.png){kind=logo}
- Insights
- Cryptocurrencies
- Stocks
- White Papers
- Industry
- Geography
- Insights
- Cryptocurrencies
- Stocks
- White Papers
- Industry
- Geography
If starting a business is one challenge, being on the toes in the ever-changing digital landscape, is quite another. Most companies struggle with innovation in terms of adapting themselves to new technologies as well as product innovation. Kalypso belongs to the rare breed of companies, that thrive on innovation and informed opinions to help enterprises overcome the hurdles in digital transformation. Drew Cekada is a digital transformation consultant who leads transformational programs beside senior product leaders inside some of the world's most notable brands. He is a Senior Manager in Kalypso's Consumer Industry Practice, a leader of the Retail, Footwear, and Apparel (RFA) team, and the founder of the RFA Advanced Analytics unit. Analytics Insight has engaged in an exclusive interview with Drew Cekada, Senior Manager- Digital Transformation Consulting, Kalypso.
Kalypso is the digital services arm of Rockwell Automation, and our global team of 600+ client service professionals helps clients discover, create, make and sell better products with digital solutions. Our digital transformation services span consulting, data science, technology, and managed services which we combine with deep expertise and thought leadership in the industries we serve.
Within the retail, footwear, and apparel (RFA) sector, our team serves a global portfolio of clients whose transformation initiatives are creating competitive advantages by tying together digital innovation strategies, operational excellence, and foundational product technologies, like product lifecycle management (PLM), and the latest in digital product creation (DPC) capabilities to virtualize, automate and analyze products and consumers across the entire product lifecycle, which we refer to as "the Digital Thread."
Since 2004 Kalypso has had a proven record for transforming our clients' product engines and helping them achieve extraordinary results through growth, innovation, optimization, and resilience. Now as part of Rockwell, a leader in the supply chain, manufacturing, and automation space, we've multiplied our global team, extended the breadth of our services, and built an unparalleled data science capability to harness the power of advanced analytics and fundamentally rethink the way products are brought to market. This unique combination of our exclusive focus on product, our comprehensive capabilities across the end-to-end digital thread, and our informed cross-industry points of view, truly make Kalypso a market of one.
When deploying any new capability, our clients will naturally face a variety of technological, operational, and people challenges. And although technological and operational hurdles can slow progress, our clients' most persistent challenge is overcoming the resistance to change. Leaders and teams must begin to think differently about how they integrate analytics into their daily work. Here are a few common ways teams get caught up:
Mistaking Retrospective Dashboards for Advanced Analytics: If your people rely on backward-looking, descriptive dashboards instead of forward-looking, predictive, and prescriptive insights, there's tremendous untapped potential in your organization's data.
Fear of Replacing Human Intuition with Machines: If your people, leaders, and teams are fearful advanced analytics will cause them to lose autonomy and decision-making power, they misunderstand that advanced analytics is actually about augmenting humans with never-seen-before insights and predictions to help them make more confident decisions, more quickly than ever.
Confusion & Mistrust Around Insights: If your people are being asked to blindly follow the insights of an algorithm they do not understand and a data source they cannot see, your program will be plagued with mistrust. Instead, drop the black box and adopt a mantra of radical transparency and overcommunication until the results begin to speak for themselves.
Unguided Insights Drive Inaction: If your people are being fed insights without clarity on how those insights should be operationalized to improve their work and decision-making, even the most elegant technological solution, the cleanest data, and the most brilliant use of cutting-edge data science will fail to transform your business results.
Kalypso's team of data scientists and analytics translators have worked with clients to amass a library of more than 100 use cases spanning the four phases of the product lifecycle (discover, create, make, and sell); each proven to deliver real business value in the form of top-line growth, bottom-line profitability, workforce productivity, operational efficiency or risk reduction. Among those use cases are three that have had near-universal appeal to our clients:
Line Plan Optimization & Assortment: Clients are using machine learning models on historical performance data and macro-trends to automate the creation of line plans that are optimized to deliver category growth goals and leverage these models, along with product data, to prescribe multiple assortment options by channel, level, and flow.
BOM Advisor: Clients are leveraging AI-powered workforce advisors, embedded directly into PLM, to sense and correct errors and anomalies in the product record, to recommend substitute materials or components to improve economies of scale across your seasonal assortment, or to provide machine-learning-powered auto-complete suggestions that radically reduce time spent by teams on administrative duties.
Returns Analysis: Clients are deploying natural language processing capabilities to scrub return codes, comments, and call-center notes to provide product teams with distilled and directive product feedback directly from the voice of the consumer. Teams are using these automated capabilities to intervene immediately to resolve bulk production issues and to improve future product designs in subsequent seasons.
Kalypso advocates a value-first, scale-second approach to advanced analytics; one that provides a near-immediate payback for a single high-impact use case using existing data sets to address practical challenges in the business. Then, once the value is proven, a self-funding "analytics factory" can emerge with a backlog of the next-highest value analytics use cases and the ability to assemble, develop, deploy and operationalize them across the organization. As a result, the notion of increasing net cost is entirely counter to how we approach things.
Our clients have historically focused on creating analytics dashboards that are retrospective in nature. They look backward to describe something that already happened within the organization or, at best, to diagnose why that thing occurred. That sort of capability is useful but insufficient in a digital age where the inhuman scale of real-time data is growing exponentially and the immense power of artificial intelligence and machine learning is readily accessible. Today, our leading clients are using advanced analytics capabilities and interwoven networks of data across their entire value chain to create competitive advantages through foresight and prediction of what is going to happen before it does. These clients are automating the errors out of their processes, predicting consumer preference, generating high-value product designs, automating production triggers, and accelerating operational throughput and speed to market; all levers for profitability and growth in a volatile global market.
For decades the consumer industries, including our clients in RFA, have led the world in using analytics for marketing and communications and have seen how these predictive and prescriptive capabilities have transformed their businesses and accelerated growth. However, until recently, our industry has lagged behind others in the use of advanced analytics for product creation. But no more…
Today, the world we once knew as PLM, is rapidly evolving into product lifecycle intelligence (PLI) and leading apparel and footwear brands are investing in building data science teams and analytics translators focused on solving real product-related problems for the business. These teams use advanced analytics and vast quantities of product data, manufacturing data, sales, and returns data, and customer data to create better products, more efficiently, and with less risk than ever, and can operationalize these solutions in weeks and months, not months and years.
With this level of investment growth, the rapid speed-to-value, and the competitive advantages many of our clients are experiencing, if your organization is not actively building these capabilities, you're being left in the analog age.
