Using OLAP to Improve Organizational Effectiveness – Part 2

February 28, 2010

This is the second in my series of 3 posts on using OLAP tools to improve the effectiveness of organizations. In Part 1 I discussed some background concepts and terminology. In this part, we’ll talk about some specific examples of how OLAP can have an impact in this area.

OLAP’s Impact on Organizational Effectiveness

How can an OLAP tool help improve an organization’s performance as measured against its objectives? Answering this question requires a greater understanding of how strategies and tactics are implemented within organizations. I’ll use a model of organizational effectiveness developed by Michael Beer to illustrate the implementation of strategies and tactics.

The picture below shows a simplified version of a model of organizational effectiveness developed by Michael Beer (Note on Organizational Effectiveness, 10). Business goals and strategy influence and are influenced by top management. Management determines and implements the proper organizational design to achieve the organization’s goals. The design of the organization, in turn, influences human resources attributes of the organization. Finally, these HR attributes directly impact organizational effectiveness.

Michael Beer Model

This simplified version of Michael Beer’s model is presented again below. Added to the model though, is the position of an OLAP tool in improving organizational effectiveness. OLAP technology exerts its influence on organizational effectiveness in three sections of the model:

Management
The Measurement and Reward Systems aspects of Organizational Design
The Coordination aspects of Human Resources.

Modified Michael Beer Model

While the impact of OLAP technology in each of the areas above is slightly different, each is related and shares a common trait: improvement in communication. Utilizing OLAP tools to improve communication requires a broad audience for their utilization. OLAP tools are traditionally utilized by analysts and managers. In this model, front-line employees become critical users of the tool as well. The wide-scale availability of web-based OLAP tools makes such organization-wide implementations cost-effective.

OLAP’s Impact on Organizational Effectiveness through Management

OLAP’s impact on organizational effectiveness through management is accomplished along traditional lines. OLAP tools facilitate the achievement of organizational objectives by giving management a more complete picture of the organization and its progress toward those objectives. Returning to the Dell example above, an OLAP tool can provide management with a quick and easy means for determining how employees are progressing on their required courses. Departments lagging behind on completing courses could be set back on track.

OLAP’s Impact on Organizational Effectiveness through Coordination aspects of Human Resources

Michael Beer describes coordination as it relates to organizational effectiveness as:

“The extent to which employees coordinate their decisions and actions across departments, functions, businesses, and national borders to improve the enterprise as a whole.” (Note on Organizational Effectiveness, 6)

OLAP’s ability to impact organizational effectiveness from a coordination standpoint stems from its ability to align the actions of individuals at all levels of the organization with the organization’s mission. This is accomplished by demonstrating how individual performance “rolls-up” to organizational performance.

A primary purpose of organizational objectives is to prompt employee coordination of actions and decisions by providing a common target. By relating these organizational objectives to individual employee actions, coordination of effort is increased. The 90% customer satisfaction objective referred to earlier provides an example. A well-designed OLAP cube could demonstrate to employees how quicker call resolution with no complaints leads to higher overall customer satisfaction. If management has done a good job setting objectives that are aligned with the mission of the organization, employees can now see how their effort leads to improved organizational effectiveness. This increased visibility of individual performance and its relationship to organizational performance should lead to increased coordination of effort.

OLAP’s Impact on Organizational Effectiveness through Measurement and Reward Systems

The greatest impact OLAP technology can have on organizational effectiveness is through its impact on measurement and reward systems.

OLAP’s Impact on Measurement and Reward Systems

A group of theories known collectively as Expectancy Theory stress the connection between effort and performance, performance and reward, and motivation. As the name implies, the concept of expectation is Important to Expectancy Theory. An expectation is an individual’s belief that an action on their part will lead to some particular result. The most widely known version of Expectancy Theory, the Vroom Model, stresses two important expectations that effect employee motivation:

The expectation that effort will lead to performance
The expectation that performance will lead to reward (Vecchio, 185).

OLAP technology can help improve employee expectations in both areas as illustrated below.

Effort and Performance

OLAP technology can be utilized to reinforce the connection between effort and performance to employees. The Vroom model postulates that the clearer the connection between employee effort and performance, the more likely it is that individuals will exert the desired effort. By emphasizing this connection, an OLAP tool can contribute to increased effort.

An OLAP cube showing performance at an individual employee level provides a powerful link between effort and performance. For instance, a company in a situation similar to the Dell example above may choose to implement a cube showing:

Total technical support calls
Total calls requiring a call-back
Total number of complaints
Number of minutes to resolve a call
Customer survey ratings of support representative performance.

