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Vorstellung der Version 2.0

Vorstellung der Version 2.0

Im Entwicklungsprozess unserer Lösung spielen der Markt und die Bedürfnisse unserer Kunden eine wichtige Rolle. Um diesen Anforderungen gerecht zu werden, haben wir Software-Updates, in denen wir unsere Lösung ständig weiterentwickeln. Neben der sich ständig weiterentwickelnden Entscheidungsintelligenz, basierend auf den Abverkäufen, ist es uns wichtig, dass jeder unserer Anwender mehr aus seinen Daten herausholen kann. Die Produktleistung, insbesondere für die Kollektionsrahmenplanung, spielt dabei eine entscheidende Rolle. In unserer neuesten Version stellen wir drei wesentliche Updates vor. Erstens, haben wir der Nachversorgungsliste eine Kartenansicht hinzugefügt. Jede Karte in dieser Ansicht stellt eine Aggregation aller SKU-Standorte dar, die zu einer einzigen Stil- und Farbkombination gehören. Jede Karte bietet Metadaten über diese SKU, Verkaufsdaten und Bestandsdaten. Sie können der Kartenoption Produktbilder hinzufügen, um auf einen Blick zu sehen, auf welchen Artikel sich die Karte bezieht. Hiermit wollen wir einen weiteren Schritt in Richtung einer umfassenderen Produktperformance gehen und unseren Kunden mehr Informationen für z.B. ihre Kollektionsrahmenplanung bieten. Weitere Updates werden hier in Zukunft verfügbar sein. Zweitens, haben wir zusätzliche Nachversorgungs-Logiken entwickelt, wie z. B. End-of-Life-Verfahren und Forward Cover auf SKU-Ebene. Dies gibt den Anwendern noch mehr Kontrolle, pro POS (Point of Sale) und pro Produkt, um die Warensteuerung für ihre individuellen Bedürfnisse anzupassen. Zu guter Letzt, haben wir einige wichtige Updates für unsere intelligente initiale Verteilung vorgenommen. Basierend auf unseren dynamischen Clustern und errechneten Prognosen kann die initiale Verteilung der gesamten Kollektion pro SKU automatisiert werden. Jeder POS wird mit der optimalen Menge auf Stil-, Farb- und Größenebene bestückt. So können wir nicht nur den Umsatz steigern, sondern auch das Risiko von Fehlbestückungen und daraus resultierenden Überbeständen und/oder starken Reduzierungen minimieren. Möchten Sie mehr über dieses neueste Update erfahren? Nimm gerne Kontakt mit uns auf

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Introducing Version 2.0

Introducing Version 2.0

In the development process of our solution, the market and the needs of our customers play a key role. To meet these requirements, we have system updates in which we constantly develop our solution. Besides the always evolving decision making intelligence, based on sales, it is important to us that each of our users can get more out of their data. Product performance, especially for collection planning, plays a crucial role in this. In our latest version we proudly introduce three major updates. Firstly, we have added a cardview option to the replenishment list. Each card in this view represents an aggregation of all SKU-locations belonging to a single style and color combination. Each card provides meta data about abut the SKU, sales data and inventory data. You can add product images to the card option to see at a glance what item is being referred to. Hereby we want to take another step closer to a more comprehensive product performance and offer our customers more information for, for example, their collection planning. More updates will be available here in the future. Secondly, we have developed additional replenishment logics, such as end-of-life procedures and forward covers at the SKU level. This gives users even more control, per POS (point of sale) and per product, to customize the merchandise management for their individual needs. Last but not least, we made some important updates to our smart initial allocation. Based on our dynamic clusters and forecasts calculated, you can automate the initiale allocation of the entire collection per SKU. Each POS will be allocated with the optimal quantity on style, color and size level. This allows us not only to increase sales, but also to reduce the risk of misplacement and the resulting overstocking or significant reductions. Would you like to know more about this latest update? Feel free to contact us

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Introducing Version 2.0

Introducing Version 2.0

In the development process of our solution, the market and the needs of our customers play a key role. To meet these requirements, we have system updates in which we constantly develop our solution. Besides the always evolving decision making intelligence, based on sales, it is important to us that each of our users can get more out of their data. Product performance, especially for collection planning, plays a crucial role in this. In our latest version we proudly introduce three major updates. Firstly, we have added a cardview option to the replenishment list. Each card in this view represents an aggregation of all SKU-locations belonging to a single style and color combination. Each card provides meta data about abut the SKU, sales data and inventory data. You can add product images to the card option to see at a glance what item is being referred to. Hereby we want to take another step closer to a more comprehensive product performance and offer our customers more information for, for example, their collection planning. More updates will be available here in the future. Secondly, we have developed additional replenishment logics, such as end-of-life procedures and forward covers at the SKU level. This gives users even more control, per POS (point of sale) and per product, to customize the merchandise management for their individual needs. Last but not least, we made some important updates to our smart initial allocation. Based on our dynamic clusters and forecasts calculated, you can automate the initiale allocation of the entire collection per SKU. Each POS will be allocated with the optimal quantity on style, color and size level. This allows us not only to increase sales, but also to reduce the risk of misplacement and the resulting overstocking or significant reductions. Would you like to know more about this latest update? Feel free to contact us

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Wir stellen vor: Initiale Verteilung - Lasst vorausschauende Algorithmen die Arbeit machen!

Wir stellen vor: Initiale Verteilung - Lasst vorausschauende Algorithmen die Arbeit machen!

