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By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 1
Convergence Creating Big Data
The Three “V”s of Big Data
What do they mean to Financial Planners?
Big Data is currently garnering a tremendous amount of attention.1
When compared to the vast
quantities of data in the recent past, thought leaders often point to three key attributes—volume,
velocity, and variety.2 The analysis of these three key attributes can be extended into understand-
ing what Big Data means to the financial planning and analysis function. This article identifies the
technology developments converging to create the Big Data rush and examines how the financial
planning function is impacted by volume, velocity, and variety of data. It seeks to help financial
planners leverage these Big Data differences into better performance management and more effec-
tive planning.
There are several distinct technology developments that have converged to create the
Big Data storm. Following are the most important factors:
1 	 The Internet opens the path for collaboration and knowledge
sharing. This means virtually anyone can be enabled to partici-
pate.
2 	 Mobile devices have uncoupled both input sources and re-
porting locations opening them to virtually anywhere that can
be reached by a tower or a satellite. This means participation
can come from virtually anyone, anywhere, anytime.
3 	 Sensor technology has automated data collection while dramat-
ically lowering device costs. This means cost-effective tracking is
within reach of more and more organizations.
4 	 Cloud computing reduces the upfront costs of technology while
opening access to millions. This means that users are freed from con-
straints in their Information Technology departments—freed to quickly deploy
business applications without the IT manpower required for typical on premise
applications. It also frees time in that these applications are configurable rather than
customizable, which further reduces the IT requirement. The IT department also
enjoys this freedom as the time freed up means they can focus on other strategic
projects.
5 	 Digitized business has become the norm creating an ocean of data as a normal
by-product of their operation. This means a wealth of business data that merely
needs to be accessed.
6 	 Social media has rapidly spread to provide millions of data points, constantly
flowing by, that just need to be tapped into and analyzed. This means a wealth of
additional data that is consumer generated and low cost to access.
7 	 In-memory storage costs have continued to follow Moore’s Law of increasing
storage capacity at lower costs. This means that all the data being generated has a
better chance of being available to be used in “real-time” via RAM storage.
Big
Data
In-memory
computing
In-memory
storage
Social
media
Digitized
business
Cloud
computing
Sensor
technology
Mobile
devices
Internet
By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 2
When speaking about planning, budgeting, and forecasting, I often note that financial planners
send out instructions that approach the annual budgeting exercise as if they are beginning with a
clean sheet of paper. This might work if your organization is a brand new start up; however, most
companies will find more useful plans by assuming their organization is like a ship that is sailing out
on the water.
Using this sailing analogy, you should view your ship as an accumulated set of capabilities with a
related cost structure. It has been formed based on thousands of decisions you made in the past—
decisions about:
●● What products and services you should pro-
vide.
●● What customers you will serve.
●● What people you have hired.
●● What processes you are running.
●● Where you have chosen to locate your
facilities.
●● What equipment you have.
●● And thousands of additional past decisions.
In planning you can choose to change any of those
things. In reality it typically takes a project or initiative
and the related planning and implementation time to
make that change occur. And that change must happen
while your ship keeps sailing.
In financial planning it is important to realize that the
small pond or lake we may have thought we were
sailing on has turned into a huge sea of available data.
And the oceans of data created by Big Data volume have made the surface a lot rougher and poten-
tially dangerous. [See Figure 1]
Just as a sailor would ask when facing rough seas, a financial planner in the sea of Big Data must ask
“What do we need to know? What of this information is relevant to our decision making?”
This first question on the volume of Big Data options is one of current priority.
●● Is there information that helps to better understand our customers? For example, retailers
are analyzing customer buying patterns and their response to specific types of promotions.
Planners use this knowledge to better forecast sales.
Big Data: Volume
IDC Forecast Growth for Big Data
$
Billion
2010 2015
3.2
16.9
40% Compound
Annual Growth Rate
Source: Worldwide Big Data Technology and Services 2012-2015
Forecast released by International Data Corporation (IDC)
Figure 1
8 	 In-memory computing brings the processing power to allow analysts to convert
data into insights. This means that there is a powerful way to bring all these devel-
opments together to produce insights that lead to greater value.
