This month, we hosted a Data Visualization webinar with bestselling author Cole Nussbaumer Knafflic. Cole wrote the popular book “Storytelling with Data” and is also known for her blog. She’s worked at and with some of the most data-driven companies on the planet, including Google, Adobe, Genentech, JPMC, Target, and the World Bank. She also works with organizations and individuals to help them become more effective data storytellers through workshops. We had a chance to talk to her about some best practices for effective data visualization leading up to the webinar. In this short interview, she shares some of her trade secrets and a sneak preview of what you can find in her book.
- How do you define storytelling with data?
For me, storytelling with data is the communication step of the analytical process. Let’s consider the analytical process. Perhaps you start off with a question or hypothesis. Then you have to gather the data and clean the data. Next, you analyze the data. At that point, it’s easy to throw it into a graph and be done. But that graph is the only part of the whole process that your audience sees. So it deserves at least as much—perhaps more—attention compared to the other parts of the process, and yet is so often overlooked or given the least amount of time. To take that a step further, my view is that you should never simply show data. Rather, you should make data a pivotal point in an overarching story or narrative. This helps it make sense to your audience, makes it resonate and can help make it stick. This is storytelling with data.
In a time when the term ‘disruptive’ is being over-used I find myself increasingly using the term when describing the impact of our product to clients and prospects.
It’s uncomfortable because prior to starting with AIMMS two years ago, I spent 20 years in consulting and IT services and experienced many terms being over-used (such as ‘optimized’ or ‘disruptive’). I promised myself that I’d endeavor to never use a meaningful term in a superficial way.
The Brexit is a reality and with it, companies in Europe are facing even more uncertainty than before. There is serious concern that the UK’s decision to leave the EU will bring further destabilization and economic risks. How will it impact your supply chain and your bottom line? This article discusses 5 key things supply chain leaders should consider post-Brexit. It also explains how analytics can help you determine the best way forward. Specifically, I will explore how Prescriptive Analytics can help you improve decision-making and make data actionable in an increasingly volatile economic landscape, instead of only providing insight into your data’s behavior.
Last week, part of our EMEA team (Christophe, Marcel and Kim) attended the Supply Chain & Logistics Summit as a sponsor for the fifth consecutive time. The conference took place in Barcelona. The overall theme of the Summit was the Value Chain and How to Build the Competitive Supply Chain of the Future. This main topic was covered throughout the whole program. Sessions addressed subjects like:
- Enhancing Competitiveness Through Technology
- Supply Planning & Optimization
- Harnessing Logistics to Satisfy Customers
- Leveraging the Global Economy
My takeaways from Gartner’s Supply Chain Executive Conference 2016
Apps have come to define the way we work and live in many ways. We have cars with Apps, watches running Apps, TVs that operate with Apps…as the phrase goes “There’s an App for That.” There are Apps out there for just about anything, it’s hard to imagine a world without them. Why do we love Apps so much? We get the information we need upfront, they can be used anytime, anywhere, they help us connect, and they serve a specific purpose.
When it comes to Supply Chain Analytics, an “Apps approach” can have just as many benefits. Gartner’s Noha Tohamy offered a great presentation about this at their recent Supply Chain Executive Conference. But what exactly is a Supply Chain Analytics app? Noha defines it as “a solution developed in-house or by a service provider, targeted at a specific use case.” By taking an Apps approach, companies can build an app library with solutions. Think for instance of a Source Optimization app for your retail company – a custom solution that helps you understand how and when to source your supplies, foresee possible supplier issues and adapt your plans accordingly. Another example, this time in the oil industry, would be an oil blending app. Oil blending is not easy. Blending rules are always in development and are considered to be extremely proprietary. A custom Optimization or Prescriptive Analytics app can be adapted quickly as the rules change, it can empower people in your organization, be readily accessible for end users and help you create better blends.
It comes as no surprise that business and supply chain leaders are seeking new approaches to get ahead in the analytics age. Implementing an analytics strategy, and in particular implementing prescriptive analytics, can significantly improve revenues and drive down costs. How can you ensure that your team is prepared to embrace these new technologies and approaches? Experience shows us that technology is the easy part. Getting buy-in agreement and changing your company culture to embrace analytics is often more difficult. A Center of Excellence (COE) can help you start off with the right team structure, engage the right stakeholders and put you on the right path to implementation.
It’s no mystery that some of the world’s largest retail chains are struggling to survive. Walmart is closing a record number of stores (269) in the U.S. and abroad this year. Trusted names like Sears, J.C. Penney, and Gap have also lost their momentum. In Europe, V&D, a major Dutch department store, and Brantano, a large footwear retailer operating in the Netherlands, Belgium and the UK, have officially declared bankruptcy. Demand is sluggish and many have failed to adapt and streamline shopping experiences for today’s connected consumer. Still, even in the midst of this turmoil, retailers like Kroger and Zalando are thriving. What are these companies doing differently and what trends should retailers look out for? Let’s take a closer look.
Big data, analytics, BI…Everyone in business today has heard these terms at some point, and yet the path to analytics-driven business improvement remains somewhat elusive. We spoke with Keith B. Carter, Actionable Intelligence Expert and Decision Sciences Visiting Senior Fellow at the National University of Singapore Business School and Affiliate Professor Business Analytics Center, to unravel some of the difficulties managers face while embracing an analytics culture and discuss some best practices for success.
Keith is a global supply chain operations leader with over 16 years of extensive global experience in the Cosmetics-Beauty, Government, and Financial Services industries. He has managed teams across continents – from the United States to Belgium and Singapore. Previously, he worked at Estée Lauder in a variety of global supply chain roles, and Accenture in financial services and government. His book. Actionable Intelligence: A Guide to Delivering Business Results with Big Data Fast!, provides expert guidance to establish a culture of fact-based decision making and appropriate high-speed governance.
Through the Hype Cycle: Exploring the Many Applications of AIMMS Technology in Supply Chain Planning
As you may have heard, AIMMS was recently featured in Gartner’s Hype Cycle for Supply Chain Planning (SCP). The Hype Cycle is a great resource for Supply Chain and IT leaders. It offers an overview of the enormous breadth of solutions for Supply Chain planning, giving you insight into the many fields where you can leverage technology to boost your company’s performance. It also helps you understand which technologies and applications have gone through their teething cycle, which ones are already mature, and ultimately, which one would be right for you. In the document, Gartner positions AIMMS as a key vendor in Prescriptive Analytics – a form of Advanced Analytics that can improve decision making in several areas of the supply chain, including logistics, planning, and manufacturing. But you can apply AIMMS to many other areas as well. I will explore some of those areas in this post.
2015 was a very exciting year for AIMMS. We welcomed many new customers, resulting in a 40% increase in revenue growth. We also grew as a team and have expanded to a new office in The Netherlands. I’m happy to say that 2016 looks even more promising! We are witnessing a growing interest in prescriptive analytics across a wide variety of industries. The use of AIMMS PRO specifically is increasing, as companies are realizing the huge benefits of providing their staff with decision support tools. In this blog post, I will share some exciting new use cases, a quick glimpse of our product and customer service goals, and a short update about AIMMS partnerships.