KlipBlog / thoughts.

After writing last month's article where we considered how different time frames impact comparative metrics, I thought it would be interesting to follow that up with a look at the period of your time frames. Just like a sine wave, these types of time frames are characterized by their repeating cycle - allowing you to compare the ebb and flow of your trend more accurately, chronologically speaking.

So what counts?

A commonly used measure of time in business reporting is the 30 day cycle. While the reporting periods in each cycle can be broken up in discrete chunks, a 30 day time frame, consisting of just over 4 weeks makes for poor analysis. And that all boils down to the fact that your 30 day schedule may begin on a Monday, but your last reporting day will be a Tuesday, with your next reporting cycle beginning on a Wednesday. So, in fact, the periodicity is not following a natural cycle.

Let's compare that to a 24 hour, 7 day, or 28 day reporting cycle. This consistent time frame will, for example, always begin on a Monday and end on a Sunday. The data or trendline now lends itself to comparison - consistently every reporting period.

Towards an objective reporting cycle

The idea behind consistent time frames is that you break each monitoring period into discrete, equal chunks. Consistent time frames offer a more objective way to monitor and compare your metrics. Not only that, but each day in each cycle is parallel to previous cycles. Spotting patterns becomes much easier compared to the 30 day cycle, since you are essentially comparing apples to apples, Mondays to Mondays.

Is symmetrical reporting for everyone?

The answer is simple: no. Setting up time frames for your KPI dashboard is about knowing the best way to monitor your metrics in order to increase understanding and, in turn, improve your decision making. Your KPIs need to speak to your organization's goals and improve your ability to achieve those goals. Rather than advocating blind adoption of consistent reporting periods, this article is about adding another tool (or question) to your KPI tool belt.

13 months, each 28 days does seem to add up quite nicely. Food for thought!

Missed our article last month? Don't worry, here it is:
Business Reporting - Time frames and comparison metrics.

While you're here, why not check out some of these other interesting articles:
Top Ten Call Center Metrics
Top Ten Sales Metrics
Top Ten Inventory/Warehouse Metrics

Today we are launching a new "What is" series of short articles. Check out the first three in our series:

This series of articles will introduce many of the key terms and concepts used within the BI industry. You will hear these terms bantered about so casually that you might not have stopped to think about what they really mean. Sometimes a simple definition will change your perspective on terms you use everyday.

Stay tuned for more articles!

It's an on going debate. Does use of social media as a way to communicate, support and engage prospects and customers demonstrate ROI? As a business intelligence company, not having a firm grip on that answer makes us uneasy to say the least.

We like to get a sense of how you - the customer, user and fan - prefer to stay in touch with the companies you deal with. We've intentionally left out the "traditional" face-to-face and phone channels, because we'd prefer to focus purely on social media.

We'll digest the results of this poll, along with existing opinions, and share our findings.

“Managing through the rear view mirror. A dangerous practice for any business!
You’d never drive only looking backwards.”

You've heard lines like this one before…it has all the right ingredients to be remembered and retold. It's catchy, it paints a clear picture, adds a dash of FUD (fear, uncertainty, and doubt), and may even be confused with true wisdom!

Let’s debunk this.

Let’s frame the story by discussing measured data, environmental factors, and how decisions get made.

Measured data (we discussed measures, metrics and KPIs a few months ago), or measurements are values associated with an agreed upon standard (such as km/h). For example, I’m driving at a speed of 50km/h. This is a “real-time” measurement, but it could have been; Yesterday, my top speed was 120km/h, or my average trip speed is 35km/h for the past 30 minutes. Measured data is historical no matter how you spin it. However, knowing when the data was measured is a critical factor that often gets left out of the “rear-view mirror” picture.

Let’s say you’re driving in an unfamiliar neighborhood. You know from experience (historical data) that on a street of this size, with children playing outside, you should probably not exceed 40km/h. Ahead, a road-sign warns of a school zone: 25km/h max. This is new data, and it will cause you to adjust your speed.