"Der aktuelle Entwicklungsschritt ist für uns sehr wichtig, da wir nicht nur das gesamte In-Season-Management mit Nachversorgung und alternativen Produkten verbessern wollen, sondern auch das gesamte Geschäft nachhaltiger gestalten wollen" Ben Vermin, CEO & Founder Das Thema Nachhaltigkeit ist in letzter Zeit in aller Munde. Und das ist auch gut so, denn wir haben nur diese eine Welt und wir müssen uns um sie kümmern. Aber ist Nachhaltigkeit in der Modeindustrie möglich? Stell dir vor, du musst manuell analysieren, in welchem Teil des Landes die Konsumenten etwas kaufen und in welchem nicht. Stell dir vor, du gehst noch einen Schritt weiter und analysierst denselben Artikel, aber dann auch in allen Farbe. Dann stell dir vor, du gehst noch einen Schritt weiter und analysierst nicht nur den Artikel und die Farbe, sondern auch die Größe. Du wirst Stunden um Stunden mit der Analyse verbringen, ganz zu schweigen von der Möglichkeit menschlicher Fehler. Nein danke, darauf verzichte ich! Also, was tun? Die Verluste zählen und alles, was nicht rechtzeitig verkauft wird, in die Outlets werfen und dabei den aktuellen Trend zum Nachhaltigkeitsbewusstsein ignorieren? Oder bittest du um Hilfe, wenn du nicht mehr in der Lage bist, es selbst zu tun? Bei Chainbalance gehören Nachhaltigkeit und der Kampf gegen die Verschwendung zu den obersten Prioritäten. Deshalb basiert jedes Mal, wenn eine neue Funktion eingeführt wird, diese auf aktuellen Zahlen und Trends, die im Markt aktiv sind. Das ist eine große Herausforderung und erfordert Erfahrung mit Produktgruppen, Produkteigenschaften und dem POS (Point-of-Sale). Welche Art von Kunden kauft in diesem spezifischen Geschäft und was kaufen sie? Das Sammeln all dieser Informationen auf Basis der tatsächlichen Verkaufsdaten ermöglicht es, die Wertschöpfungskette noch weiter zu optimieren. Wir stellen vor: Intelligente Initiale Verteilung - Lasst vorausschauende Algorithmen die Arbeit machen! Die wichtigste Frage, die sich bei der Einführung neuer Produkte in einem Markt stellt, ist: "Welche Produktgruppen, Stile, Farben und Größenschlüssel und in welcher Menge müssen im Laden verfügbar sein, um die anfängliche Verbrauchernachfrage zu erfüllen?" Du wirst diese Frage wahrscheinlich auf der Grundlage von Erfahrungen beantworten, die du in der Vergangenheit mit ähnlichen Artikeln gemacht hast, richtig? Dann lass dies doch automatisch erledigen! Die Analyse der Abverkäufe aus den voherigen und besonders der "Spiegelsaison", also einer vorangegangenen Saison mit ähnlichen Artikeln, wird als Grundlage für eine intelligente Entscheidungsfindung genutzt, um Überbestände und zu frühe Ausverkäufe zu vermeiden. Diese Analysen sind extrem umfangreich und daher sehr zeitaufwendig. Es ist notwendig herauszufinden, welche Kuratierung für die spezifische Fläche erforderlich ist, basierend auf der historischen Abverkäufen. Wie funktioniert das? Die A-B-C-Cluster werden häufig zur Umsatzprognose und zur groben Angabe der Größe des Fläche und des Sortiments verwendet. Bei der A-B-C-Cluster-Methode kennzeichnen Sie Ihr größtes Sortiment mit dem Buchstaben A, die mittlere Größe mit dem Buchstaben B und die kleinste Größe mit dem Buchstaben C. Diese Methode hat sich über die Jahre etabliert und soll die großen Unterschiede zwischen Flächen im Norden und im Süden eines Landes aufzeigen. Aber was passiert, wenn man in diese Standorte noch detaillierter analysiert und die Unterschiede in der Kundennachfrage und den Trends auf Stadtebene betrachtet? Was wir wirklich wissen müssen ist, was die Unterschiede zwischen zwei Geschäften in derselben Stadt sind. Ja, beide haben ihre eigene Customer Journey, verkaufen unterschiedliche Produkte und sprechen unterschiedliche Kunden mit unterschiedlichem Einkaufsverhalten an, aber warum sind sie so grundlegend verschieden? Um also ein dynamisches und individuelles Cluster für jeden POS zu erstellen, müssen diese Unterschiede identifiziert werden und sich zusammen mit den Produkten, der Zeit und den bestehenden Marktbedingungen verändern. Was du siehst, ist was du bekommst, richtig? Bei der Einführung neuer Produkte auf dem Markt spielt der Zeitpunkt der Saison eine wichtige Rolle. Ein Geschäft, das nur große, warme, flauschige Mäntel verkauft, wird wahrscheinlich im Winter erfolgreicher sein. Dies ist jedoch keine Standardregel mehr. Das Kaufverhalten der Verbraucher wird immer dynamischer. Es ist nicht mehr, das was du siehst, ist das was du bekommst, sondern eher eine was du willst, ist das was du bekommst Denkweise. Wenn Sie den flauschigen Mantel im August haben wollen, dann hält Sie nichts davon ab, ihn zu kaufen. Das bedeutet, dass dieses starre Protokoll für die Branche nicht mehr ganz passt. Die Textil- und Modeindustrie hat dafür eine Lösung. Um die dynamische Nachfrage über das ganze Jahr hinweg optimal bedienen zu können, bietet die Branche mehrere Kollektionen und Kapseln an, auch Ready-to-Wear genannt. Dabei sind 12-24 Kollektionen keine Seltenheit mehr. Dies ist eine wesentlich bessere Möglichkeit, die Nachfrage genauer zu befriedigen, erhöht aber auch den Aufwand für die Industrie und den Handel. Der Analyseaufwand steigt ins Unermessliche, wenn man bedenkt, dass 12 Kollektionen pro Jahr, mit vielen SKUs, nach dynamischen Clustern verwaltet werden müssen. Wie hilft Chainbalance nun? Durch 12 Jahre Erfahrung im Bereich Nachversorgung, erlernte Geschäftsregeln und die Anwendung von dynamischen und intelligenten Algorithmen werden automatisierte Entscheidungen für die optimale initiale Verteilung getroffen. Diese basiert u. a. auf dynamischen Clustern für die POS-Performance und die Performance bestimmter Artikel in Bezug auf die aktuelle Marktsituation. Für eine erste Berechnung der Erstzuteilung werden lediglich Umsatzinformationen von 4-13 Wochen benötigt. Daraus wird eine Prognose für die optimale Mengenzuteilung pro Größe, Farbe und Stil erstellt und zur Verfügung gestellt. "Der aktuelle Entwicklungsschritt ist für uns sehr wichtig, da wir nicht nur das gesamte In-Season-Management mit Nachschub oder alternativen Produkten verbessern, sondern auch das gesamte Geschäft nachhaltiger gestalten wollen. Dazu müssen wir gemeinsam mit unseren aktuellen Kunden in die Pre-Season-Optimierung gehen. Welche Produkte benötigt werden, insbesondere wie viele und wann ein Produkt nachproduziert werden muss oder nicht, sind entscheidende Fragen, die wir beantworten wollen." Ben Vermin CEO & Gründer Starte noch heute und mache dein Business nachhaltiger! Ein nachhaltiges Geschäft entsteht, wenn man seine Kunden besser versteht und Daten nutzt, um wertvolle Erkenntnisse zu gewinnen. Die derzeitige Überproduktion und die daraus resultierenden Restbestände schaden der Umwelt und dem Geschäft. Chainbalance hilft! Nach einem erfolgreichen Start und Test freuen wir uns nun, anderen Marken diese Lösung zur Verfügung zu stellen, um das gesamte Geschäft noch nachhaltiger zu gestalten. Sie möchten unsere Lösung für die initiale Verteilung kennenlernen? Lass uns in Kontakt treten!