Each of these measures could be tracked at an individual employee level across a variety of dimensions. The OLAP tool could then be utilized to communicate to employees:

Their level of individual performance
Their performance compared to targets and to organization averages.

With such specific, tangible measures, individuals would have immediate evidence on how their daily efforts lead to performance.

The link between effort and performance is also related to the coordination aspects of effectiveness covered above. As mentioned, an OLAP tool could be utilized to demonstrate to employees how their individual performance rolls-up into overall organizational performance.

Performance and Reward

OLAP technology can also be utilized to reinforce the connection between performance and reward. In addition to emphasizing the connection between effort and performance as shown above, the Vroom model also stresses the importance of employee expectations regarding performance and reward. Employee motivation may be adversely affected if employees do not believe that achieving a level of performance will result in reward. OLAP tools can contribute to improved organizational effectiveness by making it clear that designated levels of performance will indeed lead to associated rewards.

While this capability can provide a powerful incentive, it is critical that rewards be structured properly. Again, the main function of an OLAP tool in such a situation is to provide clear communication to employees of the link between performance and reward. If such a link does not exist, that is if performance does not lead to reward, utilizing an OLAP tool to communicate information on a non-existent link may be detrimental.

In the customer support example, an OLAP cube could be designed displaying customer survey ratings of an individual support person’s performance. A graphical indicator could show the level required to receive a performance bonus.

An employee could quickly see how increasing their performance leads to the achievement of the bonus. In this manner, an OLAP tool can provide a clear indication of the link between performance and reward.

Motivation

Overall, the Vroom model makes the following point: the more clear it is to each employee that Effort will lead to Performance and that Performance will lead to Reward, the higher the level of employee motivation. The role of OLAP technology in this process is to clarify to individual employees the relationship between Effort and Performance and between Performance and Reward.

Next Post…

In the next post, I’ll wrap up with a discussion on leveraging OLAP tools to improve employee Performance Feedback.

Written by TedWimmel · Filed Under Business & Leadership, Business Intelligence | 3 Comments

Mmmmm…cheesecake

February 24, 2010

I was sending a text message to my BFF Rose the other day. She was suggesting the Cheesecake Factory for a celebratory lunch. I wanted to respond in a way that let her know that my eyes were spinning as if I were in a cheesecake-induced, coma-like state and being led to my cheesecake master. My response was intended to be “Mmmmmm….cheesecake”. Thanks to my trusty iPhone auto-correct, the response came through as “Hmmmmm…cheesecake”. Clearly a HUGE difference! This response sent the message that I was thinking through the cheesecake option, though I had not yet settled on an opinion. The only response that would’ve been worse was had it auto-corrected to “Ummmm…cheesecake”, which would imply, “Really? You are thinking cheesecake?”

The whole cheesecake, text message snafu led me to think – HOW DEEP IS YOUR METADATA?? Consider the following:

Mmmmm = Yummy
Hmmmm = Thinking
Ummmm = Thinking

In your organization, how many variants do you have to the word Revenue? It’s really the same thing:

Invoiced Revenue = Stuff we sent a bill for
Sales Revenue = Value of an order
Recognized Revenue = $$ added to the financial statements

As you start to build your data warehouse, you may run into the same issue. How do you keep it all straight? Certainly in a word document or in your requirements document you’ve created the definition. But how accessible are those documents at the conclusion of the project? How are they distributed to the end-users? Are they in a user manual somewhere? How often is that manual consulted? When new reports are being created or new project teams are being established, are these documents reviewed at the beginning of the new effort? If there is a conflict in the definition, whom should be called to resolve the dispute? Sounding familiar??

LUCRUM partners with a great local company, Balanced Insight. Balanced Insight makes a product called Consensusthat allows you to track your metadata, organize it, and build data structures to support it. Imagine if you could produce a picture to show your customer how data is related. This picture allows them to confirm that “you’ve got it!”.

Consensus also allows you to see how the terms are defined and interconnected. Using a tool like Consensus allows you to set priorities and target the items that may “break” if a system is converted or taken off-line. I can’t imagine gathering requirements without using this tool!!

I don’t know if it will save my next iPhone auto-correct issue, but it sure would be helpful.

- Jodie

Written by Jodie Heflin · Filed Under Business Intelligence | 2 Comments

New Partner: TARGIT!