In that example, the sign is an environmental factor. When you’re making business decisions, environmental factors might include competitive threats, economic opportunities, or regulatory changes. A simple way to differentiate might be to think of these as the external factors – the O and T of your SWOT analysis. Don’t confuse environmental with a sudden snow storm…although that too, should cause you to drive differently.

Provided you’re not flipping a coin, decision making is, of course, much more involved. Past experiences (measured historical data) are combined with cognitive and personal biases (know any folks at your office?), environmental factors, and time constraints to influence the choices people make. Read up at Wikipedia - interesting stuff.

I suspect that much of where the rear-view mirror warning comes from has to do with using an appropriate timeframe. My speedometer tells me how fast I’m going now, not yesterday – yes, that would indeed be dangerous. Is that the issue?

Ideally, and this is possible using today’s dashboards and BI software, you would have the following decision support at your disposal:

1. Current performance (real-time or near-real-time)
2. Timeframe-appropriate historical performance data
3. Predictive or conditional alerts (based on goals, history, or environmental factors)

Let’s add a pre-emptive note about predictive analytics – a wonderfully powerful tool to assist with future decision making. Keep in mind though, that predictive models exploit patterns found in historical and transactional data to identify risks and opportunities for future decision guidance.

Nobody has a crystal ball. However, a keen understanding of your history, an understanding of trends and cycles, awareness of your environmental factors, and smart, analytical thinking will help you predict what's around the next corner.

See also: Anatomy of a KPI

I have a well-referenced book in my library at work, Wayne Eckerson's "Performance Dashboards." Although it is now about five years old—and aging, given how quickly the BI industry is advancing—I continue to use it and discover new ideas.

If you've got his book, check out chapter 6. It classifies three types of performance dashboards: Operational, Tactical, and Strategic.

In a nutshell, Wayne defines Operational Dashboards as being focused on exception alerting, based on real-time or transactional data. It's up to the user or a script to then act upon this opportunity or issue. OK, I'm with him so far.

Tactical Dashboards display data that is not quite as real-time as operational dashboards, and are generally not evaluated against absolute conditions. Contextual information, and the ability to explore the data, tends to guide users to the decision process.

Strategic Dashboards, according to Wayne, track performance against high-level objectives. As a result, these dashboards tend to summarize performance over the past month, quarter, or year. Strategic objectives are usually also the result of many underlying metrics, and require social analysis to digest properly.

At Klipfolio, we tend to use the terms operational and tactical interchangeably. If, instead of using the naming conventions, we simply arrange these dashboards on a time continuum—real-time, daily, and monthly—this aligns better with what's actually happening. (For the sake of definition, let's ignore how frequently the data gets refreshed, because after all, each of these dashboards can accept real-time data.)

The real-time dashboard is likely to be quite volatile, its data changing frequently throughout the day, but it can be fully trusted to present an accurate snapshot of what is happening right now. This is your "speedometer." It's also one of the most easily understood dashboards, applicable to a wide range of employees for various tasks. The logic for this type of a dashboard is simple. But don't mistake simple and easy for less value. Would you want to drive without your speedometer?

The daily dashboard settles down considerably. We're now looking at an aggregated, summarized, or averaged view of data. Because this presentation tends to smooth the outliers, we can start comparing it against historical values, benchmarks, and goals without having a panic attack every time the data refreshes. This would be your "average trip fuel consumption" metric. The daily dashboard allows you to make informed decisions. Because it's usually a collection of real-time data points over time, users of this dashboard have a little bit of depth to play with, and they can ask questions of the data.

The monthly dashboard is the most difficult one to influence. It's made up of many data points, rolled up into a key business metric, a reflection of many processes and initiatives. Although this type of dashboard or scorecard is most associated with executive management, it is tremendously valuable to communicate these KPIs to the entire organization, to make sure everyone's rowing in the same direction. Because of the voluminous data that feeds these dashboards, the requirement to ask questions of the data is of utmost importance. The analysis and commentary on these values is often as important as the metric itself.

Given the persistent nature of Klipfolio Dashboard, we tend to see more of the real-time and daily dashboards (or according to Wayne's definitions, the operational and tactical dashboards). And for that matter, we find that customers consider the terms real-time, operational and tactical analogous as well. 