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Introducing Smart Initial Allocation - Let predictive algorithms do the work!

Introducing Smart Initial Allocation - Let predictive algorithms do the work!

"The current development step is very important for us, as we not only want to improve the overall in-season management with replenishment or alternative products but also make the entire business more sustainable" Ben Vermin, CEO & Founder Sustainability is something on almost everyone's mind lately. Which is a good thing, because we only have one world, and we need to take care of it. But is sustainability possible in the fashion industry? Imagine having to manually analyze in which part of the country consumers buy items and in which part they don’t. Imagine taking that a step further and analyzing the same item but then based on color too. Then imagine taking that even further and analyzing not only the item and color but also the size. You will be spending hours and hours analyzing this, not even to mention the chances of human error. No thank you, I'll pass on that! So, what do you do then? Count your losses and throw anything that isn’t sold on time into the outlet ignoring the current trend in sustainability awareness? Or do you ask for help when you are not able to do it yourself anymore? At Chainbalance, sustainability and battling waste are some of the top incentives. Therefore, each time a new feature is launched this is based on actual figures and trends active in the market. It is a big challenge and requires experience with product groups, product characteristics, and POS (point-of-sale). What kind of customer buys at that specific store and what do they buy? Gathering all this information based on actual sales data makes it possible to optimize the value chain even further. Introducing Smart Initial Allocation - Let predictive algorithms do the work! The main question asked when launching new items in a store is: “what product groups, styles, colors, and size keys and in what quantity needs to be available in-store to meet the initial consumer demand?” You will probably answer this question based on experiences you had with similar items in the past, right? Then why not have this done automatically! The analysis of sales from the ‘mirror season’, a previous season with similar items, is used as the foundation for smart decision making, avoiding overstocking and running out too early. These analyses are extremely extensive and therefore very time-consuming. It is necessary to figure out what curation is needed for the specific POS based on the historical performance of the POS. How does it work? The A-B-C clusters are often used in predicting sales and roughly indicating the size of the POS and assortment. With the A-B-C cluster method, you mark your big size assortment with the letter A, middle size with the letter B, and small size with the letter C. This method has been used throughout the years and has always shown the big differences between stores located in the north and the south of a country. But what happens when you zoom in on these locations and analyze differences in demand and trends on a city level? What you really need to know is what the differences are between two stores in the same city. Yes, they both have their own customer journey, sell different products, and appeal to different customers with various shopping behaviors, but why are they so fundamentally different? So, to create a dynamic and individuell cluster for each POS these differences need to be identified and change dynamically along with the products, time, and existing market conditions. What you see is what you get, right? When introducing new items onto the market the time of the season will play an important role. A store that only sells big, warm fluffy coats will probably be more successful in the winter. However, this is no longer a default rule. The buying behavior of consumers is becoming more and more dynamic. It is no longer what you see is what you get, but more a what you want is what you get the mindset. If you want that fluffy coat in August, then nothing is stopping you from buying it. Meaning that a static protocol doesn’t fully fit the industry anymore. The textile and fashion industry has a solution for this. To optimally meet the dynamic demand throughout the year, the industry offers several collections and capsules, also known as Ready to Wear. Thereby 12-24 collections are not uncommon any more. This is a much better way to meet demand, but it also increases the efforts of the industry and retailers. The analysis effort increases immeasurably when you consider that 12 collections per year, with many SKUs, need to be managed according to dynamic clusters. How does Chainbalance step in? Through 12 years of experience in replenishment, learned business rules, and the application of dynamic and intelligent algorithms, automated decisions are made for the optimal initial allocation. This is based, among other things, on dynamic clusters for POS performance and the performance of specific items in relation to the current market situation. For an initial calculation of the first allocation, sales information from just 4-13 weeks is needed. From this, a forecast for the optimal quantity allocation per size, color, and style is created and made available to you. "The current development step is very important for us, as we not only want to improve the overall in-season management with replenishment or alternative products but also make the entire business more sustainable. To do this, we must go into pre-season optimization together with our current customers. Which products are needed, especially how many and when a product needs to be reproduce or not, are crucial questions we want to answer." Ben Vermin CEO & Founder Start today and make your business more sustainable! A sustainable business comes from understanding your customers better and using data to gain valuable insights. The current over-production and resulting leftover goods are hurting the environment and the business. Chainbalance will help! After a successful start and test, we are now happy to provide other brands with this solution to make the entire business even more sustainable.

