Ask Quebit About Analytics

Episode 42: Launching a Diversity and Inclusion Program Guests: Andrew Chavis, Dallas Crawford, Odile Davis-Wolfe & Gus Slaughter In Episode 39 we talked about how companies that have inclusive cultures and embrace diversity also end up with real business advantages. These are a consequence of attracting the best talent, and then creating the conditions for that talent to meet their potential. Other positive impacts are increases in employee engagement, morale and loyalty. The “right thing” from an equity and justice point of view, turns out to be the right thing for business success as well. Today’s Ask QueBIT podcast takes a brief detour away from analytics and technology to explore QueBIT’s own efforts to address these important questions. Our guests are the architects of QueBIT’s Diversity and Inclusion Program, affectionately known as the QueDIP Committee. In this episode we take an honest look inward, and touch on some of the very difficult questions that cause people of sincerely good intent to hol

Episode 41: From “spreadsheet hell” to better decisions at Eversource Guest: Fran Berger As the largest utility in New England, Eversource has all the planning and reporting needs one would expect of a Fortune 500 company – and maybe more! Operating in a highly regulated and unionized industry while also a public company, not to mention occasional acquisitions and mergers, leads to some unique challenges. According to Fran Berger who manages performance and financial systems at Eversource, the decision to invest in IBM’s Planning Analytics technology platform (then called TM1) thirteen years ago was prescient and far-sighted (though they may not have realized it at the time!) The first corporate budgeting application built on this platform involved only a small handful of finance users, but once the capabilities of the technology were established, adoption grew. And grew. Today hundreds of users in finance and operations interact with the system every day, benefiting from secure self-service access to the dat

Episode 40: Why Master Data Management Matters Guest: Clare Hutton Our clients often ask us whether we “do” Master Data Management (MDM). It’s a good question because Master Data Management is important to DO, but answering the question can feel a bit like tip-toeing through a minefield. This is because the term “Master Data Management” means different things to different people. QueBIT’s answer may be “yes” or “no” depending on what you are thinking of. This is why, when QueBIT launched its internal Guilds initiative in 2019 as a way to build community through having cross-functional teams explore and “go deep” on different topics that interested them, we selected Master Data Management as a guild topic. The goal was to drill down past the jargon, the hype put out by “MDM” software vendors and QueBIT’s own experiences, to understand the essential business problem that MDM purports to solve. In this episode QueBIT Master Consultant Clare Hutton, who led the guild, shares the guild’s findings, including clear,

Episode 39: Diversity, Inclusion … and Transformative Analytics No guest This episode was partly inspired by an article in the November-December 2020 issue of the Harvard Business Review titled “Getting Serious about Diversity: Enough Already with the Business Case”. The point of the article is that harnessing diversity to add value to your business is not just about hiring more women and black people to check a box, but about HOW willing you are to reshape your power structure to harness that diversity. In QueBIT’s 20+ year history of delivering successful analytics-based projects to hundreds of companies we have lived through countless case studies that support the position taken in the article. Projects rarely succeed or fail just because of technology selection. The biggest factors that drive success pertain to leadership and culture: Do team members trust each other? Are they engaged, or just going through the motions? Do they feel supported by their executives, or set up for failure? These are big quest

Episode 38: You can’t have Agile Planning without Building Models Guest: Richard Creeth Most businesses rely on spreadsheets as a tool to inform, and to drive decision-making. Often these spreadsheets contain models where certain inputs drive calculations to produce outputs. Examples of common calculations include [Units] * [Price] or sales projections. Because spreadsheets are so ubiquitous, easy and (sometimes) FUN to build models in, they tend to proliferate across businesses, like weeds. This is where well-known limitations around controls, auditability, scalability, collaboration and accuracy begin to dilute the benefits of using them. And yet – a business cannot succeed without these models. In this episode Richard Creeth who is a physicist-turned-UK Chartered Accountant talks about the art and science of modeling a business, why it is indispensable, and how to transcend the limitations of spreadsheets to take full advantage of all that technology has to offer, including Artificial Intelligence (AI) pow

Episode 37: Learning about Splunk Guest: Jim Miller It’s not easy keeping up with technology but one of QueBIT’s Master Consultants, Jim Miller, has found a neat way to do it: he writes technology books in his free time! Jim’s latest book, which will be available at the end of the month, is called Mastering Splunk 8. In this episode Jim gives us a short introduction to what Splunk is, illustrated with real-life examples of how to put it to use. Then he takes us through his process for producing a book starting with inspiration and topic selection, all the way to technical research, writing and publishing. If you find yourself curious to learn more about Splunk, you can order Mastering Splunk 8 on Amazon.com, and while you are there check out other books by Jim.