Wayne goes on to describe which dashboards tend to be the most popular, and which ones amass the most users. Five years ago, strategic dashboards captured the popularity vote (in the number of firms having deployed this type). However, with the growth of operational BI outpacing traditional BI, I wonder if it's still in top spot. Certainly there is no question about which dashboards capture the greatest audience ... you just need to follow the pyramid of employment to know that tactical and operational dashboards out-number strategic ones. Some of our customer deployments range in the tens of thousands.

No matter what you call them, performance dashboards are seeing incredible growth. And, as the accessibility, ease of use, self-service, and costs become more competitive, this trend is not likely to slow down.

What are your thoughts on dashboard types and naming conventions? Let us know.

This past Friday was an anxious day - it would be for any parent - our three year old daughter was scheduled for an adenoid-tonsillectomy - a good thing, trust me. I'll cut that part of my story short, because it was wonderfully uneventful and a success. 

However, taped on a wall outside of her recovery room, were a dozen printouts containing charts, numbers and indicators. They looked like key performance indicators and of-course, they caught my eye. Hospital KPIs are of particular interest currently because we're working with one of Canada's largest health care providers, helping them expose, and track operational metrics in various emergency departments.

These key performance indicators were a little less exciting, but did have all the right tactical measurements and components to be valuable. The majority of these print-outs were displaying on-time surgery starts. In other words, how many surgeries had started on time yesterday, for the past 30 days and YTD. The metrics were sliced by type of surgery, and compared actual values against historical averages, industry benchmarks and of course their target metric. 

Quite commendable really ... but why kill all those trees? Also, this means someone has to gather the information, update the spreadsheet, print out multiple copies, then walk around the hospital taping the updated KPIs to the wall outside each recovery room.

Just think of all the time that could be saved, and the additional impact if this information was presented using a KPI Dashboard on a large flat screen monitor to display to the the latest KPIs, or by making the information available to consultants and medical staff via their mobile device?

What are your thoughts? What are the best hospitals doing to measure their performance and more importantly expose these KPIs to their staff?

Allan

PS: Cardiology ranked in the middle of the pack ... late about 30% of the time. Ah, the broken hearts.

Happy Valentines Day!

Pervasive access to data

The next twelve months will see operational BI become more pervasive within the enterprise, at all levels, driven by the increased accessibility offered by mobile devices such as iPhones, iPads, Blackberrys and Google Android devices. Likewise, Business Intelligence and Dashboard vendors will continue to optimise the user experience to leverage these mobile devices as viable portals for viewing and interacting with critical data.

To the cloud!

We will see the introduction of more SaaS and cloud based offerings that will make BI affordable and more accessible to the small, medium enterprise (SME) with a pay-per-use model, removing the capital expense of an on premise BI deployment.

Industry specialization

The change in the cost and deployment model will also see the emergence of niche vendors specializing on BI for a specific vertical, or audience (i.e. Healthcare). The push for more real-time BI metrics will continue as cost for storage and CPU cycles fall and capacity and speed increase.

 All of these trends – mobile access, investments in ease of use and self-service and a lower cost barrier will work in concert to bring KPIs and operational BI to a greater audience. And that’s something we’re excited about because there are direct correlations between broad awareness of performance data and overall company performance.

To the uninitiated a call center could be viewed as a group of individuals randomly answering calls. However, nothing could be further from the truth. No matter what the size of your business the call center, whether it is a sales or service operation, is usually the first point of contact for most prospects or customers and it is this critical touch point that can make a difference in the perception of your company image.

To be effective a call center has to be an integral part of a company’s strategic plan with clear goals and objectives than can be measured and managed. The importance of continuous performance evaluation and strategic planning in a call center cannot be underestimated and the relevant KPI Key performance indicators have to be identified and tracked to measure the overall cost or contribution to the business.