While each of these developments is individually powerful, it is the interaction between them that
creates the current Big Data storm. For financial planners, the right focus can turn the storm into a
gold rush.
By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 3
●● Is there information that helps us to understand our operations? For example, utilities are
accessing smart meter data to understand customer usage patterns to optimize capacity
and avoid expensive capital additions.
The second question on Big Data volume is one of risk mitigation.
Is there information that helps us better understand our competitors? Just as data volume helps
you evaluate your capabilities and cost structure, it can also be used to evaluate competitors’ ca-
pabilities and cost structure. In places where you identify that they have an advantage, you can use
the information to catch up. Likewise, you can exploit the places where you have an advantage.
The third question on Big Data volume is one of future effectiveness.
What can we do to better position our organization? This question requires mining Big Data to help
validate your strategic plan and your ability to achieve your objectives. In addition to your own
performance and that of competitors, you also need to overlay the environmental forces. Even
though you seem to be on bigger water facing more competition, your organization still has goals
and objectives. You just have much greater information to help understand your situation and more
ways in which you can respond.
Big Data: VELOCITY
The massive expansion in data volume is being fed by expanding data velocity. Improvements in
mobile phones began to hint of potential changes. The pace accelerated as the phones became
smarter. Their capability began an explosion in data velocity with Tweets, Facebook posts, and the
desire to always be in touch—all being done from your smartphone. Then the iPad opened the
flood gates by capturing the imagination of consumers everywhere it was available. Consumers
raced to buy it and then put it to use. It made it easy to capture and easy to share everything—
photos, videos, jokes, product and service recommendations, maps and directions, your thoughts,
hopes, and dreams—in essence your life. Social media became more mobile and the technology
forces noted above began to feed on each other. Data velocity increased geometrically.
The iPad also began to impact business as consumers began to want the same experience at work
that they found at home. While past IT efforts faced huge resistance to change, the current explo-
sion is fueled by the consumerization of IT.3 For many IT professionals this is moving too fast. Some-
times they have become the resisters of change. That may be justified as concerns over security and
privacy need to be thoughtfully considered and addressed. But by now it is clear that this velocity is
accelerating. The key to success is identifying how to take advantage of it.
Those struggling with accelerating data velocity can benefit from looking at sports analogies. When
players move up in levels, such as from high school to college or college to the professional ranks,
coaches often advise that the player work to slow the game down.4 What they are referring to is
how an athlete’s perception of time is altered by his preparation for the contest being entered. As
sports coach Geoff Miller explains,
“In simple terms, the game speeds up because our perception of time is altered by
how we concentrate and by how much information we make automatic. If you can
understand how to control the way you focus your attention and automate the im-
portant physical skills and mental cues you’ll need …, you can slow the game down
and improve your performance under pressure.”5
Is there information
that helps us to
understand our
operations?
Is there information
that helps us to
better understand
our customers?
By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 4
Big Data: Variety
Organizations can benefit from this same advice.
Similar to athletes, organizations can get into “the Zone” where performance flows. The key is to
deeply understand the information that is flowing around you and how your organization interacts
with it.
For financial planners, the biggest clear benefit of velocity is how it enables real-time moni-
toring and analysis as well as immediate action/reaction to adjust and improve.
In the old financial planning world the feedback loops were painfully slow. They were often tied to
monthly financial reporting cycles that produced monthly reports three to 15 days after month end.
By the time results could get analyzed, organizational reaction would lose two to three months just
to the lags on reporting. Those same delays would permeate reporting while management waited
to see if their planned countermeasures were having the desired effect without any negative con-
sequences. Real-time monitoring can provide almost instant feedback on whether your actions are
having the desired effects.
The second benefit is closely related in that real-time monitoring enables financial managers to
eliminate batch management cycles.
Reporting can shift to continuous trend lines that track actual results compared to forecast expec-
tations. While management teams will need to distinguish normal statistical fluctuations from true
movement, the move away from monthly and quarterly batch cycles can greatly smooth workloads.
