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Delta Partners is the leading Advisory and Investment firm specialized in Telecoms, Media and Technology with offices in the Middle East, Africa, Europe, Asia and Latin America. We partner with global and regional telecom providers, digital players and other TMT clients to help them address their most challenging strategic issues.
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A new Analytics Center of Excellence Community has been launched on analyticszone.com - where you can download the free book "5 Keys to Business Analytics Program Success". Join the conversation today at www.
Tim O'Bryan 270001NMX7 email@example.com | | Tags:  timobryan financialperformancemanag... businessanalyticstoday businessanalytics | 0 Comments | 2,765 Visits
Finance teams are the performance management captain of the corporate ship empowered to provide the executive team, and business and support units with real insight and understanding of past, present, and future performance while guiding them on what the information means to each of their constituents and how it can be interpreted for decision making. That is their most strategic value to the business. However, because of the explosion of information, speed of business, growing systems through M&A and unique information capture needs of different areas of the business not to mention growing business practice demands, such as regulatory compliance to meet the regional, national, and global reporting requirements, the corporation’s most important analytical asset, finance departments, remains mired in just completing the basic week-to-week tasks without providing this strategic guidance. As a result, emerging trends, exploitable opportunities, efficiency gains, addi
In the 1960′s, IBM was the 800-pound gorilla in the mainframe business whose technology supremacy went unchallenged and superior performance went virtually unabated into the 1970′s. They were the blue suits bearing information-based mainframes to help companies use data to run their large – sometimes multinational – businesses with greater know-how about customers, products, operations, and financial performance far more adeptly than any other technology could. Yes, they were considered the masters of product innovation largely due to world-class business practices and industry expertise. However, Big Blue got complacent and far too comfortable in their long held pole position. Their inflated confidence and market share eventually disintegrated as they missed the advent of the new information-based technology, which, if they would have had the right analytic capabilities in place, they would have seen it coming; the emergence of the minicomputer. Minicomputers were technologically simpler than mainframes but with stronger computing power while requiring less resources to run them. To be fair, it wasn’t just IBM that missed the advent of minicomputers. It was virtually every mainframe company in existence at that time. This new technology virtually wiped out the entire mainframe business such that no mainframe business would be a major player in the minicomputer business at all.
What happened? What was missed? Who screwed up?
In my opinion, there were many failures that caused this emerging technology to go unaddressed by IBM and others, but the chief culprit who could and should have been prepared for it was finance. Yes, I think it’s up to finance as the owners of business performance (past, present, and future) to fundamentally understand the business climate – internally and externally – to then advise their corporate constituents on what the information they’ve analyzed means to them. For this to happen finance needs to get a handle on its core responsibilities before it can begin to really spot these performance-sapping icebergs that can possibly turn into business shuttering threats.
Let’s get back to the technology story for a minute if that’s okay. Then, I’ll finish my point.
Where were we? IBM’s out because the mainframe business has gone south – way south by way of the minicomputer. Exit IBM. Enter Digital Equipment Corporation. DEC virtually created the minicomputer business along with a few other aggressively managed companies like Data General, Prime, Wang Computer, Hewlett-Packard, and Nixdorf. Did DEC and others in the minicomputer business learn any lessons from IBM’s big miss on the minicomputer market so as to not repeat the same mistake? Of course not. The story of DEC’s demise rings almost too tellingly true to IBM’s mainframe debacle of the 1970′s. In fact, the management gurus and business journals missed it too. Digital Equipment Corporation was considered by all who had some insight into the company’s operations as being the ultimate technology company for decades to come. For certain it was a featured company in the McKinsey Study that became the stellar 1980′s management book, In Search of Excellence. DEC seemed destined for monster success. Still, despite all this fanfare, DEC missed the next wave in computing technology, the desktop computer market.
Again, where was finance watching past performance by measuring and monitoring it, to get analytical insight into what the future might look like to then advise their constituents across the business on what all of this means to each one of them? Answer: Heads down.