Balancing Customer and Business metrics

Managing an effective call center is complex; they are dynamic, requiring information and data to be on hand when needed. Call center metrics are a balance of customer satisfaction and business process and are heavily interrelated. A KPI Dashboard should be used as part of a balanced scorecard approach for measuring overall performance. Customers want a good experience, short wait times, knowledgeable agents, resolution to inquiries in single call without long periods on hold. Your business is looking to maximise the revenue per call, while minimizing its costs. While also looking to leverage opportunities to up-sell products and services, keep customer satisfaction levels high and keep agents busy.

Keeping team and business priorities front and center

A KPI Dashboard optimised for the call center provides a simplified, actionable visualisation of the operational business data to front line agents, supervisors and managers so they can see trends, manage exceptions and take corrective action to achieve business objectives and keep callers happy. Providing agents with call statistics from the phone system in addition to being able see and search on up-to-date information from enterprise CRM or ERP applications from their desktop, agents never lose sight of what they are being measured against, how they are performing and can manage their behaviour accordingly.

We see from our customers that individual’s actions are aligned with, and contribute to, team goals that are driven by business strategies underlying the key performance indicators in front of them and the ROI of a Dashboard is calculated in weeks, not months or years.

@Stray__Cat, a BI expert in Italy who I follow on twitter, published a blog post called Measures, Metrics and KPIs. As you know, anything KPI related peaks my interest. This post aimed to clarifying these terms, and as we've got a similar initiative underway, I thought I'd jump into the discussion with my own thoughts... I encourage you to read his thoughts as well, and let us both know what you think.

What is a measure?

Definition: A measure is an agreed upon concept of quantification. It's a standard, which when "measurements" or "values" are associated, allows for a common language and a basis for comparison.
Example: Speed expressed in km/h, or temperature expressed in ºC, or beer as a pint.

What is a metric?

Definition: IMHO, a measure and a metric are the same thing. And according to the Oxford dictionary, the word measure is derived from the Latin "metiri". Having said that however, in speaking with a number of my colleagues, there seems to be a subtle difference in that the term metric has more of a goal or performance nuance to it, as opposed to the fundamental or unit specific term measure.
Example: Speed limit of 50 km/h, or the boiling temperature of 100 ºC, or ordering half a pint of beer.

What is a KPI key performance indicator?

Definition: KPIs are measurable industry, department or task relevant performance metrics that are evaluated over a specified time period, and compared against acceptable norms, past performance or targets.
Example: Currently we are driving at 60 km/h (10 km/h higher than the posted speed limit of 50 km/h), or the average water temperature over the past week was 95 ºC (5 ºC lower than the target temperature of 100 ºC), or average pints per patron per visit at our pub this month is 1.6 (compared to the local pub average of 1.4ppv and last month's average of 1.3ppv).

This is fun! On a related note, check out "The Anatomy of a KPI".

Many companies never realize the expected returns from their CRM implementation. There is no magic increase in sales, no increase in the customer satisfaction index following the implementation of a shiny new application.

CRM is not just an application you buy and install; it is also integral to business ethos, an essential part of its DNA that touches every part of the organization, is understood, and practiced by its employees.

A well planned and executed CRM implementation can bring huge returns. An IDC study relating to the ROI of successful CRM implementations found companies have yielded returns ranging from 16% to more than 1000%. Over half of the companies surveyed yielded returns of between 50% and 500%. Consider those metrics for a moment. They are nothing short of staggering.

Consider now that Gartner estimates that 60% of CRM implementations fail after the go-live date, usually fizzling out over time as users fail to maintain the information and adoption rates drop. It then becomes a matter of time before the system is abandoned, or worse, the information being gathered from it is out of date and inaccurate.

Some of the main reasons for poor implementation are cited as;

• Failure to define business objectives or develop processes for meeting objectives
• Failure to conduct ongoing reviews of application performance against objectives
• Not setting specific metrics and incentives for users
• Under estimating end user training requirements

How can a KPI dashboard help application adoption?

Definition of business objectives

As part of the initial project scope, the business objectives for each department that will be affected by the implementation should be agreed. This will provide a clear definition of the KPIs that should be tracked and measured using a KPI dashboard .