It also provides a more timely warning system of where period results will wind up. The rolling fore-
casts process shows the expected outcomes. Daily reporting tracks against it providing up-to-date
status. Monitoring provides greater insights to business fluctuations. Do revenues spike in relation
to sales bonus targets? Do expenses swing upward at yearend as budget authority closes? Are the
fluctuations due to the natural business cycle or caused by reaction to the management system?
Understanding how your processes interact with the underlying business environment enables your
organization to become more agile. An agile organization is much better equipped to deal with an
ocean of Big Data.
A key reason for this increased agility is how the use of Big Data collapses the analysis to action
cycle. Tools such as in-memory computing allow organizations to tap and leverage this data because
the information is better understood, more precise, and insightful, and therefore more actionable.
The organization effectively slows the game down by being able to act much more quickly.
While most of the explosion of data volume is digital, it comes in a tremendous variety. Financial
planners are very familiar with transactional data which is their historical data source. There is even
some familiarity in using nonfinancial data (such as activity volumes, driver quantities, and quality
measures) as managers have expanded the metrics in their balanced scorecards. But data is now
springing free from all directions.
Much of the data is unstructured—think of the ubiquitous social media channels such as Facebook,
Twitter, and blogs. While tools such as LinkedIn have label tags, the underlying data has limited
structure. You also have sensor data, traffic counts, searches by Global Positioning Systems (GPS),
Similar to athletes,
organizations can
get into “the Zone”
where performance
flows. The key is to
deeply understand
the information
that is flowing
around you and how
your organization
interacts with it.
By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 5
When initially considering how to apply Big Data, financial planners may feel overwhelmed. This is
as natural as the first time you take a sailboat out into open water. You can overcome this by start-
ing slowly. Take your planning areas and break it down into smaller chunks. Successfully completing
small chunks can build confidence to take on larger tasks. Three smaller chunks you can use for
quick start ideas include:
1 	 Take an existing area such as a revenue line item and build the logic diagram back-
ward. Remember you are trying to build all the way back to where you first touch
potential customers. List all the touch points and find where Big Data can provide
useful insights.
2 	 Evaluate how Big Data impacts your management framework. Begin with a diagram
of your current process. Annotate the places where Big Data is already assisting and
where it could help in the future. This can be used to develop your process improve-
ment road map. (If you have never diagrammed your management framework,
begin the process with one of the general management models available such as the
APQC’s global process classification scheme or the U.S. Malcolm Baldrige National
Quality Award criteria.)
and even mobile GPS data. It would be virtually impossible to
produce an exhaustive list because new sources are constantly
being developed. The challenge is to use this ocean of data
without being lost at sea—and it’s a sea of complexity bred by
the variety of data.
When examining this data I am often reminded of the old style radio dials that allowed tuning by
turning them left or right. When you got one positioned just right, the signal would get translated
into clear words or sounds. If you had it wrong, the only noise you heard was static. As we move
about today, we are surrounded by a spectrum that carries information. But the only way we can
hear it is if we are properly tuned in. Likewise, there is a variety of Big Data streaming around our
organization to which many of us are oblivious. There are tremendous opportunities for those who
harvest the insights this information provides.
Planners are already using predictive logic diagrams. These management tools provide visual exam-
ples of the change of activities that lead to desired actions. Forecasters work with sales managers to
forecast expected sales by examining the current status and movement being tracked in an organi-
zation’s sales funnel. The sales funnel serves as a predictive logic diagram showing the relationship
between different levels of sales interest. Inquiries and targets are pursued to be converted into
leads. Leads are tracked and converted into proposal opportunities, which are tracked through sales
completion. The size of jobs and results being experienced provide knowledge that can be used in
predicting future outcomes. The lag time through the sales cycle predicts the future outcomes from
the current pipeline.
These predictive logic diagrams become more useful when they extend further up into the leading
activities that foreshadow future outcomes. New tools such as sentiment analysis help extend these
efforts to provide faster customer feedback and longer lead times for reactions. They are the new
fields that planners are beginning to learn how to harvest.