The desktop computing market was predictably seized not by DEC or one of its minicomputer compadres but by Apple Computer, Tandy, Commodore, and IBM’s PC-division. (Yes, IBM can’t be held down for long!)
What happened next? Like Rick Blaine says in the movie Casablanca, “Play It Again, Sam.” Apple, Tandy, IBM and the rest of the desktop computer gang focused on making the best desktop computers they could but ended up missing the next new, new thing. Apple Computer and IBM lagged 5 years behind bringing the latest-and-greatest technology rage to the market: portable computers. That market was owned by Silicon Graphics, Sun, and Apollo – all newcomers to this market.
In each case, the leading companies mentioned were regarded as the gold standard given their product excellence and operational execution only to be quickly pushed aside by an out-of-nowhere, technologically superior solution that reset the market’s expectations rendering the prior leader’s solution frumpy and stale. Missing emerging trends in the marketplace and not adapting to them quickly enough can ring a death knell for most companies. Think Wang, Silicon Graphics, Apollo. For others, this misstep can set them back 5 or even 10 years before they’re back on their feet again.
As a note, in the above example, I simply chose the technology sector but we could have easily used the retail merchandising sector (Think Sears vs. Nordstrom) or retail books (Think Barnes & Noble vs. Amazon), or Automotive (Think GM vs. Toyota). Each situation is an example of a failure to see the changing landscape which, I believe, finance is mostly at fault for squandering these opportunities.
How come finance? I think finance failed their companies in each instance because they weren’t effective enough in managing the day-to-day, low value tasks which, if they had them under control, they would have greater leverage to spend time on higher-value practices like forecasting and business analytics to uncover data points that can help the entire business spot emerging market forces before it’s too late to respond. This responsibility to identify these threats and opportunities lies squarely on finance. If not them, then who else? Be careful because whomever you’ll name will probably expect finance to provide them with the meaningful insight into performance results across the business as well as external information, which, again, means it’s incumbent on finance.
So, how does finance get to that point where it’s able to provide this kind of insight with the resources it has because Lord knows it’s not going to get additional headcount? Well, it all starts with finding a way to better leverage the resources it has. This requires finance teams to get the lower value tasks automated as much as they can so that they can off-load these process management steps to take on added capacity for these analytic practices.
What are the world class finance teams doing to be analytic leaders in their industry? World class analytic finance teams have these repeatable practices down to great consistency and repeatability from end-to-end:
These practices are the foundational elements required for finance to be the advisor in providing guidance to the business. Excel at the practices mentioned above and you’re soon positioning your analytic experts on your finance team to do the real analysis they’re supposed to be doing. It’s incumbent upon the CFO’s finance department to provide this guidance and leadership given finance’s role as the performance managers for the company. It is therefore finance’s job to provide insights into past, present, and future performance but also trends, anomalies and market opportunities that become visible only after thorough analysis of the information-based business results gleaned from systems, i.e. ERP, CRM, SCM, etc. and processes, i.e. forecasting, what-if scenario analytics, etc.
This finance role is looked to not only explain past business performance and its financial effects but also advise and guide the strategy in determining where to make investments with the resources at hand. The CFO’s analytics team – finance – needs to spend its time not on the everyday execution of basic, low value process steps, like compiling, validating, and reconciling data for various internal and external reporting needs but also analyzing past, present, and future to present guidance on what’s happened, what’s happening now, and what could happen. Only with an infrastructure in place to easily manage these basic elements of the finance team’s mandate can the real value-added analytic insights come to light. Otherwise, their companies will continue to drive through its business climate with a perpetual blind spot on what’s coming soon rendering them the next Tandy Computer, Silicon Graphics, or Apollo.
It’s up to you finance to not let this happen.
Check out more blogs by Tim O'Bryan by clicking here!
