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Episode 22: A Practical Approach to Innovation in Analytics

Guest: Andreas Kugelmeier, IBM

Innovation is much easier to talk about than to do in practice. Challenges include getting buy-in from groups you depend on but have little leverage over, and resisting the urge to go for a BIG vision. In this episode, Andreas Kugelmeier from the IBM Data and AI Labs, talks about the concept of a Business Analytics Innovation Loop as a practical, low-risk and high-reward approach to effecting innovation. The concept has strong parallels with the notion of agile software development, in which progress is made through a sequence of incremental but valuable steps. In Business Analytics there is an added advantage to taking an incremental approach because each steps brings new insights and understanding to light, which can inform and change subsequent steps for the better!

Andreas uses an extensive example from Financial Planning and Analysis (FP&A) in banking to illustrate his point, and makes an important point about the roles of culture and business process versus software tools in driving innovation and change. This episode is sponsored by QueBIT, trusted experts in analytics.  

Episode 21: Everything you always wanted to know about Testing

Guest: Jim Brinnen

When implementing a new analytics system, testing is sometimes treated as a “nice-to-have” rather than a core requirement. While no one says up-front that testing is a low priority, it is not unusual for there to be inadequate dollars, time and planning set aside for testing. While this is true for any software application implementation, it may be particularly true in analytics because analytics projects are often initiated and owned by the Line of Business, rather than IT. This is a good thing because the Business recognizes business value when it sees it (and can thus be a very engaged partner), but issues may arise because the Business typically has limited experience in implementing software systems. At the beginning of the project, the challenges of acquiring data and defining requirements can be overwhelming. It is normal to go through a process of learning that leads to changed expectations and modified scope. Since analytics tools are pitched as business friendly and easy to use, this often leads to pressure to shift consulting costs away from testing towards expanded scope under the assumption that the customer will, by then, have learned enough about the system to take care of testing it themselves.

In this episode, QueBIT’s Customer Success and Solution Delivery leader Jim Brinnen explains all the different kinds of testing needed along with what must be taken into account in each case to be successful. If you are new to testing, you will be surprised at how much there is to consider!

Episode 20: Data Virtualization

Guest: Keith Hollen

Data Virtualization technologies can be used in a number of different ways, including real-time operational reporting and analytics against multiple source systems, and quick-and-dirty data exploration! As business users increasingly expect to have direct access to data for self-service analytics, data virtualization can be an effective way to make that possible.

In this episode, QueBIT Data Expert Keith Hollen explains what data virtualization is, and how it fits into the pantheon of data management tools and strategies. While not a replacement for a true data warehouse, it can be a viable alternative to an Operational Data Store to enable analytics and reporting. Keith ends with Good and Bad Use Case examples to help explain when data virtualization may be valuable, and when it likely will not be.

Episode 19: Lean Demand Forecasting

Guest: Dan Barrett

Dan Barrett, QueBIT’s Advanced Analytics Technical Sales Manager, claims that MOST companies waste far too much time on demand forecasting!

Considering how crucial an accurate demand forecast is to planning your supply chain, this is a bold statement. Keep in mind that Dan is NOT saying that you don’t need a demand forecast: of course you do! The problem he wants to address is accuracy, and his point is that more people spending more time on it does not typically result in a commensurate increase in accuracy.

In this episode, Dan explains what he means by Lean Demand Forecasting, and how measuring a metric called Forecast Value Add that compares your forecast to actuals on a continuous basis is an important tool for real forecast accuracy improvement. We compare different approaches to demand forecasting, including when a naïve approach is good enough, and when building a predictive model becomes valuable.

Episode 18: The Evolution of Business Intelligence

Guest: Robin Wilkinson

It turns out that Business Intelligence (BI), as a concept, has been around since 1865! Back then it was a manual paper and pencil process, but it still enabled one business to prevail over its competitors by making better data driven decisions. Today we are dealing with massive amounts of data, technology has evolved tremendously, and people have evolved too!

In this episode Robin Wilkinson, who is the General Manager of QueBIT’s Business Intelligence and Data Management practice, gives us a BI history lesson and takes us through how the process of implementing and deploying BI has evolved though the years. The conversation includes some great specific examples, and lots of great best practice advice for BI success. Among many other things, Robin points out that today everyone wants results quickly, so the focus needs to be one delivering BI solutions in days or weeks, not months or years.