You want to know about our solution for the initial allocation? Let's get in contact!

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How the Corona crisis influenced the fashion industry

How the Corona crisis influenced the fashion industry

Slowly but surely, the world is reopening around us, and people are starting to consume more again. But what will happen with last year's merchandise that hasn't been sold due to lockdown? Will all this merchandise be released into the market anyway? Because we are talking about tons of clothing! We will tell you more about it in this blog. What is the market telling us?
The Corona pandemic has caused considerable damage in the private sector and in the economy worldwide. The apparel and fashion industry have suffered greatly. Sales losses of 30-50%, job losses and mountains of merchandise in closed stores and warehouses which cause problematic overstocking. The question most people are asking is, what will happen with unsold goods from last year’s collection? Well, what is the market telling us right now?

Firstly, the fact that in many countries the stores have been able to re-open is a first sign. The Netherlands has reopened in May, England and Wales since mid-April and now Germany is following this trend too. This is a very good sign for the overall trade and industry and gives hope for “the new normal”. Secondly, the very pleasing figures within the industry showing frequent growth is a key metric in predicting the trends. In the early stages of reopening stores in England the industry was blown away when it reported a weekly frequency growth of over 200%. And this is not unusual, because the Netherlands has shown similar growth results after reopening. Overall, very pleasing news and very important progress for the industry. What will happen in 2021 with the goods from 2020?
As mentioned earlier, overstocking is a major problem. But what happens with the clothes that are not sold? Will they just get burned? Or thrown in the trash? Certainly not! All around us we are seeing fashion stores pushing their collections forward to compensate for lost sales and lower as much of the overstock as possible. Thomas Fischer, consultant for recycling management at the Fachverband Textilrecycling, speaks of "150,000 tons of clothing that will soon be pushed into the market. That's 54 soccer fields full of fabric bales." Can you imagine! Is there a new trend?
Many goods from last year were not seen by the consumer, and the need for these products is still there. Because the classic protocol for the summer and winter sales has actually not been valid for a long time, and already showed the first sharp moves of change in 2020. Due to delivery delays, in the first lock down, the initial allocation of many collections was changed for the first time and used more dynamically in the market than in previous years. The market has reacted positively to this and furthermore industry experts have been demanding this change for years. An individual adjustment of the initial allocation to the needs of the consumer brings many advantages, such as margin optimisation, through higher sales and lower discount. This trend will continue to grow. Fashion recovery plan
The next step is to successfully distribute these products into the market. The question is, how do you do that? What is necessary to quickly cover the dynamic demand, with the optimal products and quantities? The answer is detailed analyses and super speedy reactions on this data. Which raises a new question. How will the retailers and industry ever find all that time to do these analyses? Retailers often manage hundreds of brands, with sometimes 6-24 delivery dates. There is no time for detailed analyses on size and color level. Moreover, retailers will probably not continue to invest in buyers, due to heavy losses in the years before. This concept no longer works. This means more responsibility for the industry. However, more responsibility needs to go hand in hand with more control. But how should the industry handle this challenge and realize its growth potential? Relying on software
The effort of the analyses, especially on style, color and size level, for each product in the collection is incredibly high - not to be done manually, if you consider that today's shopping behavior is dynamic and fast. Even solutions such as 1-on-1 replenishment or static reorder targets, cannot keep up with consumer demand. In order to keep up with consumer demand, solutions are needed that analyze each product daily, on style, color and size level, based on demand and make independent decisions. Using logic beyond our human brain will help calculate the best replenishment cycle allowing you to focus on other important things like marketing your store.

Companies like YAYA, adidas and Van Bommel have been working with Chainbalance for a few months already and they have all seen massive changes in their sales, lowering overstock and freeing up more time to focus on full recovery. Read their business cases here and find out how you can also successfully recover from Covid-19. Chainbalance - make the consumer the heartbeat of your value chain!

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Der Einfluss der Corona-Krise auf die Modebranche

Der Einfluss der Corona-Krise auf die Modebranche

Langsam aber sicher öffnet sich die Welt um uns herum wieder und die Menschen beginnen wieder mehr zu konsumieren. Aber was passiert mit der Ware aus dem letzten Jahr, die wegen der Schließung nicht verkauft wurde? Wird all diese Ware trotzdem auf den Markt kommen? Denn wir reden hier von Tonnen von Kleidung! In diesem Blog erfährst Du mehr darüber. Was sagt uns der Markt? Die Corona-Pandemie hat im privaten Sektor und in der Wirtschaft weltweit erheblichen Schaden angerichtet. Die Bekleidungs- und Modeindustrie ist besonders betroffen. Umsatzeinbußen von 30-50%, Arbeitsplatzverluste und Berge von Waren in geschlossenen Geschäften und Lägern, die eine problematische Überfüllung verursachen. Die Frage, die sich die meisten Menschen stellen ist, was mit der unverkauften Ware aus der letzten Kollektion passieren wird? Nun, was sagt uns der Markt im Moment?