February 22, 2010

Have you heard of TARGIT? TARGIT is a suite of BI Tools geared toward getting you to BI “in the fewest clicks”. LUCRUM has always been a big believer in doing BI..Faster! This suite of tools is a great tool in our toolbox. We encourage you to learn more: http://www.targit.com/Products/TARGIT_Suite.aspx

Written by Jodie Heflin · Filed Under Business & Leadership, Featured, LUCRUM News | 2 Comments

Using OLAP to Improve Organizational Effectiveness – Part 1

February 21, 2010

OLAP tools have been widely available for years and are in use in a large number of organizations. They are typically deployed as speedy, easy-to-navigate reporting tools. With a little creativity though, this class of software can also be utilized in a very different manner.

As organizations struggle to communicate their objectives to employees and to align the activities of those employees with the objectives of the organization, they can get help from these same OLAP products. OLAP software can help by providing the capability to:

Improve management’s knowledge of progress on objectives
Improve employee coordination on efforts to achieve objectives
Communicate the link between employee effort and performance
Communicate the link between employee performance and reward
Improve employee performance feedback.

In this series of three posts, I’ll talk about the role OLAP tools can play in each of the areas above. But first, I’m going to start out with an introduction to the concept of Organizational Effectiveness. This introduction will give us a structure to frame the rest of the discussion.

I am not going to spend any time defining OLAP. If you’re interested, check here and here for some background and definitions.

Organizational Effectiveness Defined

Effectiveness is defined as simply having the intended outcome. In an organizational context, the intended outcome is the goal of the organization which is usually expressed in a mission statement. The Hierarchical Definition of Strategy provides a framework for defining and explaining these concepts and I am going to use it extensively in these posts.

Hierarchical Definition of Strategy

Explaining organizational effectiveness requires a discussion of business strategy and the Hierarchical Definition of Strategy provides a simple framework for this discussion. The Hierarchical Definition of Strategy is built on the concepts of Mission, Objectives, Strategies, and Tactics (Barney, 10). I’ve drawn a simple figure below to help explain this model:

An organization develops its objectives based on its mission while strategies and tactics provide specific details regarding the attainment of these objectives. In the Hierarchical model, the effectiveness of the organization can be determined by simply comparing actual performance to objectives. Michael Beer summarizes organizational effectiveness in this manner:

“An effective organization is one capable of implementing its strategy … A strategy is implemented effectively when people and groups in the organization work in a motivated, skilled, and coordinated manner on the appropriate tasks.” (Note on Organizational Effectiveness, 10)

In other words, the effectiveness of the organization is determined by its ability to achieve its objectives.

Hierarchical Definition of Strategy – Example

An example will help to clarify these concepts and make them a little more concrete. Dell Inc.’s Mission Statement is:

“Dell’s mission is to be the most successful computer company in the world at delivering the best customer experience in markets we serve.”

The high level nature of the statement, though necessary, makes it difficult for individual employees to apply it to their daily efforts. At the next level of the strategy hierarchy, Dell management has likely developed Objectives that will lead to the achievement of this mission. For instance, we can imagine that Dell has defined an objective to “Provide customer support with a customer approval rating of over 90%.” This supports their mission of “…delivering the best customer experience…” and provides employees with a tangible performance target.

The final two levels of the hierarchy are related to execution. Strategy is a means to accomplish an individual objective. Continuing with our imaginary Dell example, the strategy developed might be “Deliver the fastest, most accurate technical support in the industry.” This supports their objective in the sense that a firm delivering the fastest and most accurate technical support would very likely receive high approval ratings from customers. Tactics are execution oriented and exist at the lowest level of detail. In the Dell example, a tactic may be a requirement that all customer support personnel complete a certain set of technical and communication skill classes.

In the example developed above, Dell’s organizational effectiveness can be determined by comparing actual appraisals of their support services with their objective of a 90% approval rating.

Next Post…

Now that we’ve laid out some concepts and terms, we can move on to the heart of the discussion. In Part 2, I’ll dive into the details and talk about how utilization of an OLAP tool can help an organization become more effective.