Episode 17: Analytics for Retail Buyers

Guest: Jim Hanifin

As on-line shopping becomes the norm, the traditional retail industry is going through a lot of adjustments. Employing analytics technology to increase operational efficiency and make better decisions faster is an obvious avenue to take.

In this episode we speak with Jim Hanifin who recounts the journey at a retail customer he worked with recently. We go into detail about how their retail buyers transitioned from a weekly paper-based analysis and planning system, to an on-line dashboard that put the data at their fingertips in real time. If

you have ever wondered how retailers get the products you want to buy into stores, you should find this peek under the covers interesting!

This episode is brought to you by QueBIT.

Episode 16: How to become an Analytics Expert

Guests: Daniel Williams, Odile Davis Wolfe, Pete Horgan

QueBIT has grown by cross-training business and finance people in analytics technology, and by cross-training engineers and computer scientists in business and finance. Meanwhile analytics experts such as data scientists are at a premium in the marketplace, and many finance and business leaders are recognizing the need for their business and financial analysts to develop more technical skills, so as to be able to service growing demands for data and insights in support of better decision making! Specifically, there is a trend towards the finance function expanding beyond responsibility for financial reporting, financial planning and analysis into a new world that encompasses data and analytics strategy for the entire organization!

In this week’s episode, we put these two things together: perhaps QueBIT’s experience in developing these skill sets will be of use to organizations that are moving in this direction? We’ll hear from a panel of QueBIT consultants who are relative newcomers to analytics, so listeners can learn from their experiences.

Episode 16: Planning a Global Insurance Merger with Analytics

Guest: Chris Appel

Insurance is a complicated business. It is so complicated that it has spawned an entire profession – the actuarial profession – to compile and analyze statistics to calculate insurance risks and premiums. An insurance company cannot operate successfully over the long term without using analytics to plan its operations.

Consider then a merger of two large global insurance companies: what does it take to get a unified of the entire business, or to do analyses of different insurance products (Life, Property & Casualty etc) across varied geographies, regulatory environments and cultures?

In this episode Chris Appel tells us about how one such global insurance company is tackling this problem. We have a great conversation about some of the challenges, and the approaches that were taken to overcome them. Here’s a bonus: Some of the discussion is applicable to a global merger in any industry – not just insurance!

This episode is sponsored by QueBIT, "Trusted Experts in Analytics".

Episode 15: A Financial Consolidation is an Analytics project!

Financial Analytics is an important branch of the field of Analytics. It involves data management, modeling and reporting. A Financial Consolidation system is a Financial Analytics project that brings together data from one or more ERP (Enterprise Resource Planning) system together with a financial model with the purpose of producing consolidated financial reports. Not only are these obligatory for regulatory reporting, but they can also be a strategic asset. Shorter month-end closing cycles, coupled with detailed product/segment/regional/entity/etc reporting made available quickly, to front line managers WITH the ability to drill down for more detail in an intuitive and interactive manner … can all translate into business value.

In this episode we tell the story of how a real QueBIT customer moved beyond Excel spreadsheets and implemented a robust enterprise financial consolidation system using a combination of a relational data art and a special purpose multi-dimensional database technology. Along the way, we cover some of the fun stuff that needs to be considered on a journey like this, and hopefully convince you that it is worth the effort!

Episode 14: Nerding out on FP&A!

Guest: Beth Thomas

The Financial Planning & Analysis (FP&A) function is the original analytics function within any organization. The Profit & Loss (P&L), Balance Sheet and other financial statements tell the story of the business. When they are correct, timely, and reach the right audience, they are invaluable for identifying problems and driving informed decision-making.

This week, Beth Thomas who is the General Manager of QueBIT’s Financial and Operational Performance Management business, and a former Manager of FP&A herself, shares her insights and experiences. She talks about why she finds FP&A so interesting, and how it is time to transcend Excel’s limitations by enhancing (NOT replacing) it with modern data management and modeling tools. Financial Analysts should be spending their time doing analysis and adding value to the business instead of being bogged down in mundane data collection and manipulation activities! The podcast ends with some solid, practical advice on how to reduce the risk of financial reporting errors while increasing the quality and timeliness of the information used to run the business.