Action Items for Financial Planners
New sources of data are constantly being developed
Sensor data
Traffic counts
GPS data
Blogs
Mobile GPS data
By Steve Player,
Program Director,
Beyond Budgeting Round
Table, North America
Copyright 2012.
Beyond Budgeting Round
Table, North America.
All rights reserved.
Page 6
3 	 Examine what benefits you can get from external data sources that have become
available from cloud-based data providers. These include OPEX Engine that provides
all public SEC data that is accessed by XBRL or Prevedere, which provides various
economic trend data.
In addition to the small chunks, organizations should consider investing in in-memory (RAM-based)
computing to help process Big Data’s volume, velocity, and variety. Many senior executives are stuck
in old paradigms. Frankly, the total cost of ownership of the applications has become very afford-
able. This is a technology area that can yield significant returns quickly. The good news is that prac-
tices in these areas are evolving quite rapidly—but it is only good news if you and your organization
are evolving with them. The currents are swift and teams are learning how to sail more effectively.
Planning managers should ask their staffs how they see Big Data developing. What information is
already being generated and just needs to be captured and used (such as GPS data)? What new
insights are becoming available (such as the public data available at very low cost)? How can your
customers’ actions help forecast their needs? Remember that one key driver of increased potential
value is that most major trends are pushing the cost lower and making more and more information
accessible. That continues to open new possibilities.
1	 See Harvard Business Review October 2012 theme issue “Getting Control of Big Data,” p. 59-83
2	 See McAfee, Andrew and Erik Beynjolfsson’s “Big Data: The Management Revolution”. Harvard Business Review, Oct. 2012, p. 60- 68. Also note the discussion of
the 3Vs of Big Data appears to have first occurred in a 2001 by Doug Laney on the “Three Dimensional Data Challenge” published by META Group (now part of
Gartner).
3	 See how quickly the iPad/ tablets have been adopted at http://www.zdnet.com/1-in-4-tablet-owners-say-it-is-now-their-primary-computer-7000004770/
4	 See Geoff Miller’s “Slowing the Game Down” at http://www.beabetterhitter.com/text/mental/SlowingtheGameDown.htm . While it uses a baseball analogy, it
provides useful advice to planners as well.
5	 Ibid.
6	 For a deeper understanding of what’s contributing to the explosion of data vs. just digital see the following link http://mashable.com/2012/06/22/data-created-ev-
ery-minute/

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The Three "V"s of Big Data

  • 1. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 1 Convergence Creating Big Data The Three “V”s of Big Data What do they mean to Financial Planners? Big Data is currently garnering a tremendous amount of attention.1 When compared to the vast quantities of data in the recent past, thought leaders often point to three key attributes—volume, velocity, and variety.2 The analysis of these three key attributes can be extended into understand- ing what Big Data means to the financial planning and analysis function. This article identifies the technology developments converging to create the Big Data rush and examines how the financial planning function is impacted by volume, velocity, and variety of data. It seeks to help financial planners leverage these Big Data differences into better performance management and more effec- tive planning. There are several distinct technology developments that have converged to create the Big Data storm. Following are the most important factors: 1 The Internet opens the path for collaboration and knowledge sharing. This means virtually anyone can be enabled to partici- pate. 2 Mobile devices have uncoupled both input sources and re- porting locations opening them to virtually anywhere that can be reached by a tower or a satellite. This means participation can come from virtually anyone, anywhere, anytime. 3 Sensor technology has automated data collection while dramat- ically lowering device costs. This means cost-effective tracking is within reach of more and more organizations. 4 Cloud computing reduces the upfront costs of technology while opening access to millions. This means that users are freed from con- straints in their Information Technology departments—freed to quickly deploy business applications without the IT manpower required for typical on premise applications. It also frees time in that these applications are configurable rather than customizable, which further reduces the IT requirement. The IT department also enjoys this freedom as the time freed up means they can focus on other strategic projects. 5 Digitized business has become the norm creating an ocean of data as a normal by-product of their operation. This means a wealth of business data that merely needs to be accessed. 6 Social media has rapidly spread to provide millions of data points, constantly flowing by, that just need to be tapped into and analyzed. This means a wealth of additional data that is consumer generated and low cost to access. 7 In-memory storage costs have continued to follow Moore’s Law of increasing storage capacity at lower costs. This means that all the data being generated has a better chance of being available to be used in “real-time” via RAM storage. Big Data In-memory computing In-memory storage Social media Digitized business Cloud computing Sensor technology Mobile devices Internet