Ongoing review of performance against objectives

A KPI dashboard provides right-time visibility of key metrics, and progress against them, highlighting trends and additional insight to aid better decision making.

Specific metrics and incentives for users

Each department should have a clear understanding of the metrics that will change after the implementation of a CRM system. Providing users a KPI dashboard enables them to track their individual or the department’s progress against business goals. It can also increase productivity by simplifying workflow. In a sales environment a dashboard can increase productivity by up to 85% simply by integrating into the sales workflow, reducing the time taken to access information.

If we take the example of checking for a new lead;

1: The dashboard provides an alert as the new lead arrives in the SFA application.

2: Clicking on the lead in the dashboard application launches the SFA application and opens the appropriate record for review.

3: This eliminates the need to launch and login to the SFA to check for new leads periodically saving both  time and the number of clicks required to access information.

The table below illustrates some of the savings in time for regular tasks using Klipfolio Dashboard to integrate into the workflow.

Giving users the ability to make tactical decisions based on up-to-date information from the CRM application, and affect business outcome increases personal productivity and application adoption.

Under estimating end user training requirements

According to a recent IBM/MIT survey, adoption of new technology is hindered, not by cost or complexity, but by human nature. This inbuilt resistance to change highlights the importance of training for new users. Using KPI dashboard to reduce the learning curve for new users by makes it easy to access a customer record or be directed to the correct page for data entry.

It is important that new users understand how it will benefit their role as well as the overall benefits to the business. A KPI dashboard achieves this by providing relevant business information, improved visibility of key metrics and increased productivity.

Every business is dynamic; change in process or metrics that measure its success are inevitable. Integrating a KPI dashboard as part of a new or existing deployment provides focus on the definition of objectives and metrics, provides visibility and feedback on the effectiveness of these metrics and progress against them, and most importantly, can increase application adoption by streamlining workflow and making it easier to use.

What are your thoughts regarding CRM adoption, and the use of dashboards to improve adoption?

In a call yesterday with a long-standing customer of ours - we were discussing target users and use-cases – an interesting albeit obvious thought was raised: The need to consolidate and summarize data and metrics increases as you move up the corporate hierarchy … Makes sense. The breadth of responsibility a manager or executive has, makes it close to impossible to analyze all information in depth.

So, it becomes important then to understand exactly how relevant information will be summarized and presented. Let me introduce some FUD (fear, uncertainty and doubt) to the discussion.

1. Truth and Untruth. You could argue that you’re distilling the information down to its essence; however, the more realistic scenario is that you are abstracting or blending the data. For example: Out of 8 regions, 5 sold on target, 1 excelled, and 2 performed well below plan. Does it make sense to average these into a single number? Perhaps the better solution here is to manage by exception, and highlight the best and worst performers (the things that actually require action).

2. Analyzing vs Monitoring. My car has a function on the instrument cluster that can tell me what my fuel consumption is per kilometer. It’s taught me that when I accelerate hard, I use an incredible amount of fuel, or that I can conserve fuel by lowering my highway speed. This is good, but once I know this, it’s time to watch my speedometer – if I don’t I’m asking for trouble. Akin to analytical and operational dashboards, I see too many managers and executives pouring over analytical BI tools, uncovering trends, however unaware of their operational “speed” or “direction”. Here is my rule of thumb: Analysis is best completed in intense exploratory sessions, however, just like your speedometer, operational metrics are best kept peripherally visible whenever you’re moving.

3. Data Creep. Feature creep, is a term most product managers are likely familiar with, but it is just as common for dashboards. Abstracting the entire business to a single red/amber/green traffic light metric is absurd. Equally, so is having 4 tabs loaded with indicators, dials, gauges and charts to provide a summarized view. As my colleagues will vouch for, I’m a big fan of the one-page dashboard. I think it’s a good constraint to help users decide what to keep and more importantly what not to keep. With every metric, ask the following questions: Does it align with business/departmental goals, is it actionable, is it timely and accurate and last but not least, does it provide context such that the metric can be understood. Learn more about this in our article: KPIs, Dashboards and Operational Metrics.