Zunächst einmal ist die Tatsache, dass in vielen Ländern die Läden wieder öffnen konnten, ein erstes Zeichen. Die Niederlande haben im Mai wieder geöffnet, England und Wales seit Mitte April und nun folgt auch Deutschland diesem Trend. Das ist ein sehr gutes Zeichen für den gesamten Handel und die Industrie und macht Hoffnung auf die "neue Normalität". Zweitens sind die sehr erfreulichen Zahlen innerhalb der Branche, die ein stetiges Wachstum zeigen, ein wichtiger Gradmesser für die Vorhersage der Trends. In der Anfangsphase der Wiedereröffnung von Geschäften in England war die Begeisterung der Branche groß, als sie ein wöchentliches Frequenzwachstum von über 200 % meldete. Und das ist nicht ungewöhnlich, denn die Niederlande haben ähnliche Wachstumsergebnisse nach Wiedereröffnungen gezeigt. Insgesamt eine sehr erfreuliche Nachricht und ein sehr wichtiger Fortschritt für die Branche. Was wird 2021 mit der Ware aus 2020 passieren?
Thomas Fischer, Referent für Kreislaufwirtschaft beim Fachverband Textilrecycling, spricht von "150.000 Tonnen Kleidung, die bald in den Markt gedrückt werden. Das sind 54 Fußballfelder voll mit Stoffballen." Kannst du dir das vorstellen? Wie bereits erwähnt, ist der Überbestand ein großes Problem. Aber was passiert mit den Kleidungsstücken, die nicht verkauft werden? Werden sie einfach verbrannt? Oder auf den Müll geworfen? Sicherlich nicht! Überall um uns herum sehen wir, wie Modegeschäfte ihre Kollektionen nach vorne schieben, um entgangene Verkäufe zu kompensieren und so viel wie möglich von den Überbeständen abzubauen. Gibt es einen neuen Trend?
Viele Waren aus dem letzten Jahr hat der Verbraucher nicht gesehen und der Bedarf an diesen Produkten ist immer noch da. Denn das klassische Protokoll für den Sommer- und Winterkollektionen gilt eigentlich schon lange nicht mehr und zeigte bereits 2020 die ersten scharfen Züge der Veränderung. Aufgrund von Lieferverzögerungen wurde im ersten Lockdown die initiale Verteilung vieler Kollektionen erstmals verändert und dynamischer im Markt eingesetzt als in den Vorjahren. Der Markt hat darauf positiv reagiert - zumindest in der Öffnungsphase - und darüber hinaus fordern Branchenexperten diese Änderung seit Jahren. Eine individuelle Anpassung der initialen Verteilung an die Bedürfnisse des Verbrauchers bringt viele Vorteile, wie z.B. eine Margenoptimierung, mit höhere Umsätze und geringere Reduzierungen. Dieser Trend wird sich weiter durchsetzten. Die Erholungsphase Der nächste Schritt besteht darin, diese Produkte erfolgreich im Markt zu verteilen. Die Frage ist, wie man das macht? Was ist notwendig, um die dynamische Nachfrage schnell zu decken, mit den optimalen Produkten und Mengen? Die Antwort sind detaillierte Analysen und superschnelle Reaktionen auf den Bedarf. Was eine neue Frage aufwirft. Wie werden die Einzelhändler und die Industrie jemals die Zeit finden, diese Analysen durchzuführen? Einzelhändler verwalten oft Hunderte von Marken, mit manchmal 24 Lieferterminen. Da bleibt keine Zeit für detaillierte Analysen auf Größen- und Farbebene. Außerdem werden die Einzelhändler aufgrund der hohen Verluste in den vergangenen Jahren wahrscheinlich nicht mehr in Einkäufer investieren. Dieses Konzept funktioniert nicht mehr. Das bedeutet mehr Verantwortung für die Industrie. Mehr Verantwortung muss jedoch mit mehr Kontrolle einhergehen. Doch wie soll die Branche mit dieser Herausforderung umgehen und ihr Wachstumspotenzial ausschöpfen? Der Einsatz von Software Der Aufwand der Analysen, insbesondere auf Stil-, Farb- und Größenebene, für jedes Produkt in der Kollektion ist unglaublich hoch - und nicht manuell zu leisten, wenn man bedenkt, dass das heutige Einkaufsverhalten dynamisch und schnell ist. Selbst Lösungen wie 1-zu-1-Nachversorgung oder statische Meldebestände können mit der Verbrauchernachfrage nicht mithalten. Um mit der Verbrauchernachfrage Schritt zu halten, werden Lösungen benötigt, die auf Basis der Nachfrage jedes Produkt täglich auf Stil-, Farb- und Größenebene analysieren und individuelle Entscheidungen treffen. Die Verwendung von Logik jenseits unseres menschlichen Gehirns hilft dabei, den besten Nachschubzyklus zu berechnen, sodass Sie sich auf andere wichtige Dinge wie die Verkaufsförderung Ihres Geschäfts konzentrieren können. Unternehmen wie YAYA, adidas und Van Bommel arbeiten bereits seit einigen Monaten mit Chainbalance und sie alle haben massive Veränderungen in ihren Verkäufen festgestellt, den Überbestand gesenkt und mehr Zeit gewonnen, um sich auf die vollständige Erholung zu konzentrieren. Erfahre in unseren Erfahrungsberichten, wie auch Du dich erfolgreich von Covid-19 erholen kannst. Chainbalance - machen Sie den Verbraucher zum Herzschlag Ihrer Wertschöpfungskette!

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Introducing Smart Initial Allocation - Let predictive algorithms do the work!

Introducing Smart Initial Allocation - Let predictive algorithms do the work!