  • 2. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 2 When speaking about planning, budgeting, and forecasting, I often note that financial planners send out instructions that approach the annual budgeting exercise as if they are beginning with a clean sheet of paper. This might work if your organization is a brand new start up; however, most companies will find more useful plans by assuming their organization is like a ship that is sailing out on the water. Using this sailing analogy, you should view your ship as an accumulated set of capabilities with a related cost structure. It has been formed based on thousands of decisions you made in the past— decisions about: ●● What products and services you should pro- vide. ●● What customers you will serve. ●● What people you have hired. ●● What processes you are running. ●● Where you have chosen to locate your facilities. ●● What equipment you have. ●● And thousands of additional past decisions. In planning you can choose to change any of those things. In reality it typically takes a project or initiative and the related planning and implementation time to make that change occur. And that change must happen while your ship keeps sailing. In financial planning it is important to realize that the small pond or lake we may have thought we were sailing on has turned into a huge sea of available data. And the oceans of data created by Big Data volume have made the surface a lot rougher and poten- tially dangerous. [See Figure 1] Just as a sailor would ask when facing rough seas, a financial planner in the sea of Big Data must ask “What do we need to know? What of this information is relevant to our decision making?” This first question on the volume of Big Data options is one of current priority. ●● Is there information that helps to better understand our customers? For example, retailers are analyzing customer buying patterns and their response to specific types of promotions. Planners use this knowledge to better forecast sales. Big Data: Volume IDC Forecast Growth for Big Data $ Billion 2010 2015 3.2 16.9 40% Compound Annual Growth Rate Source: Worldwide Big Data Technology and Services 2012-2015 Forecast released by International Data Corporation (IDC) Figure 1 8 In-memory computing brings the processing power to allow analysts to convert data into insights. This means that there is a powerful way to bring all these devel- opments together to produce insights that lead to greater value. While each of these developments is individually powerful, it is the interaction between them that creates the current Big Data storm. For financial planners, the right focus can turn the storm into a gold rush.
  • 3. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 3 ●● Is there information that helps us to understand our operations? For example, utilities are accessing smart meter data to understand customer usage patterns to optimize capacity and avoid expensive capital additions. The second question on Big Data volume is one of risk mitigation. Is there information that helps us better understand our competitors? Just as data volume helps you evaluate your capabilities and cost structure, it can also be used to evaluate competitors’ ca- pabilities and cost structure. In places where you identify that they have an advantage, you can use the information to catch up. Likewise, you can exploit the places where you have an advantage. The third question on Big Data volume is one of future effectiveness. What can we do to better position our organization? This question requires mining Big Data to help validate your strategic plan and your ability to achieve your objectives. In addition to your own performance and that of competitors, you also need to overlay the environmental forces. Even though you seem to be on bigger water facing more competition, your organization still has goals and objectives. You just have much greater information to help understand your situation and more ways in which you can respond. Big Data: VELOCITY The massive expansion in data volume is being fed by expanding data velocity. Improvements in mobile phones began to hint of potential changes. The pace accelerated as the phones became smarter. Their capability began an explosion in data velocity with Tweets, Facebook posts, and the desire to always be in touch—all being done from your smartphone. Then the iPad opened the flood gates by capturing the imagination of consumers everywhere it was available. Consumers raced to buy it and then put it to use. It made it easy to capture and easy to share everything— photos, videos, jokes, product and service recommendations, maps and directions, your thoughts, hopes, and dreams—in essence your life. Social media became more mobile and the technology forces noted above began to feed on each other. Data velocity increased geometrically. The iPad also began to impact business as consumers began to want the same experience at work that they found at home. While past IT efforts faced huge resistance to change, the current explo- sion is fueled by the consumerization of IT.3 For many IT professionals this is moving too fast. Some- times they have become the resisters of change. That may be justified as concerns over security and privacy need to be thoughtfully considered and addressed. But by now it is clear that this velocity is accelerating. The key to success is identifying how to take advantage of it. Those struggling with accelerating data velocity can benefit from looking at sports analogies. When players move up in levels, such as from high school to college or college to the professional ranks, coaches often advise that the player work to slow the game down.4 What they are referring to is how an athlete’s perception of time is altered by his preparation for the contest being entered. As sports coach Geoff Miller explains, “In simple terms, the game speeds up because our perception of time is altered by how we concentrate and by how much information we make automatic. If you can understand how to control the way you focus your attention and automate the im- portant physical skills and mental cues you’ll need …, you can slow the game down and improve your performance under pressure.”5 Is there information that helps us to understand our operations? Is there information that helps us to better understand our customers?