Episode 36: Analytics Shorts: 3 Stories Guests: Christine Schoenen, Dan Viterise, Jim Miller This week we are showcasing three of QueBIT’s expert consultants: Christine Schoenen, Dan Viterise and Jim Miller. They have so many great stores to tell, but very little spare time, so we came up with this idea of the three-minute-story. Tell us about a favorite project in about three minutes by recording it on your own phone, whenever you have a moment! It’s a fun format, and you get to hear about a property manager in the hospitality industry, a global insurance company and a heavy equipment rental business … all in under 15 minutes! Each of these companies had a different planning and analysis business problem that they solved using analytics technology and a little help from QueBIT. We hope these examples help you imagine the value analytics technology can bring. It goes far beyond merely saving time, reducing manual effort and better governance, important as these all are. What we strive for is to help compani

Guest: Gary Quirke  What do “cash forecasting” and “looking out for bears” have in common? Both these activities have existential consequences. The damage a bear can cause is obviously terrifying to think of, but if your company runs out of cash and you lose your job as a result it can be quite frightening too. A company with a good model-driven cash forecasting process can anticipate cash problems far enough in advance to take mitigation steps, for example to delay payments, renegotiate terms or cut costs. If its cash forecasting process is sufficiently detailed and supported by the right technology, a company will easily be able to consider a range of scenarios and prepare different plans ahead of time to be in the best possible position as reality plays out. Conversely, not having this capability is the equivalent of tripping over a bear cub with mama bear in sight. In this week’s podcast episode we interview QueBIT CEO and UK Chartered Accountant, Gary Quirke, who gives us a quick lesson in cash fore

Guest: AG Tan Planning, forecasting, reporting and analysis are core business activities served by analytics technology. Many companies are busily re-doing plans and forecasts in response to the 2020 COVID-19 pandemic, to figure out how to stay in business (when demand has plummeted) or how to maximize capacity (when demand has sky-rocketed). At the frontlines of all these efforts are financial analysts working in the corporate finance, treasury and operational planning functions. If they do a good job, better decisions are made, a company survives, jobs are saved, and the economic recovery is hastened. This is extremely important work that is poorly understood, and little appreciated, by those who don’t do it for a living. Especially poorly understood is the qualitative value of giving financial analysts the right tools to manage data, build models, collaborate and share information. Companies that understand this are flying supersonic jets in comparison with companies that don’t, which are doing the equival

Guests: Justin Croft and James Saronson When there is so much going on around you that you can’t do anything about, it is helpful to reflect on the things you can control. If your job involves business planning and forecasting, it’s about becoming more comfortable with uncertainty. This can be done by exploring a range of possible scenarios ahead of time, so that you are prepared to act regardless of which scenario plays out. There is nothing new in this concept: planners explore scenarios all the time. But the COVID-19 pandemic has drastically altered the context in which planning and forecasting takes place. Most of all, it has compressed the timeline and increased the frequency. Annual budgets and quarterly forecasts will not be any use. Companies need to look at their business assumptions by month, by week or even by day! Analytics technology to support planning and forecasting functions evolve from being a nice-to-have, to being indispensable. In this week’s podcast episode, Justin Croft and James Sarons

Episode 32: Embedding AI in FPA Replay Guest: AG Tan This episode is a replay of an in-person keynote presentation delivered at IBM’s offices in New York City in November 2019. The purpose of the talk was to demystify the value of Artificial Intelligence (AI) for planning and forecasting use cases in extended Planning and Analysis (xP&A = integrated financial and operational planning and analysis), and to provide practical advice on what it takes to get started. We explained the relationship between AI, Machine Learning and Predictive Analytics, and went on to provide a checklist of considerations to help prepare for a successful predictive demand planning initiative. This epsiode is sponsored by QueBIT.

Episode 31: Analytics in Uncertain Times: COVID-19 edition Guest: Gary Quirke QueBIT has clients from all industries, that range in size from smaller and mid-sized businesses to giant global companies. Surveying our client base is like looking at a microcosm of business in general, and so in this week’s podcast episode, we speak with QueBIT CEO Gary Quirke about how the COVID-19 pandemic is affecting our clients, and the ways in which analytics are helping them cope. Uncertainty is always present in business, but the pandemic amplifies it. Analytics tools, when used well, help by giving you visibility into what’s happening in the business and increasing planning agility. Some of the most important analytics-supported activities for dealing with uncertainty are what-if scenario planning, the ability to compare results for multiple scenarios and cash management and forecasting. We also went on to talk about what QueBIT is doing to survive, and support our employees and customers through these difficult times.

Episode 30: Analytics for Hospitality & Property Management Guest: Walter Hugo Añez Customer experience is a hot topic in every business these days, but in the hospitality industry it has always been paramount! When you walk in the doors of a hotel or a resort as a customer, your expectations are already sky-high. No one goes on an expensive vacation “hoping for the best” after all! Meeting these high expectations is the non-negotiable everyday reality of everyone in hospitality. How do they do it – and still make a profit? In today’s podcast episode, Walter Hugo Añez gives us some insight into how it is done. Superior analytics in the form of planning, reporting and analysis make all the difference regardless of whether you are a brand (such as Marriott, Hilton or Holiday Inn), an investor/owner or a property manager. Daily reporting on occupancy and “on-the-books” reservations enables hotel managers to optimize staffing levels and drive promotional efforts. Cash flow modeling enables investors to projec

