In these spaces, leveraging technology can empower individuals, from making more informed decisions based on historical data, to freeing up time with automation. Using technology in that way means creative experts get to focus on innovation and in turn deliver a more engaging product offering for shoppers.
TFR: As a start-up, what do you think are the key success factors that brings you to compete with big companies like JDA, Oracle or SAP?
J.Villalba: Passion, innovation and impact. Our passion singles us out. We’re very lucky in that our team is formed of many retail experts – not only have we attracted talent from leading retailers and retail consultants, but our founders had firsthand experience in what the industry needed. At our core we are retail. That means our solutions speak very directly to our industry’s needs. Many of us in the company have seen directly from the inside how the customer has changed, how the markets’ needs have shifted and understand the complexities of merchandising and allocation.
We’ve taken the depth of that knowledge and have a committed vertical focus – something that other software companies can’t do, due to their size. That means our artificial intelligence and machine learning are developed specifically for companies in the business of selling seasonal products.
We’re also incredibly committed to making sure we have a significant bottom line impact, not just by improving collaboration and communication or by automating transactions, but by improving the quality of the decisions. Also, we didn’t want to develop a technology that took several months to deliver value. Nextail starts impacting a retailers’ bottom line right after implementation. That same quest for impact filters down to every new product feature and team output.
Finally, innovation is in our DNA, all our platform is based on new technology, native for the cloud and designed to scale and transform how companies make decisions. For example, the look and feel of the Nextail platform is designed to look like a consumer app, easy to use by anyone, especially when compared to traditional systems…
Passion, innovation and impact are the core values of Nextail. If you feel that you share them, please get in touch with us!
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