Written by TedWimmel · Filed Under Business & Leadership, Business Intelligence | 3 Comments

Predictive Analytics & Healthcare

February 12, 2010

As a follow up regarding my post yesterday on Predictive Analytics, I wanted to bring attention to an article that Wired Magazine had last November on a predictive concept for “Modeling Human Drug Trials – Without the Human.” Using similar concepts, as well as rules which were indeed put in place by PHD’s, these folks replicated human trials which had taken 7 years of study – in about an hour. Yup, hit run on the computer, and an hour later the results popped up – which according to the article hit 2 of the 4 markers studied perfectly, the 3rd within an approved margin of error, and the 4th was just below the accepted margin of error. Ok, the computer model took 2 months to setup, and 1 hour to run, but running this model in 2 months and 1 hour, compared with the actual trial which involved thousands of people, millions of dollars, and 7 years? WOW, very very powerful, controverisal for sure, but very powerful. Here’s the link for your reading pleasure. http://www.wired.com/magazine/2009/11/ff_archimedes/…

Written by JodyDetzel · Filed Under Business & Leadership, Business Intelligence, LUCRUM News | 3 Comments

Microsoft Predictive Analytics!

February 11, 2010

Data Mining. Predictive Analytics. Quick what comes to mind? Expensive. Complicated. Statistical PHD required. Right? Not anymore, I’m very excited that Microsoft has entered this field with SQL 2008, and it appears could make a big difference regarding time, complexity and cost associated with leveraging your historical data to predict future events related to your organization.

Which products will sell best in a down economy?
Who is likely to be a loyal customer, and who is not?
Which treatment would be the most effective for this patient?

Answers/predictive models based not upon gut instinct – but upon the facts derived from the very real treasure trove of data locked up in transactional IT systems. Very cool concept. It may not be an iPad – but I think Microsoft’s predictive capabilities will have a big impact on their intended market nonetheless, and I’m very excited to be a part of it!

Written by JodyDetzel · Filed Under Business Intelligence, LUCRUM News | 2 Comments

The Value of Slowing Down: Go Slow to Go Fast!!

February 10, 2010

I once read about a Chinese mathematician who calculated complex scientific formulas by hand using a slide rule. He lamented the rising cadre of scientists who punched formulas into calculators and computers. Although they worked more quickly, the new generation of scientists often lost sight of the concepts behind the calculations. Without this fundamental understanding, the younger scientists often failed to grasp the significance of what they were doing or apply concepts in new ways to make new discoveries or effective designs.

This story parallels an area in Information Technology called “Business Intelligence.” Business Intelligence is also known as “Data Warehousing” and “Executive Information Systems” with dash boards or digital cockpits. The IT organization provides a rich repository of data for the business knowledge workers. Providing data has become so important; in addition, the tools leveraged have become more and more rich in functionality. And yet, the number of business users truly leveraging this kind of technology-oriented business information environment lags the productivity that the organization could receive. Simple questions like: who are my best customers and why? What’s my best product and what is its margin contribution? Why is my market share in a particular geography increasing where in another market it’s declining? How can I get my business results information faster so I can be more informed on the ever-changing aspects of the market? A user says, I can make a lot of informed decisions….how can I make even more of them instead of hire more decision-makers? The business and market questions go on and on and on.

As IT professionals, we are used to being held accountable to deadlines with ever changing resources and requirements. In the world of Decision-Making, as data warehousing managers, we often are rushing to meet these same deadlines. Often the deadlines and deliverables overshadow the underlying purpose for building the data warehouse. The good thing about bad times is that they force us to slow down and painstakingly evaluate what we are doing. So, although there are dark clouds ahead, there is a silver lining in the reality of our environment in having to do “more” with “less” resources.

Here are 3 tips to consider making your Data Warehousing environment even more “ready” for business decision-makers.

Meet with the Business Decision-Makers frequently. I am suggesting that a weekly meeting at a minimum would be beneficial in order to review their data, listen carefully to understand what data they are really using, and what data they may be leaving behind. Is the data they are leaving behind the result of not understanding how to use the data, is the data no longer relevant to their decisions, or perhaps the data is too summarized or too detailed?
Document the business flow of the data graphically using business terms, not technology metadata definitions. Distribute the business document to all business and IT users so that everyone really knows how the data is being used in the context of business. Too often, we revert to memorizing the technical definitions and only use them. We lose the business context and as new people join the data analysis, the true business definitions are lost.
Proactively have discussions sponsored by IT with the Business Users about the cleanliness of the data and how IT is transforming the data. Show them the techniques that you are using to cleanse the data and transform it so that there’s a common repository of data that they can use. The more the Business Users understand what you do in context of the IT problem, the more they will provide their insight into how the data is most meaningful to use.