Delaney Turner 270003RQ8K Delaney.Turner@ca.ibm.com | | Tags:  deloitte ibmbao | 0 Comments | 1,020 Visits
If using analytics in the Office of Finance isn’t particularly new, the kinds of analytics now available to finance professionals most certainly are. Finance still builds budgets and closes the books, but now it’s in areas such as model-based forecasting, advanced fraud detection and portfolio optimization where Finance professionals are finding new sources of value and competitive advantage. Here, I speak to Miles Ewing and Scott Wallace of Deloitte. (Download the podcast version)
Miles is partner in Deloitte’s Finance practice and leads Deloitte’s Integrated performance management practice in the U.S. Scott is a Director in Deloitte’s Risk Information practice and leads the U.S.-Cognos Alliance Relationship.
Analytics can mean different things to different people because you can do so many things with them. Can you explain how Deloitte defines analytics for its clients?
Miles Ewing: Analytics is a very broad term, and from our perspective they’ve been going on since humanity created fire and decided it was warmer to stand next to it than further away from it. But when we think about what’s different today, there are three aspects. First is the fundamental volume of data that’s available today. There will be more information created this year than in the past 5,000 years. Next is the speed at which we can analyze this data. If it took us 10 years to code the genome a decade ago, we can do that it in a week today with our processing power. Third, there’s the reach and breadth of the data. From social networks to sensing technologies there’s a dramatically broader reach.
These combine to give us an enhanced capability to look at both patterns in data and advise on specific individual transaction-level data. Because of this we can make decisions either at a higher level or lower level that we weren’t able to do in the past. And it’s that combined capability and bringing those disciplines to business that is really where Deloitte defines analytics.
Scott Wallace: More tactically speaking, it's really bringing what used to be back-office functions – either with your statisticians and actuaries - into the front office, where Finance professionals can use capabilities to do this analysis on their own. There’s an ability to do more with analytics tactically than before that’s bringing it to life.
Deloitte has different analytical disciplines. Can you provide us with some examples?
Miles Ewing: We break analytics into three areas. The first is core analytics – from basic variance analysis in your budget to the analysis that goes into your external reporting. It’s not just in your traditional FP&A group, but the analytics in your tax department, treasury, investor relations and operations. Companies have been doing that for a long time will continue to do so.
There are two things that are new. The first is where Finance teams are taking advanced analytic methods such as model-based forecasting - algorithmic-based forecasting, advanced fraud detection or portfolio optimization - and bringing those capabilities to their core, either to improve the efficiency and accuracy of these functions, or to add a different way of looking at it and get more bang for their buck on the core analytic side.
The second area is what we would call Finance-supported analytics. And these are areas where Finance is bringing its cross-functional capabilities to the problems faced by other parts of the business, be they in supply chain, procurement, IT or sales and marketing. What we see here is Finance taking a cross-functional view of the situation and coming out to support things like pricing, or vendor spend analysis or technology investment prioritization. These are areas where because of the reach and speed of data, Finance can support decisions at the micro level and provide better, more effective decision-making in those functions in a way that they couldn’t in the past.
Scott Wallace: It’s been core to Finance for a long time to have access and visibility across the organization. The CFO and his or her team need to be aware of what’s happening in other parts of the organization. What you’re seeing with analytics is that coming together and making it more meaningful and more impactful to the organization. Lately we’ve have a lot of requests from our clients asking how to integrate their sales or operational planning with their financial planning. So not only has Finance typically taken a cross-functional view, now there’s a demand pull for that view across organizations because of the capabilities of the tools and the data availability.
What areas of Finance need the most help?