"The current development step is very important for us, as we not only want to improve the overall in-season management with replenishment or alternative products but also make the entire business more sustainable" Ben Vermin, CEO & Founder Sustainability is something on almost everyone's mind lately. Which is a good thing, because we only have one world, and we need to take care of it. But is sustainability possible in the fashion industry? Imagine having to manually analyze in which part of the country consumers buy items and in which part they don’t. Imagine taking that a step further and analyzing the same item but then based on color too. Then imagine taking that even further and analyzing not only the item and color but also the size. You will be spending hours and hours analyzing this, not even to mention the chances of human error. No thank you, I'll pass on that! So, what do you do then? Count your losses and throw anything that isn’t sold on time into the outlet ignoring the current trend in sustainability awareness? Or do you ask for help when you are not able to do it yourself anymore? At Chainbalance, sustainability and battling waste are some of the top incentives. Therefore, each time a new feature is launched this is based on actual figures and trends active in the market. It is a big challenge and requires experience with product groups, product characteristics, and POS (point-of-sale). What kind of customer buys at that specific store and what do they buy? Gathering all this information based on actual sales data makes it possible to optimize the value chain even further. Introducing Smart Initial Allocation - Let predictive algorithms do the work! The main question asked when launching new items in a store is: “what product groups, styles, colors, and size keys and in what quantity needs to be available in-store to meet the initial consumer demand?” You will probably answer this question based on experiences you had with similar items in the past, right? Then why not have this done automatically! The analysis of sales from the ‘mirror season’, a previous season with similar items, is used as the foundation for smart decision making, avoiding overstocking and running out too early. These analyses are extremely extensive and therefore very time-consuming. It is necessary to figure out what curation is needed for the specific POS based on the historical performance of the POS. How does it work? The A-B-C clusters are often used in predicting sales and roughly indicating the size of the POS and assortment. With the A-B-C cluster method, you mark your big size assortment with the letter A, middle size with the letter B, and small size with the letter C. This method has been used throughout the years and has always shown the big differences between stores located in the north and the south of a country. But what happens when you zoom in on these locations and analyze differences in demand and trends on a city level? What you really need to know is what the differences are between two stores in the same city. Yes, they both have their own customer journey, sell different products, and appeal to different customers with various shopping behaviors, but why are they so fundamentally different? So, to create a dynamic and individuell cluster for each POS these differences need to be identified and change dynamically along with the products, time, and existing market conditions. What you see is what you get, right? When introducing new items onto the market the time of the season will play an important role. A store that only sells big, warm fluffy coats will probably be more successful in the winter. However, this is no longer a default rule. The buying behavior of consumers is becoming more and more dynamic. It is no longer what you see is what you get, but more a what you want is what you get the mindset. If you want that fluffy coat in August, then nothing is stopping you from buying it. Meaning that a static protocol doesn’t fully fit the industry anymore. The textile and fashion industry has a solution for this. To optimally meet the dynamic demand throughout the year, the industry offers several collections and capsules, also known as Ready to Wear. Thereby 12-24 collections are not uncommon any more. This is a much better way to meet demand, but it also increases the efforts of the industry and retailers. The analysis effort increases immeasurably when you consider that 12 collections per year, with many SKUs, need to be managed according to dynamic clusters. How does Chainbalance step in? Through 12 years of experience in replenishment, learned business rules, and the application of dynamic and intelligent algorithms, automated decisions are made for the optimal initial allocation. This is based, among other things, on dynamic clusters for POS performance and the performance of specific items in relation to the current market situation. For an initial calculation of the first allocation, sales information from just 4-13 weeks is needed. From this, a forecast for the optimal quantity allocation per size, color, and style is created and made available to you. "The current development step is very important for us, as we not only want to improve the overall in-season management with replenishment or alternative products but also make the entire business more sustainable. To do this, we must go into pre-season optimization together with our current customers. Which products are needed, especially how many and when a product needs to be reproduce or not, are crucial questions we want to answer." Ben Vermin CEO & Founder Start today and make your business more sustainable! A sustainable business comes from understanding your customers better and using data to gain valuable insights. The current over-production and resulting leftover goods are hurting the environment and the business. Chainbalance will help! After a successful start and test, we are now happy to provide other brands with this solution to make the entire business even more sustainable.

You want to know about our solution for the initial allocation? Let's get in contact!

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How the Corona pandemic influenced the fashion industry

How the Corona pandemic influenced the fashion industry

Slowly but surely, the world is reopening around us, and people are starting to consume more again. But what will happen with last year's merchandise that hasn't been sold due to lockdown? Will all this merchandise be released into the market anyway? Because we are talking about tons of clothing! We will tell you more about it in this blog. What is the market telling us?
The Corona pandemic has caused considerable damage in the private sector and in the economy worldwide. The apparel and fashion industry have suffered greatly. Sales losses of 30-50%, job losses and mountains of merchandise in closed stores and warehouses which cause problematic overstocking. The question most people are asking is, what will happen with unsold goods from last year’s collection? Well, what is the market telling us right now?