Chinese “Business Intelligence” Proverb: If you plan for one year, plant rice. If you plan for 10 years, plant trees. If you plan for 100 years, educate mankind.

Written by John Bostick · Filed Under Business & Leadership | 2 Comments

Smart Grid Reporting

February 10, 2010

I’ve been working in and around the Utility industry for the last 9 years or so. In order to have meaningful conversations with my customers and in order to create solutions that are meaningful to them I subscribe to some industry publications. One such publication is IntelligentUtility. This morning an article caught my eye. In it, Bart Thielbar discusses his mother’s reaction to receiving Smart Grid technology in her home.

For those that haven’t heard, the Smart Grid is the biggest technology investment being made by Utility IT managers. The concept is that your local energy provider will be bringing Business Intelligence into your home. You’ll have a device in say your kitchen that tells you how much electricity you are using when you run your dishwasher. It may even suggest alternate times to run your dishwasher. Ultimately it is believed that you will make better decisions on where to set your thermostat, when to run your washer and dryer and also illuminate you to how much energy is truly being consumed by that hallway chandelier. Additionally, the utility company can also start to do meter reads from their headquarters, thus eliminating meter readers…and also can increase the speed by which new service can be turned on and service can be disconnected for late payments, which will eliminate some service personnel. The idea is that it provides for tremendous cost savings for the utility and potential cost savings to the consumer if behavior is changed. (There are other benefits and pitfalls as well…too numerous to mention.)

Bart’s mother’s response when her son explained all of this to her was very simple, “Can’t we just look around the house and turn off lights that aren’t being used, adjust the thermostat or replace appliances that are less efficient?” Ah yes…having BI for the sake of BI. How many times have you seen an implementation of a dashboard or a new report that was projected to save $$ that just became a rather large paperweight or unused app? If you aren’t planning on using the information to change any behavior then why measure it in the first place?

I’ve seen countless business intelligence efforts fail simply because the users weren’t engaged to create a solution that “fit” the problem. The best BI initiatives are simple, focused, and highly customer centric. Sure the Smart Grid has a lot of benefit and cost savings for the utility, but how many customers are truly going to take those data points and make different decisions in their home? My guess…not as many as you think. As with any technology, it will be a novelty at first and used a lot the month after a high bill. Companies are recognizing this and starting to make adjustments to their new products. So rather than have a consumer look at some guages and dials and decide what to do next, your next dishwasher may be able to tap into the Smart Grid and know when to run the next load of dishes. Perhaps we’ll have a setting that says “Energy Efficient” that will read the rate structure and turn itself on at 3AM rather than run right now.

Is your BI initiative just a bunch of guages and dials? Or is it truly changing the behavior of your users and customers?

– Jodie

If you are interested in other Smart Grid discussions, this blog summarizes some new ideas out there and links to several other sites. http://knowledgeproblem.com/2009/06/30/smart-grid-device-update/

Written by Jodie Heflin · Filed Under Business Intelligence, Featured | 5 Comments

Turducken (Slicing customers differently)

February 5, 2010

** This great blog was originally posted on 2/26/2008 **

—————————————————————————————–

Talk about complexity, I will never forget the day that I first learned about Turducken! For those of you who don’t know, a Turducken is exactly as it sounds; a chicken stuffed in a duck, stuffed in a turkey (http://en.wikipedia.org/wiki/Turducken). You know, the classical hierarchal relationship of meat taken to the extreme. They go for about US $100 after shipping, but the adventurer can stuff their own. When I think of customers I sometimes think of the Turducken – Let me break this down a bit.

I have always thought that the most important thing that a company can do is to keep their customers. Makes sense to me, after all there is that great concept that its “X times as expensive to attract a new customer than to keep one”. Now don’t get me wrong, I would walk on broken glass without shoes uphill in the snow to help my customer with their Oracle Forms 4.5 on top of a My Sql implementation in a Citrix environment running off of a 1982 walkman radio. But when businesses say customers, they know what they are really talking about. But let’s decompose this a bit more.

You all know those sayings – the ones we all know and love…

Customers are great!
The customer is always right!
Customers may not be right but they are never wrong!
Our Customers are number 1!

Well, over the years I have come to modify that statement a bit and here’s why. “Customer” is a large group to take into analysis at face value. Customers are a complex group. Companies shell out a lot of moolah to understand this group. After all, this group is responsible for the business’ inertia. When companies wish to understand who their customers are, they don’t simply run a ‘customer listing’ and read through it while attending some boring IT meetings about data governance. They spend big money and they head down the road that ultimately leads to … Segmentation.