Scott Wallace: As you read the different literature around Finance and analytics from firms like ours and from the academics, they’re really pushing the envelope on how to become a more value-added function using analytics; yet many organizations are still fundamentally trying to fix core processes. I do see a continuing demand and convergence in the area of forecasting. That’s where you’re seeing this convergence of the analytic capabilities and when you think back to what Miles said about the different kinds of analytics, the ability to have insight into other functional information and data, and then how do I move that kind of information into predictive forecasting – identifying those real key drivers of the business across the functions that I can model based on historical data, based on external data, and start to have more confidence in my ability to predict the future financial performance of the company. That’s where we’re asked to provide help.
Miles Ewing: Companies are at very different places. Some are still trying to get the core right and they need to get that set first. Organizations that have been unable to get that core right over the past decade will find it difficult to really advance into that support. They may lack credibility as analytical leaders in their company. Focusing on that core becomes increasingly urgent for them.
Where does the demand for analytics come from? Is it from a CFO setting out a new vision, or does it come from the bottom up? What trends are you seeing?
Scott Wallace: Right now we’re experiencing lot of top-down demand from the CEO and CFO. A lot of it is borne of frustration – despite all the data they have in their ERP and their more advanced operational systems they still don’t feel they’re getting the right levels of transparency and insight. Also, because of the influx of information about analytics and tools and methodologies and success stories they’ve seen, CFOs are really asking themselves how they can continue to grow their relevance within their organizations. They’re really pushing on analytics.
Deloitte has six guiding principles for getting started with analytics. Can you outline them?
Scott Wallace: First off, link your goals and objectives with clear business drivers. If you’re going to use analytics, make sure they tie to your existing strategies or other initiatives you have inside and outside Finance. Ask yourself: What am I really trying to do? What are the competitive differentiators I’m trying to find in my data set?
The second is to know your data. Many of our clients have a good vision. They know what they want to do and how to tie their analytics together, but they run into data issues because the data isn’t in a single location or it’s not clean enough to provide the right insights.
The third is to start simple. Analytics needs to be something that can be accepted by your organization. Pick an area where there’s a need or pent-up demand. Stay focused on that area, get the numbers right and get them delivered properly. Build the confidence within your leadership team that the predictive capabilities and outcomes you’re providing make sense.
The fourth is to leverage existing insights. If you’ve got programs under way – customer analysis programs, working capital analysis programs, for example – look for ways to enhance them using insights you can get from analytics. How can you better project things that are already being looked at by the organization? You’re adding insight to a point of view that’s already being used in the organization.
Tim O'Bryan 270001NMX7 firstname.lastname@example.org | | Tags:  businessanalytics businessanalyticstoday provenpractices timobryan | 0 Comments | 905 Visits
Learn the value of the new IBM Cognos Planning 10.1.1 (GA November 22). You will be pleased to learn of this release as it affirms IBM’s continued commitment to ongoing support and value-added enhancements to the IBM Cognos Planning solution. The release fulfills our customers latest requests with:
- features for greater ease and speed;
IBM Cognos Planning v10.1.1 delivers additional functionality for contributors (end users), faster access to data for reporting, an improved installation features, and conformance with IBM Cognos BI version 10.1.1 and Microsoft Excel 2010, and other key solutions.
Click here to listen!
Tim O'Bryan 270001NMX7 email@example.com | | Tags:  timobryan provenpractices businessanalyticstoday | 1 Comments | 1,262 Visits
We often hear Business Analytics being so many different things that we feel it’s near impossible to get a handle on what it really is. I’m sure you were just getting used to the idea of what Performance Management is and now we throw Business Analytics into the equation. To make matters worse, there’s a great deal of prognosticators, thought leaders, and industry analysts who still are married to the idea of calling the space Business Intelligence. I thought it might make sense to pass along a simple explanation of each without all of the Big 5 consulting speak that usually goes with it. So, here you are.
Business Intelligence (“The Historian”)
BI is where the historian in all of us comes out. This is where you’re doing rear view mirror analysis, querying, reporting, with enabled “alerts”, real-time monitoring, dashboards, scorecards, and visualization focused on past performance. This is your investigative practice area asking the questions ‘what happened?’ and ‘how are we doing?’ followed by thorough analysis of the detail behind the answers to these questions, i.e why are we on- or off-track?