Firstly, the fact that in many countries the stores have been able to re-open is a first sign. The Netherlands has reopened in May, England and Wales since mid-April and now Germany is following this trend too. This is a very good sign for the overall trade and industry and gives hope for “the new normal”. Secondly, the very pleasing figures within the industry showing frequent growth is a key metric in predicting the trends. In the early stages of reopening stores in England the industry was blown away when it reported a weekly frequency growth of over 200%. And this is not unusual, because the Netherlands has shown similar growth results after reopening. Overall, very pleasing news and very important progress for the industry. What will happen in 2021 with the goods from 2020?
As mentioned earlier, overstocking is a major problem. But what happens with the clothes that are not sold? Will they just get burned? Or thrown in the trash? Certainly not! All around us we are seeing fashion stores pushing their collections forward to compensate for lost sales and lower as much of the overstock as possible. Thomas Fischer, consultant for recycling management at the Fachverband Textilrecycling, speaks of "150,000 tons of clothing that will soon be pushed into the market. That's 54 soccer fields full of fabric bales." Can you imagine! Is there a new trend?
Many goods from last year were not seen by the consumer, and the need for these products is still there. Because the classic protocol for the summer and winter sales has actually not been valid for a long time, and already showed the first sharp moves of change in 2020. Due to delivery delays, in the first lock down, the initial allocation of many collections was changed for the first time and used more dynamically in the market than in previous years. The market has reacted positively to this and furthermore industry experts have been demanding this change for years. An individual adjustment of the initial allocation to the needs of the consumer brings many advantages, such as margin optimisation, through higher sales and lower discount. This trend will continue to grow. Fashion recovery plan
The next step is to successfully distribute these products into the market. The question is, how do you do that? What is necessary to quickly cover the dynamic demand, with the optimal products and quantities? The answer is detailed analyses and super speedy reactions on this data. Which raises a new question. How will the retailers and industry ever find all that time to do these analyses? Retailers often manage hundreds of brands, with sometimes 6-24 delivery dates. There is no time for detailed analyses on size and color level. Moreover, retailers will probably not continue to invest in buyers, due to heavy losses in the years before. This concept no longer works. This means more responsibility for the industry. However, more responsibility needs to go hand in hand with more control. But how should the industry handle this challenge and realize its growth potential? Relying on software
The effort of the analyses, especially on style, color and size level, for each product in the collection is incredibly high - not to be done manually, if you consider that today's shopping behavior is dynamic and fast. Even solutions such as 1-on-1 replenishment or static reorder targets, cannot keep up with consumer demand. In order to keep up with consumer demand, solutions are needed that analyze each product daily, on style, color and size level, based on demand and make independent decisions. Using logic beyond our human brain will help calculate the best replenishment cycle allowing you to focus on other important things like marketing your store.

Companies like YAYA, adidas and Van Bommel have been working with Chainbalance for a few months already and they have all seen massive changes in their sales, lowering overstock and freeing up more time to focus on full recovery. Read their business cases here and find out how you can also successfully recover from Covid-19. Chainbalance - make the consumer the heartbeat of your value chain!

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Wholesale - a losing game? How brands are preparing for the new D2C strategy.

Wholesale - a losing game? How brands are preparing for the new D2C strategy.

S.Oliver, Adidas, Nike want to do what Dior and Bottega Veneta have been doing for years. Direct to consumer - from the classic wholesale model to direct sales! But why are more and more brands deciding on this strategy these days? Especially when you consider that many brands with their own stores have already taken this step. At the time, many retailers threatened to delist and were gleeful to see how difficult the brands found this step. The traditional retail structures with their multi-label department stores were not so easily pushed out of the playing field. Why a new attempt now? Here some reasons. One, of course, is the reaction to the market and its growing online sales channels (+16% in Germany & +20% in the Netherlands). Digitalization makes it possible and the pandemic has only accelerated the online growth channel! The brands have a real experience advantage over the established multi-label retailers. In addition, the online shop promises the desired independence that has been missing in decentralized wholesale for many years. And today's marketplaces create an enormous reach that could never be achieved in offline shops in this way. Moreover, many brands have realized one thing through the pandemic and the continuing staggering losses. Many wholesale addresses will no longer exist in the future! The tectonic shift of the wholesale business. Does this now mean the end of the wholesale business? No. D2C will also drive the re-evolution of the classic wholesale business. Responsibilities, Risks, and controls will be more carefully shared between the retailer and the brands - not a classic wholesale or concession model. The retailers become marketplaces that inspire customers and guests with outreach, atmosphere, and emotion. The brands take over the entire merchandise management at the POS. Of course, this also means more risk for the brands, but also more control and the use of the missing retail know-how. Digitalization is advancing. An optimal D2C strategy, with the new responsibilities in merchandise control for the brands and the changed consumer behavior, also means more responsibility and effort. Due to the enormous availability of products through various channels for the consumer, the demand for dynamic and consumer-driven merchandise management is increasing. Classic systems such as 1-to-1 or static stock levels have not been able to keep up with consumer buying behavior for a long time. Due to the high degree of availability, the classic product life cycles have also changed. Jumpers in winter and T-shirts in summer - these are old-fashioned concepts and nowadays product life cycles are no longer easily assigned to these patterns. Likewise, with increased availability, products have grown in width and depth in recent years, which drastically increases the effort required for so many pieces. Traditional manual analysis by humans has long been unable to keep up with dynamic consumer behavior. Turn hours into seconds. This is where dynamic and intelligent solutions come into play that can autonomously analyze millions of information, decision-making processes, and external factors, to make automatic decisions for replenishment, next best offers, or price reductions. By analyzing each product and all options (style, color, size), in relation to the POS and all external information, the solution is able to make accurate decisions for further steps in the value chain. For example, the re-production of fast movers in a growing life cycle or a forecast for the ideal production quantity within the collection planning. For a successful D2C strategy, intelligent and dynamic merchandise management based on buying behavior is a must and gives the necessary control and speed to provide the optimal availability of the right products for all channels & POS. Find out how Chainbalance can optimize your entire merchandise management process.

More
Wholesale - a losing game? How brands are preparing for the new D2C strategy.

Wholesale - a losing game? How brands are preparing for the new D2C strategy.