So, as you’re designing and developing dashboards for executive or management use, you will have to weigh a few considerations. Think about the use case, the requirements and start small. I’m sure you’ll remove most of the fear, uncertainty and doubt clouding executive dashboards. If you have questions, don’t hesitate to connect … awille@klipfolio.com.

Today, rapid changes in technology are nothing new. However, the adoption of new or emerging technology is being hindered, not by cost or complexity, but by human nature. Our inbuilt resistance to change (or at least some change according to Dan and Chip Heath, authors of “Switch”) is cited as a barrier to the adoption of business intelligence and analytics according to an IBM/MIT study, which surveyed nearly 3,000 executives and business analysts from 108 countries and 30 industries.

According to the survey, the adoption barriers organizations face most are related to management and culture rather than data and technology.

The top obstacles to widespread corporate adoption and use of BI and analytics are cited as:

38% Lack of understanding of how to use analytics to improve the business
34% Lack of bandwidth due to competing priorities
28% Lack of skills internally in the line of business
23% Existing culture does not encourage sharing information

“Organizations that use analytics to tackle their biggest challenges are able to overcome seemingly intractable cultural challenges and, at the same time, refine their data and governance approaches” the study notes. A few years ago, we wrote about user adoption challenges in an article we entitled “Dashboards and the Human Condition ” and identified 3 rules to keep in mind when designing and deploying BI and dashboard applications.

Despite the “ostrich” outlook of workers collectively burying their heads in the sand, the future for analytics adoption has tremendous potential. Organizations are expecting to gain more value and extract more information through more advanced data simulation, visualization and dashboard techniques within the next 24 months.

Download the full report. Analytics:The new path to value.

KPI's and car repairs

As a vehicle owner it’s safe to say that at some point your pride and joy will be involved in a collision. Whether it was your own misjudgment or someone else's that caused the mishap, the end result is the same.  It will have to go to the body shop for repair. The exchange between vehicle owner and repair shop usually follows the same script “how long will it take to repair?” asks the owner “depends on how long it takes to get the parts and what else we find” is the reply.

It’s easy to forget that as it is a bricks-and-mortar business, where all stages in the repair process are manual, executed by skilled automotive repair technicians, rather than an automated or “high tech” environment, that they too are using KPI’s to increase production throughput, increase earnings and keep customers and insurance companies happy.

It was something I had never considered until I stumbled across a fascinating blog post by Chris Sheehy of the Auto Body Consulting Group.

He explains in his article how the automotive repair industry use a KPI called Cycle-Time and why its one of the most important KPI’s they track. The industry standard is around 10 days which is averaged out from minor scrapes to “train wrecks”.

The industry also looks at it from a production and a customer perspective, which varies the formula for the calculation.

Production Biased Cycle Time: The average number of calendar days elapsed from the date the vehicle was received at their business, to the date the repairs were completed.

Customer Biased Cycle Time: The average number of calendar days elapsed from the date the vehicle was received at their business, to the date the customer took delivery.

Analyzing the variance in Cycle Time between Production and Customer bias enables a shop to improve its workflow process, get cars back to their customers sooner and reduce costs to insurers through shorter rental costs. This in turn helps to provide am improved customer experience and lower insurance premiums.

It’s reassuring to know KPI’s are not only important to large enterprises but they also apply to the local body shop.

Next time my car is in the shop for repair I will be sure to ask how they calculate cycle time!

The entire article can be read at Chris’s blog page http://bit.ly/jakSg

Data to the people! I can hear it now, chants filling corporate hallways.

The phrase “knowledge is power” was first used by Sir Francis Bacon in 1597. It also sums up the approach to the accessibility of business data in most organisations today. Easy access to relevant business data is still the privilege of executives in the C suite, along with the keys to the executive washroom.

Today's successful companies believe in a data democracy. Making data pervasive across an organization is a powerful tool for measuring performance against corporate goals and key performance indicators (KPI) that have been agreed by management and communicated to all employees. Making “right time” information available to departments and individuals empowers them to act on this information in relation to corporate or departmental goals.