Performance Management (“The Pragmatist”)
Performance Management builds off of “The Historian” to include the following: planning, budgeting, forecasting, and scenario modeling; customer and product profitability, i.e. profitability modeling and optimization; strategy management; governance, risk, and compliance; and, financial consolidation and external reporting. Performance Management is “the Pragmatist” who looks not only at monitoring and analyzing past performance (“The Historian”) but also wants to then use this past performance to help determine what the future outcomes are expected to be (Think budget/forecast), which is based off of these past results weighed against current conditions and intuitive insight, i.e. the “knowns” and “unknowns” about today and the foreseeable future.
Also included is the practice of governance, risk, and compliance. Of course, there needs to be rigor and accountability around these processes, including stringent compliance controls to meet all regulatory requirements. In addition, risk assessments are a necessary component of performance management should not only your performance assumptions (Think Risk-Adjusted Forecasting) be wrong not to mention other business risk elements of the business including strategic risk, market risk, credit risk, IT risk, operational risk, etc. The practice of governance, risk, and compliance enables customers to identify, manage, monitor and report on risk and compliance initiatives across the enterprise, helping businesses to reduce losses, improve decision-making capabilities about things like resource allocation, and, ultimately, optimize business performance.
Performance Management = [Business Intelligence] + [Planning, Budgeting & Forecasting, Profitability Modeling & Optimization, Governance, Risk, and Compliance, Strategy Management, and Financial Management & Control]
Business Analytics (“The Futurist”)
“The Futurist” looks at everything the “The Pragmatist” does but then runs what’s called Predictive Analytics against the Performance Management data that you already have to uncover unexpected patterns and associations and develop models to guide what should be done next. It turns the human element in planning, budgeting, and forecasting on its head by applying pure user-enabled algorithms and customizable statistical analysis providing you with the data driven answers. More simply, with predictive analytics companies are able to prevent high-value customers from leaving, sell additional services to current customers, develop successful products more efficiently, or identify and minimize fraud and risk. This is all being done by businesses all over the world today. Predictive analytics is just what its name suggests: It’s about giving you the knowledge to predict. [Business Analytics = [Performance Management] + [Predictive Analytics]
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Financial Performance Management for the Empowered CFO (using IBM Cognos TM1, IBM Cognos Controller & IBM Cognos BI for Scorecarding)
Tim O'Bryan 270001NMX7 firstname.lastname@example.org | | Tags:  timobryan businessanalytics businessanalyticstoday provenpractices | 0 Comments | 925 Visits
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Tim O'Bryan 270001NMX7 email@example.com | | Tags:  provenpractices businessanalyticstoday businessanalytics timobryan | 0 Comments | 1,061 Visits
Tim O'Bryan 270001NMX7 firstname.lastname@example.org | | Tags:  timobryan provenpractices businessanalytics businessanalyticstoday | 0 Comments | 1,829 Visits
With six weeks to go before the end of the year my thoughts have of late been going in two directions, usually at once. If I'm not looking back on the year that was (an extraordinary year for IBM, given its 100th birthday as a company) I'm looking at the year that will be, given our persistently uncertain economy and the blinding pace of change.
We'll be recapping the major themes of the year over the next few weeks, but in the meantime I'd like to highlight some recent research from IBM that should help you chart your course as you look ahead to next year as well.
Mind the gap. (The analytics gap)
The first is Analytics: The widening divide. This is the second study from MIT Sloan Management Review and the IBM Institute for Business Value to explore how organizations are using business analytics to outperform and drive better outcomes. The 2010 survey identified three types of analytical sophistication: Aspirational, Experienced and Transformed. This new survey reveals what these organizations were able to achieve competitively through their use of analytics. IOD attendees saw a sneak peek of the results (Read my earlier post here).