  • 4. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 4 Big Data: Variety Organizations can benefit from this same advice. Similar to athletes, organizations can get into “the Zone” where performance flows. The key is to deeply understand the information that is flowing around you and how your organization interacts with it. For financial planners, the biggest clear benefit of velocity is how it enables real-time moni- toring and analysis as well as immediate action/reaction to adjust and improve. In the old financial planning world the feedback loops were painfully slow. They were often tied to monthly financial reporting cycles that produced monthly reports three to 15 days after month end. By the time results could get analyzed, organizational reaction would lose two to three months just to the lags on reporting. Those same delays would permeate reporting while management waited to see if their planned countermeasures were having the desired effect without any negative con- sequences. Real-time monitoring can provide almost instant feedback on whether your actions are having the desired effects. The second benefit is closely related in that real-time monitoring enables financial managers to eliminate batch management cycles. Reporting can shift to continuous trend lines that track actual results compared to forecast expec- tations. While management teams will need to distinguish normal statistical fluctuations from true movement, the move away from monthly and quarterly batch cycles can greatly smooth workloads. It also provides a more timely warning system of where period results will wind up. The rolling fore- casts process shows the expected outcomes. Daily reporting tracks against it providing up-to-date status. Monitoring provides greater insights to business fluctuations. Do revenues spike in relation to sales bonus targets? Do expenses swing upward at yearend as budget authority closes? Are the fluctuations due to the natural business cycle or caused by reaction to the management system? Understanding how your processes interact with the underlying business environment enables your organization to become more agile. An agile organization is much better equipped to deal with an ocean of Big Data. A key reason for this increased agility is how the use of Big Data collapses the analysis to action cycle. Tools such as in-memory computing allow organizations to tap and leverage this data because the information is better understood, more precise, and insightful, and therefore more actionable. The organization effectively slows the game down by being able to act much more quickly. While most of the explosion of data volume is digital, it comes in a tremendous variety. Financial planners are very familiar with transactional data which is their historical data source. There is even some familiarity in using nonfinancial data (such as activity volumes, driver quantities, and quality measures) as managers have expanded the metrics in their balanced scorecards. But data is now springing free from all directions. Much of the data is unstructured—think of the ubiquitous social media channels such as Facebook, Twitter, and blogs. While tools such as LinkedIn have label tags, the underlying data has limited structure. You also have sensor data, traffic counts, searches by Global Positioning Systems (GPS), Similar to athletes, organizations can get into “the Zone” where performance flows. The key is to deeply understand the information that is flowing around you and how your organization interacts with it.