S.Oliver, Adidas, Nike want to do what Dior and Bottega Veneta have been doing for years. Direct to consumer - from the classic wholesale model to direct sales! But why are more and more brands deciding on this strategy these days? Especially when you consider that many brands with their own stores have already taken this step. At the time, many retailers threatened to delist and were gleeful to see how difficult the brands found this step. The traditional retail structures with their multi-label department stores were not so easily pushed out of the playing field. Why a new attempt now? Here some reasons. One, of course, is the reaction to the market and its growing online sales channels (+16% in Germany & +20% in the Netherlands). Digitalization makes it possible and the pandemic has only accelerated the online growth channel! The brands have a real experience advantage over the established multi-label retailers. In addition, the online shop promises the desired independence that has been missing in decentralized wholesale for many years. And today's marketplaces create an enormous reach that could never be achieved in offline shops in this way. Moreover, many brands have realized one thing through the pandemic and the continuing staggering losses. Many wholesale addresses will no longer exist in the future! The tectonic shift of the wholesale business. Does this now mean the end of the wholesale business? No. D2C will also drive the re-evolution of the classic wholesale business. Responsibilities, Risks, and controls will be more carefully shared between the retailer and the brands - not a classic wholesale or concession model. The retailers become marketplaces that inspire customers and guests with outreach, atmosphere, and emotion. The brands take over the entire merchandise management at the POS. Of course, this also means more risk for the brands, but also more control and the use of the missing retail know-how. Digitalization is advancing. An optimal D2C strategy, with the new responsibilities in merchandise control for the brands and the changed consumer behavior, also means more responsibility and effort. Due to the enormous availability of products through various channels for the consumer, the demand for dynamic and consumer-driven merchandise management is increasing. Classic systems such as 1-to-1 or static stock levels have not been able to keep up with consumer buying behavior for a long time. Due to the high degree of availability, the classic product life cycles have also changed. Jumpers in winter and T-shirts in summer - these are old-fashioned concepts and nowadays product life cycles are no longer easily assigned to these patterns. Likewise, with increased availability, products have grown in width and depth in recent years, which drastically increases the effort required for so many pieces. Traditional manual analysis by humans has long been unable to keep up with dynamic consumer behavior. Turn hours into seconds. This is where dynamic and intelligent solutions come into play that can autonomously analyze millions of information, decision-making processes, and external factors, to make automatic decisions for replenishment, next best offers, or price reductions. By analyzing each product and all options (style, color, size), in relation to the POS and all external information, the solution is able to make accurate decisions for further steps in the value chain. For example, the re-production of fast movers in a growing life cycle or a forecast for the ideal production quantity within the collection planning. For a successful D2C strategy, intelligent and dynamic merchandise management based on buying behavior is a must and gives the necessary control and speed to provide the optimal availability of the right products for all channels & POS. Find out how Chainbalance can optimize your entire merchandise management process.

More
Wholesale - a losing game? How brands are preparing for the new D2C strategy.

Wholesale - a losing game? How brands are preparing for the new D2C strategy.

S.Oliver, Adidas, Nike want to do what Dior and Bottega Veneta have been doing for years. Direct to consumer - from the classic wholesale model to direct sales! But why are more and more brands deciding on this strategy these days? Especially when you consider that many brands with their own stores have already taken this step. At the time, many retailers threatened to delist and were gleeful to see how difficult the brands found this step. The traditional retail structures with their multi-label department stores were not so easily pushed out of the playing field. Why a new attempt now? Here some reasons. One, of course, is the reaction to the market and its growing online sales channels (+16% in Germany & +20% in the Netherlands). Digitalization makes it possible and the pandemic has only accelerated the online growth channel! The brands have a real experience advantage over the established multi-label retailers. In addition, the online shop promises the desired independence that has been missing in decentralized wholesale for many years. And today's marketplaces create an enormous reach that could never be achieved in offline shops in this way. Moreover, many brands have realized one thing through the pandemic and the continuing staggering losses. Many wholesale addresses will no longer exist in the future! The tectonic shift of the wholesale business. Does this now mean the end of the wholesale business? No. D2C will also drive the re-evolution of the classic wholesale business. Responsibilities, Risks, and controls will be more carefully shared between the retailer and the brands - not a classic wholesale or concession model. The retailers become marketplaces that inspire customers and guests with outreach, atmosphere, and emotion. The brands take over the entire merchandise management at the POS. Of course, this also means more risk for the brands, but also more control and the use of the missing retail know-how. Digitalization is advancing. An optimal D2C strategy, with the new responsibilities in merchandise control for the brands and the changed consumer behavior, also means more responsibility and effort. Due to the enormous availability of products through various channels for the consumer, the demand for dynamic and consumer-driven merchandise management is increasing. Classic systems such as 1-to-1 or static stock levels have not been able to keep up with consumer buying behavior for a long time. Due to the high degree of availability, the classic product life cycles have also changed. Jumpers in winter and T-shirts in summer - these are old-fashioned concepts and nowadays product life cycles are no longer easily assigned to these patterns. Likewise, with increased availability, products have grown in width and depth in recent years, which drastically increases the effort required for so many pieces. Traditional manual analysis by humans has long been unable to keep up with dynamic consumer behavior. Turn hours into seconds. This is where dynamic and intelligent solutions come into play that can autonomously analyze millions of information, decision-making processes, and external factors, to make automatic decisions for replenishment, next best offers, or price reductions. By analyzing each product and all options (style, color, size), in relation to the POS and all external information, the solution is able to make accurate decisions for further steps in the value chain. For example, the re-production of fast movers in a growing life cycle or a forecast for the ideal production quantity within the collection planning. For a successful D2C strategy, intelligent and dynamic merchandise management based on buying behavior is a must and gives the necessary control and speed to provide the optimal availability of the right products for all channels & POS. Find out how Chainbalance can optimize your entire merchandise management process.

More