The study's main finding was the growing gap in the ability of organizations to gain competitive advantage through analytics. Almost 60 percent of organizations are now achieving competitive advantage with analytics. Transformed organizations that apply analytics for a competitive advantage are 3.4 times more likely to substantially outperform their industry peers. Companies that wait to advance their analytics capabilities do so at their own risk.
You can connect with author Rebecca Shockley here, learn more about the report here or download the PDF here.
IT skills for future success
Next is the 2011 IBM Tech Trends Survey, which came out earlier this week. This extensive survey asked more than 4,000 IT professionals from across our developerWorks community about the future of analytics, cloud, mobile computing and social business and returned some fascinating results.
Big data means big challenges for mid-market CMOs
The third report is the 2011 IBM Midmarket CMO Study, which points out the big-time concerns of small- and mid-sized businesses. For example:
The report also suggests that today’s CMOs need to be better prepared with an empowered consumer that is impacting brands instantly on Twitter, Facebook, and other social channels. (Look no further than this week’s challenge that Bank of America faced when its Google+ channel was “brandjacked”!)
There are some success stories, though. Todd's done a great job of summarizing the findings on his blog and you can download the report here.
Tim O'Bryan 270001NMX7 email@example.com | | Tags:  provenpractices kpis timobryan businessanalytics strategymanagement businessanalyticstoday | 0 Comments | 1,872 Visits
Drive Better Performance Thru Greater Finance Integration with the Sales & Operations Planning Process
Tim O'Bryan 270001NMX7 firstname.lastname@example.org | | Tags:  businessanalyticstoday salesandoperationsplannin... businessanalytics provenpractices | 0 Comments | 2,267 Visits
Delaney Turner 270003RQ8K Delaney.Turner@ca.ibm.com | | Tags:  ibmbao iod11 | 0 Comments | 630 Visits
IOD started with kids playing with jigsaw puzzles and ended with naked baseball players.
I dare you to say that analytics isn't fun.
And transformative. And an absolute priority should you want to survive in these uncertain times. Over the past three days we've all seen and learned so much that it's sometimes difficult to recall the key themes. So I've presented them for you here, built as we've gone along learning to turn insight into action:
1. Mind the gap: The competitive and performance gap between analytics leaders and laggards is getting wider. The time to act is now. If you're just starting, start where it hurts the most. If you're on your way, take new steps to keep your momentum. Our business value assessment or Analytics Quotient Quiz will help you find your way.
2. Big data is a big deal. There's more of it every day. How much more? Exponentially more. In all forms, from every conceivable source. Learn to master the 3 'Vs' - Volume, Variety and Velocity - and use them to your advantage, or risk being buried by them, perhaps for good.
3. Commit to change, embrace the new: Last year's assumptions and last month's targets are history; focus on what will take you forward. Commitment to change has helped IBM survive for a full 100 years. Billy Beane overturned an entrenched century-old culture to redefine value and change the way his game was played. Your presence at IOD attests to your desire to change, too.
4. Paging Dr. Watson: Hospital readmissions are punitive for the provider and counterproductive for the patient. Incomplete data drives incorrect diagnoses. Medical errors cost real human lives. With our health care partners we've put Watson to work with real-world solutions to reverse these trends and eliminate these errors. With Watson's help doctors can better understand each patient in startling new detail and treat each patient in effective new ways.
5. Don't mess with Billy Beane's mom. If you're writing a book about a baseball GM who swears a lot, be prepared for her withering glare. Her son just doesn't talk like that.
6. No industry is immune from disruption. Urbanization. Changing citizen and customer expectations. Economic uncertainty. Increased regulations. Lots and lots of data. All are interconnected; all are hitting you on every side, all the time. Your task is to quantify the impact, assess the risk and harness opportunities in new and productive ways. On a planet that is instrumented, interconnected and intelligent there is no domain that is untouched by these forces. There is no domain where analytics - and IBM - cannot help. At IOD you've seen how we're doing precisely this.