That's why we believe that providing the right data, at the right level, through the deployment and proper use of dashboards is as much about monitoring performance as it is about ensuring the goals and targets are front and center.

Dashboards also pave the way for a performance culture, especially if dashboards are deployed across the entire enterprise at all operational levels. KPI Dashboards are more able to effectively leverage the strengths of the whole organization by giving every employee the power to contribute to and improve on KPI’s that have been set by management.

Performance, action and accountability with respect to departmental or corporate goals has to be part of the daily routine. Dashboards make this possible. A performance culture also has less obvious benefits:

• Companies that foster an open sharing of metrics, encourage a passion for the business.
• Employees are more engaged, more loyal and ultimately more focused on the right activities.
• It increases competitive advantage by helping to transform every employee into a “knowledge worker” equipped to make better, timely decisions to support company and customer objectives.
• It Improves operational efficiency by identifying new best practices and driving those practices from the bottom up as well as the top down
• And perhaps the most interesting point, a performance culture goes a long way in eliminating egos, arrogance, fear and politics.

Gone are the days where decisions are made by those with the biggest egos. Gone are the days where only a few people hold the data and can manipulate it. It’s true, knowledge is power, but a shared knowledge of performance against KPI’s for everyone, enables an organization to be more powerful.

I wanted to sum up the findings in an Aberdeen Group report published a few weeks ago, as their research highlights big differences in the success of companies that use Operational BI and those who don't.

I don’t like to use the phrase “I told you so”, but, as someone who evangelizes the business benefits of operational BI this comes as no surprise. For those of you that are sitting on the fence, the Aberdeen Group research provides another independent proof point that the greater the awareness and visibly of real-time performance metrics increases the ability of a company to grow revenue, increase customer satisfaction and stay ahead of their competitors by connecting operational decision makers with operational data.

A total of 260 global companies took part in the study. Here are some of the key takeaways;

• Companies using operational BI, were two times better than the average for both financial operating performance, and year-over-year sales pipeline performance.
• 86% of the top performing companies use operational business intelligence tools.
• Top performing companies believe in a “performance culture” throughout the hierarchy. Aligning operational KPI’s with employee’s activities and making them available to all employees.
• In top performing companies, 93% of key operational information is delivered to decision makers in "right time".

I am encouraged by many of the reports finding as it demonstrates the most successful companies are using operational BI tools. It also supports our beliefs at Klipfolio: that right-time awareness of role-dependent performance metrics throughout the entire organization provide our customers with improved operational efficiency, optimizes their sales pipeline, improves customer satisfaction and most importantly drives their profitability.

You can get a complimentary copy of the report through Aberdeen Group until the end of October.

The philosophical answer might surprise you. It’s not SAP's Business Objects, Corda, Klipfolio or Cognos. The most influential real-time dashboard has existed for a long time. We might tell you how long it has existed by using one: a timekeeping device. The idea, definition, measurement and communication of time have become the world’s most influential real-time dashboard. What are the criteria for achieving this prestigious title? Here are the top four ways I measure a dashboard’s influence in declining order of importance:

1. Immense value: How critical is the need to measure and communicate data? Ask this ruthless question when determining what needs to be measured for your job, team or organization. Knowing what time it is, and knowing it in real-time is immensely valuable for everything from simple scheduling to more sophisticated measures over time.
2. Profound simplicity: Does the measurement require training or is it possible to understand the data at first glance? Without these two elements – a simple concept, presented clearly – it’s an uphill battle to achieve understanding and influence. The importance of time is so profound that the limited training that is required to read and understand a timepiece at a glance is baked into elementary school curriculums for young children the world over.
3. Standardization and truth: Can you trust the data you’re looking at? This is a major challenge for organizations both large and small. First of all, is there a common language and conceptual understanding about the metric or indicator? Once that’s in place, a thorough understanding of the data and the processes by which the data is consolidated, cleaned and presented helps to weed out data quality problems.
4. Universal applicability: This last point almost did not make the list, however influence correlated so strongly with broad reach, that it’s an important lesson. In fact and argument exists, that until a critical mass of users adopt a measure, it has relatively little value. This is also related to something we believe in at Klipfolio: data democracy or performance culture. Imagine a world where only the rich had access to timekeeping devices. They would have an advantage over the peasants. Is this the way you want your organization to run? In fact, until a critical mass of users adopts a measure, it has relatively little value.

