the Closed Loop portfolio in analytics

We talked about the overwhelming power of analytics in Retail and B2C market-segments earlier and one of the topics discussed there, was the integration of operational business activities with operational analytics. In the example we saw the stock manager using analytics to change his stock-buying-behavior. He adjusted his order system by choosing another vendor and placing the order. Immediately his analytics are updated and he now requires to adjust his rolling planning or run a predictive simulation how the price-adjustment of his new stock might affect buying behavior of his customers. He might even want to adjust the governance rules with his new supplier or run a risk-assessment. Below

The overwhelming power of analytics in retailing: Part 1

Online grocery shopping, personalized bonus-card ….. We all face these initiatives day to day. They are all very strongly driven by overwhelming analytics power behind them. This article is to share my experiences on them with you and what I learned from it. These are just examples of retailing and B2C customer journeys that I am part of. The below examples are not exhaustive at all; they are also not future but happen and are in production today! One of the things that make the retailing market segment so interesting, is that it is extremely sensitive to community influences. Just a small thing might happen in society, and it immediately affects buying behavior: people are connected everywh

Business users still not drive business analytics deployments

Let us make no mistake: technology and architecture need to be heavily involved in deploying analytical platforms. If they aren’t we will quickly face issues on scalability, governance or even operational risks. But if they are involved properly, the sole drive of a business analytics platform is definitely adoption. So, why is adoption-rate the key driver for having business involved in your business analytics deployments? Well they are our biggest “customers”, aren’t they? If the analytics provided does not have the content, functionality and accuracy that the users require to run their business, they simply won’t use it. They would go and find their own trusted sources to get the insight

An analytical perspective on how insights change the game for CFO's

Have you noticed this video on Financial Excellence? Have you really listened to what CFO’s and the Office of Finance mention as their biggest challenges? You should, since it is a very interesting discussion! The top 3 biggest challenges CFO’s and the Office of Finance see for 2016 are: Given that business has changed by the Digital Transformation, how can they leverage this transformation? How can they make use of the “new data” they have access too? How can they execute on their new roles as business and strategic advisors How to develop talent in their finance organization In this article I focus on the first two challenges. Not that developing talent for the financial organizations is l

Pareto analysis and the 80/20 rule in self-service business intelligence

Quite often we will use Pareto analyses to quickly isolate or highlight the elements that matter. Though never scientifically proofed, Pareto refers to the 80-20 rules described as 20% of the causes determine 80% of the problems. In practice it has been a very efficient way of quickly analyzing and judging data. At the end of this article is an instruction video showing you how to create the pareto analyses I will guide you through the simple but strict process of creating a Pareto analysis with self-service business intelligence. Especially the cumulative sum function and the "% cumulative sum of total" are you key handles here. Pareto analysis is a formal technique useful where many possib

Manipulating and enriching data with analytics

Self-service business intelligence is about interactive analytics and using a highly visualized way of getting insights. However it is also about preparing and enriching your data. The Digital Transformation brings data from everywhere in any possible structure or format. If end users want to analyze this data they need to be able to quickly access and integrate it with their existing data. Very probably they require to enrich the new data. Enrichment of data covers a wide variety of data crunching going from creating calculations and aggregation types, into hierarchies and custom groupings. Data enrichment is also about joining different data sets or – to a limited extend – cleansing data.

Let me compare: Analytics and Data Science - each their own unique characteristics

Business analytics and data science are related disciplines since they both focus on analyzing and exploring data in search for business insights. To do so data science often uses predictive analytics tooling to deploy algorithms or search for patterns and correlations, whereas business analytics more uses those algorithms. In a previous article we spoke about using both business analytics as predictive analytics techniques to get insights from data. But what is the difference between these disciplines? Where is the one taking over from the other, and where do they overlap? Various definitions are being used and people still debate on the boundaries of both disciplines, but the definitions m

Analytics: your core competitive weapon in 2016

Did you also read Forrester’s predictions 2016 for business? Analytics is clearly indicated as core competitive weapon to be successful and win your business. Forrester emphasizes correctly that analytics should be on the top of any CXO’s agenda in 2016. I cannot agree more. So let’s discuss why this is so important? Big data in 2015 took its momentum we had foreseen already. Those Big data initiatives gave us a broader range of data. A range that brings additional data from two directions: First, we have access to more levels of details. In-memory computing allows for immediate access to archived data which is now available for analytics. In-memory also allows to present the full level of

Let Me Guide Series: creating stunning layouts and navigations in SAP lumira

In this “let me guide you series”, we focus on how to compose your story-board using the best layout and navigation practices in case your user wants a KPI Metrics storyboard. These KPI Metrics storyboards are meant to display key metrics and their trends. The series assumes your data preparation and majority of visualizations is ready; we now learn how to all add this in a stunning lay-out and using proper navigations paths. The accompanying instruction video clearly shows where to focus on. It also provides some simple tips and tricks that make life easy for you. Below is a step-by-step guide in composing your storyboards. In the example I use SAP Lumira to create my boards. Step by Step P

Let the expert speak: Prof. Dr. Rolf Hithert explaining visualization standards

This week SAP organized a web event on data visualization standards. Special guest was Prof. Dr. Rolf Hichert who is an authority on standards for visualizations applying his SUCCES formula. I have written about his standards which are now being adopted by IBCS. The event was a real eye-opener with some very nice examples of best practices that you can implement right away. By comparing bad- and good ways of visualizing data, Prof. Dr. Hichert really came to the point. Especially the combined absolute and relative variance charts showed how easy it is to make mistakes. Also watch the way he stresses correct use of scaling: I think any of us made the obvious mistake of plotting multiple chart

It's now or never: the use case for in-memory platforms for Business Analytics

Somewhere in another article I read about “Information being the new global currency”. With today’s Digital Transformation and all that she is taking in her wake like IoT or BigData, information insight is an even more necessity than it has ever been. Structured and unstructured data coming in massively to all of us; us, who act in new markets in a networked economy. Insights are today the heartbeat of a company’s success; or new currency, end of the line. Any place and any moment we require to interact with business analytics searching for new and better insights. To deliver on our requirements, we cannot do without in-memory platforms with dazzling performance and capabilities. It is now

Let Me Guide: Standards and Consistency, some of the Hichert principles I use

In this section of the Let Me Guide series I want to talk about standards and consistency in your dashboards, storyboards and infographics. Standards and consistency are of utmost use for both internal as external communications: Understandability of your boards increases Decreased risk of misinterpretation of your boards Increase of recognition and familiarity to your boards In this article I discuss some of the most impacting Hichert principles I use every time in my boards. IBCS AND HICHERT GUIDELINES Hichert Faisst defined a set of rules and guidelines compliant to the IBCS standard. These guidelines are more than a starting point for you to ensure consistency and clarity; they act as fr

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