7. Jeff Jonas is evil. Just look at the guy. Look at the way he dresses. Luckily, he's the charismatic, smart kind of evil you can't help but listen to, because you can feel yourself getting smarter the longer – and faster - he talks. Frankly, I'm glad he's on our side.
8. Got social? It's time to get serious about social media analytics. There's enough data out there and enough computational power to build predictive customer loyalty models based on blogs and tweets alone. That's along, long way from zip codes. Need the tools to get started? We have them, too.
9 .Congratulation, Ginni. Our soon-to-be President and CEO will take charge with IBM operating from a solid foundation and 'at the top of its game.' She's successful, she's thoughtful. She gets things done.
10. It's business, and it's personal. This is the age of the empowered consumer. They're demanding, they're patient and they're in control of your brand. If you want to win their business – and keep them coming back – you'll need to know more about them than their zip code. The data to do this is out there and so are the tools. The choice of how and when to use them is entirely up to you.
11. Kudos to the Mandalay Bay staff for keeping us fed and caffeinated. Greeting 11,000 bleary-eyed conference goers with a friendly smile before 9 AM is no easy task; yet to a person you outdo yourselves every single year.
Well, that's it from my end for this year's edition of Information On Demand 2011. As of right now, I'm taking what I believe to be a very necessary vacation. I'll return refreshed and recharged in two weeks. Safe travels, and see you next year.
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Delaney Turner 270003RQ8K Delaney.Turner@ca.ibm.com | | Tags:  ibmbao iod11 | 0 Comments | 730 Visits
Moneyball author Michael Lewis and Moneyball pioneer Billy Beane closed out Information On Demand 2011 in a rollicking conversation with event host Katty Kay. Among the topics were challenging a century-old business culture with business analytics, the risks of standing still and why it's never a good idea to mess with Billy Beane's mom. Turbo's already done a great summary, so I've distilled their conversation into a few key quotes.
On the meaning of Moneyball: 'This was riveting to me. The number crunching was less interesting than what it exposed about the markets people operate in. The people running baseball considered themselves player experts because they'd been doing things the same way for 150 years. And here was Beane recruiting people the market perceived as defective. He was building a juggernaut out of defective parts.'
On bias: 'People tend to overvalue things that are flashy and easy to see. And they tend to undervalue things that are more difficult to see. You need to understand the forces that are clouding your judgement.'
On Beane and his players: 'He had tremendous credibility with the players because he was a great athlete. Being bigger than them also helped. The players were physically intimidated. It was kind of the law of the jungle in the clubhouse – reason imposed by violence.'
On offending Beane's mother because he left in Beane's profanity: 'She said, 'My son doesn't talk like that.' After the book signing I invited her to a two-hour dinner. It was the most awkward conversation I've ever had. I laid on as much charm as I could and got nowhere. She was just as angry with me at the end as at the beginning.'
On the need for change: 'For us it was out of necessity. Where were we going to get the best return on our dollar? We weren't in a position to trust emotion to run our business. We couldn't invest in the romance of the players. We had to be disciplined card counters.'
On taking risks: 'We didn't think it was risky because the math told us we'd be successful. Over enough games we knew we'd weed out the randomness. There was certainly resistance, but there was more risk in not doing it. Going with our gut would have been the most irrational thing to do.'
On Lewis revealing the secret: 'You could see the market was going move. It was just a matter of time. There was already momentum – you could feel the rumblings. You couldn't ignore the fact that the data was everywhere. The secret now is to keep your expertise in-house.'
On outcomes: 'I believe the best teams make it to the playoffs, but the best team doesn't always win the World Series. Small events in a short series can have a bigger impact; we never try to make decisions based on short-term results.'
On being played by Brad Pitt: 'You tend to hold your breath while they're casting the film. When you hear it's Brat Pitt, you exhale.'
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