Episode 29: Predictive Forecasting: Under the Covers Guest: Scott Mutchler If you have ever worried that Predictive Forecasting as an application of Artificial Intelligence (AI) and Machine Learning is more hype than reality, then this podcast episode is for you! There is a lot of superficial information being put out to sell us all a gleaming vision of an AI powered future, leaving us with a sense that magic must be involved! In this episode, QueBIT’s Chief Data Scientist Scott Mutchler confirms that it is not magic, and then goes on to explain – in terms that you do NOT need to be a data scientist to understand – how it all comes together. Among other things, we talk about how there are mathematical techniques to separate effects like seasonality from the underlying trend, and how sales of low velocity items can be modeled, even when there is a shortage of data. From there we move on to talk about the power of applying predictive technology to detailed bottom-up forecasting and the opportunity to break down

Episode 28: The Challenge of Implementing Analytics on a Global Scale Guest: Dan Viterise People, especially developers and other technologists like me, tend to view analytics projects through the lens of “the technical challenge”. Even if we know that activities like “requirements gathering” and “getting buy-in” are important, they may still be allocated less time and energy than activities related to system architecture, data wrangling and model building which appear – in the moment – to be the bigger challenges. In this week’s podcast, Dan Viterise tells the story of a global luxury brand that had the reasonable-sounding idea of taking an analytics system that had been successful for financial planning in one part of the world and rolling it out to other regions. Unfortunately, it did not go well. The pitfall was that the initiative was viewed as a technology rollout, missing the fact that the purpose of the system was to solve a business problem and that the business drivers outside the original region –

Episode 27: Analytics in the Health Insurance Industry Guest: Ryan McKinney If you heard that profit margins in the health insurance industry can be as low as 3%, would you be surprised? Much as consumers like to complain about health insurers, let’s also give them their due because they are in a difficult business! In this week’s podcast, Ryan McKInney educates us on how the health insurance industry works. In the simplest terms, it’s about expanding membership, controlling medical costs and managing cash. Complexity comes from all the things that the insurer has limited control over like regulations, unpredictable claim schedules and the increasing cost of medical care. The good news is that there is a lot of potential for health insurers to deploy analytics technologies across all areas of their businesses and increase efficiency, improve quality of service, boost preventative care and negotiate better rates with providers. In this wide-ranging conversation, we touch on several valuable use cases for analy

Episode 26: Trusting the AI Forecast in Finance Guest: Allen Hudson Many companies are looking for a way to transcend the limitations of Excel for financial and operational planning, reporting and analysis. They need something that will enable them to securely centralize their data and models (so that both numbers and calculations are managed in just one place), collaborate easily, all while still retaining the flexibility to adjust in response to changing business conditions and organizational structures. Moving away from Excel to a planning software platform is just the first step, but it is an important one. The obvious benefit is that it releases analysts from the drudgery of manipulating data in Excel spreadsheets, and the stress of worrying whether all the reports are correct. They can use their new-found freedom to do more analysis and thinking about the data, and to find ways to add real value to the business. Examples range from understanding the cost structure (and finding savings), to examining sal

Episode 25: IBM Cognos Analytics – a New Paradigm for Business Intelligence Guest: Gus Slaughter Back in the early 2000s Cognos was the leader in enterprise business intelligence (BI) platforms. In July 2008 Forrester Research recognized Cognos Business Intelligence as the most modern and scalable BI platform on the market. Cognos BI brought “pixel perfect” push and pull reporting to the enterprise on a robust platform that ensured data security and responsiveness, even with large numbers of users. Valuable as this is, businesses today crave ever-increasing levels of agility, and the old model of IT-maintained and administered analytics has given way to expectations of self-service convenience. In short: business users want to work directly with their data! New players have entered the BI market catering to these expectations, but finding the right balance between ease-of-use, technical skills and data integrity is not easy. In this week’s podcast Gus Slaughter, QueBIT Business Intelligence and Data Managemen

Episode 24: Planning for Change Management Guest: Brian Moore Regardless of whether you like or dislike change, the best way to manage it is to assume there will be disruption! When change comes to a business in the form of a new software solution, we sometimes forget the disruption part because (by definition) a new software solution will be “better” and “make life easier”. If that were not the expectation, we would not be spending the money! When our guest, VP of Consulting Services Brian Moore, leads a project to implement a new financial analytics software solution, he is acutely aware of the problems that can arise when change is imposed on an organization, even if it is ultimately for the better! In this week’s episode he shares his checklist of what you need to take into account, and provides practical advice for managing change successfully.  This episode is sponsored by QueBIT, trusted experts in analytics.

Episode 23 - Predictive Price Optimization Guest: James Saronson How to price your product or service is a fundamental question in any business. If you price too high, you may sell less than you might, and if you price too low you may earn less than you might. Either of these scenarios can affect profit margins. To further complicate matters, the “right” answer – or optimal price - may vary depending on where you are selling, and what the business objectives are. For example, if you are launching a product in a new geography and trying to break into a market, you may price more aggressively than somewhere else where you have an established foothold. In this episode Principal Data Scientist James Saronson explains how predictive technologies can be leveraged to optimize pricing decisions. He describes it as a human-machine partnership where the machine deals with complexity and volume, but people still get the final say. We also talk about examples and wrap up with advice on how to be successful in implementin