Segmentation is the classification or taxonomy of the business’ customers. They are usually based on habits or lifestyles plus some kind of loyalty factor. This data is usually derived by their purchase behavior – at the purchase or cart level. There you go; you now have X-subsets of customer. The theory is that each has their own set of core beliefs, common principles and behaviors. The goal is to then approach them in a more intimate manner, allowing both a level of customization and attaining some economies of scale.

However, let’s take another look at customers. This time lets add two driving forces; Business Intelligence and a potential recession. The impending economic fear will be the catalyst for innovation, as it always is. To maintain market share or to at least out pace our competition, companies will need to do something different and the conditions seem to be perfect. Lets pick up the story from above and write the ending.

Tom is returning from lunch when he just happens to walk past the marketing folks. They are talking about how to approach the “young and fun city dwellers” segment and how that must be different than the “impoverished with kids in college” segment. As he rounds the corner, he passes the finance folks as they make mention that yesterday’s margins are down 3.2% and that translates to a need for some kind of new report because it will impact profitability. Almost back to his office, he passes the sales folks who are chattering about how the “young and fun city dweller” are buying more and that even the “impoverished with kids in college” seemed to spend their tax refunds this week. And it hits him…

What if we combine this data? What if we work together? What if we look at customer loyalty and segmentation, but we add a dimension called ‘profitability’? Like reading the last 20 pages in a good novel, Tom plays this through and nets out as follows:

If we look at our segmentation of customers, within each group:

We have customers who are loyal and profitable – these are out best customers. Our number one job is to keep these customers. Things I can do are; understand who they are and engage them on a more intimate level, customized for them (special offerings, internet bindings, tools, tips, personalized greeting, etc…), surround them with rewards and incentives (redirecting the money spent on the next group).

We have customers who are not loyal and not profitable – why do we waste our resources on these folks? Or maybe it makes sense to cut them off completely. Recently Sprint gave their top 1,000 problem customers the boot (http://www.washingtonpost.com/wp-dyn/content/article/2007/07/06/AR2007070602131.html). I’m not going to mention the online movie delivery service I use, but it seems the more I rent the longer it takes to get my movies. If I rent only a few, I get really good service. Coincidence?

Now we need to understand how to make our profitable but non-loyal customers more loyal. How can we deliver better service, what promotes loyalty, maybe we should ask this subset?

And we need to understand how to make our non profitable but loyal customers more profitable. Can we push higher margin items, does it make sense to engage them with alternatives, blend costs/products to move margin?

Of course this is only the beginning. BI can bring a depth of understanding to those who look across the enterprise to bring data together. The above scenario is only the tip of the ice berg – it’s the beginning point of an in-depth analysis that will deliver real and actionable information. Look for information to unhide and your customers will flock to your side!

Now for the perfect customer saying, feel free to quote me on this:

“Our best customers are best!”

It’s the perfect storm out there and BI just might be the generator that keeps your business’ lights on. If you do lose power, please make sure to eat up that Turducken – it only lasts a day in the fridge!

~ Scott Felten

Written by Scott Felten · Filed Under Business Intelligence | 4 Comments

CEO Tweets Resignation

February 4, 2010

@OpenJonathan Today’s my last day at Sun. I’ll miss it. Seems only fitting to end on a #haiku. Financial crisis/Stalled too many customers/CEO no more

That’s the last Tweet from Jonathan Schwartz, Sun’s former CEO. It was preceeded by his final blog just 1 week earlier. http://blogs.sun.com/jonathan/entry/where_life_takes_me_next

In the time of Social Media, how we get the news is not nearly as riveting as how FAST we get news. Via Facebook you get birth announcements, wedding invitations, divorce annoucements…via LinkedIn yo usee job changes and now via Twitter – resignations. All real time. Faster than you can spill the announcement to your immediate family, you can notify hundreds/thousands (or in Jonathan Schwartz’s 9107 people).

If you are a company, how do you manage this flow of communication? More importantly how do you exploit this communication and how do you track the effectiveness? I think that the next generation of BI will track social media impact to financial results and/or to customer satisfaction. Imagine if you could track the ROI of your marketing efforts! If a Marketer’s MBO could include # of tweets per day and % increase of profit and truly be tied together!! Ah…dreamy

CEO Dashboard of the future

Good luck Jonathan!