  • 5. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 5 When initially considering how to apply Big Data, financial planners may feel overwhelmed. This is as natural as the first time you take a sailboat out into open water. You can overcome this by start- ing slowly. Take your planning areas and break it down into smaller chunks. Successfully completing small chunks can build confidence to take on larger tasks. Three smaller chunks you can use for quick start ideas include: 1 Take an existing area such as a revenue line item and build the logic diagram back- ward. Remember you are trying to build all the way back to where you first touch potential customers. List all the touch points and find where Big Data can provide useful insights. 2 Evaluate how Big Data impacts your management framework. Begin with a diagram of your current process. Annotate the places where Big Data is already assisting and where it could help in the future. This can be used to develop your process improve- ment road map. (If you have never diagrammed your management framework, begin the process with one of the general management models available such as the APQC’s global process classification scheme or the U.S. Malcolm Baldrige National Quality Award criteria.) and even mobile GPS data. It would be virtually impossible to produce an exhaustive list because new sources are constantly being developed. The challenge is to use this ocean of data without being lost at sea—and it’s a sea of complexity bred by the variety of data. When examining this data I am often reminded of the old style radio dials that allowed tuning by turning them left or right. When you got one positioned just right, the signal would get translated into clear words or sounds. If you had it wrong, the only noise you heard was static. As we move about today, we are surrounded by a spectrum that carries information. But the only way we can hear it is if we are properly tuned in. Likewise, there is a variety of Big Data streaming around our organization to which many of us are oblivious. There are tremendous opportunities for those who harvest the insights this information provides. Planners are already using predictive logic diagrams. These management tools provide visual exam- ples of the change of activities that lead to desired actions. Forecasters work with sales managers to forecast expected sales by examining the current status and movement being tracked in an organi- zation’s sales funnel. The sales funnel serves as a predictive logic diagram showing the relationship between different levels of sales interest. Inquiries and targets are pursued to be converted into leads. Leads are tracked and converted into proposal opportunities, which are tracked through sales completion. The size of jobs and results being experienced provide knowledge that can be used in predicting future outcomes. The lag time through the sales cycle predicts the future outcomes from the current pipeline. These predictive logic diagrams become more useful when they extend further up into the leading activities that foreshadow future outcomes. New tools such as sentiment analysis help extend these efforts to provide faster customer feedback and longer lead times for reactions. They are the new fields that planners are beginning to learn how to harvest. Action Items for Financial Planners New sources of data are constantly being developed Sensor data Traffic counts GPS data Blogs Mobile GPS data
  • 6. By Steve Player, Program Director, Beyond Budgeting Round Table, North America Copyright 2012. Beyond Budgeting Round Table, North America. All rights reserved. Page 6 3 Examine what benefits you can get from external data sources that have become available from cloud-based data providers. These include OPEX Engine that provides all public SEC data that is accessed by XBRL or Prevedere, which provides various economic trend data. In addition to the small chunks, organizations should consider investing in in-memory (RAM-based) computing to help process Big Data’s volume, velocity, and variety. Many senior executives are stuck in old paradigms. Frankly, the total cost of ownership of the applications has become very afford- able. This is a technology area that can yield significant returns quickly. The good news is that prac- tices in these areas are evolving quite rapidly—but it is only good news if you and your organization are evolving with them. The currents are swift and teams are learning how to sail more effectively. Planning managers should ask their staffs how they see Big Data developing. What information is already being generated and just needs to be captured and used (such as GPS data)? What new insights are becoming available (such as the public data available at very low cost)? How can your customers’ actions help forecast their needs? Remember that one key driver of increased potential value is that most major trends are pushing the cost lower and making more and more information accessible. That continues to open new possibilities. 1 See Harvard Business Review October 2012 theme issue “Getting Control of Big Data,” p. 59-83 2 See McAfee, Andrew and Erik Beynjolfsson’s “Big Data: The Management Revolution”. Harvard Business Review, Oct. 2012, p. 60- 68. Also note the discussion of the 3Vs of Big Data appears to have first occurred in a 2001 by Doug Laney on the “Three Dimensional Data Challenge” published by META Group (now part of Gartner). 3 See how quickly the iPad/ tablets have been adopted at http://www.zdnet.com/1-in-4-tablet-owners-say-it-is-now-their-primary-computer-7000004770/ 4 See Geoff Miller’s “Slowing the Game Down” at http://www.beabetterhitter.com/text/mental/SlowingtheGameDown.htm . While it uses a baseball analogy, it provides useful advice to planners as well. 5 Ibid. 6 For a deeper understanding of what’s contributing to the explosion of data vs. just digital see the following link http://mashable.com/2012/06/22/data-created-ev- ery-minute/