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.
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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