Timepieces, sundials, watches and clocks have a profound impact on the efficiency of our society. It’s overwhelming when you think about it – a world that has adopted this de-facto standard, and has proceeded to measure it in real-time, embed it into the everyday, make it mobile etc. As a result, someone you’ve never met, half a world away, and with whom you may not share a common language, can arrange a meeting with you at a precise time.

Tempus fugit, and "what's measured gets managed".

If you’re intrigued, take a look at the impressive Wikipedia listing for timekeeping devices: http://en.wikipedia.org/wiki/History_of_timekeeping_devices.

I participated on a DM Radio panel a few weeks ago – they’re always fun, informal, and a great way to share and debate insightful ideas. One of the participants was Marko Muellner, who is VP Marketing at WebTrends. I mention this because he highlighted a common phenomenon in the context of reporting and marketing departments; a frantic need to engineer and share positive performance metrics.

However, it’s far from just a marketing thing. Selective analytics, and only sharing “up and to the right” metrics that suggest a job well done, is a perilous yet common tactic in some companies. And I think we can all see and recognize the pressures that lead to this behaviour. However, failures, unexpected results and fluctuations are just as important to track, and then learn from. There is an answer to everything. And once you have the answer, it’s a lot easier to face colleagues with metrics that are less than optimal.

Here are some pointers when working with real-world charts, KPIs and other data points:

• Do you trust your data? If not, addressing this should be your key priority.
  
• Are you looking at seasonal variations?
  
• Is this expected or planned movement?
• Do you have a rogue data point that can and should be ignored?
• Is your data naturally volatile, and are you analyzing your data over too short a time-period?

Just as with any “white lie”, the truth eventually surfaces. So a note of caution to those of you who are committed to this “up and to the right” model. Data in today’s enterprise environment is so accessible and intertwined, that if your numbers don’t mesh with someone else’s numbers and analysis, questions will pop up. And this is a good thing. At the end of the day, don’t you too want to know why the charts you’re not sharing (yes, those that also go to the right, but down) are trending this way?

Who knows, sharing these volatile real-world charts now, might help your future charts to truly all trend up and to the right!

Good luck, and don’t fake it. You’ll be found out.

An entertaining, informally produced presentation by Microsoft BI about the past, present and future of "decision making". Well worth the 10 minutes out of your day! Enjoy.

But are users any closer to better decisions?

Today IDC released two reports pointing to SAP's Business Objects portfolio as the business intelligence (BI) leader by revenue and market-share with figures around $1.5B and 20% respectively. This gorilla continues bulking up through acquisitions such as the $5.8 billion deal for Sybase approved today by the EU.

More interesting is the fact that IDC confirmed the continued growth of the BI market in an otherwise lackluster IT spending environment. There's still quite an appetite for the clarity of analysis and reporting promised by BI software on top of the scarily complex SAP Business Suite.

Big systems, like SAP, are so complex that an entire industry of system integrators and trainers has appeared to help make sense of it all. Ironically, the same is true for BI software. The high skill levels required for wrestling, crunching, and analyzing data has created BI trainers and consultants who help your people understand their own BI software.

Therein lies the value of Klipfolio Dashboard to the enterprise. Most of your people aren't SAP gurus. Very few of your people are BI professionals. They're important but they could all sit around one boardroom table. What about the other 95% of your workforce that makes operational decisions all day? Even if you could afford to train them all, not everyone is able or willing to plumb the depths of SAP.

Instead, Klipfolio Dashboard presents a streamlined view of operational KPIs to 95% of your organization without any need for training. It acts as the operational bridge to get information out of the complex reporting environment of SAP using Open Hub and J2EE web services.

As the tag-line goes, SAP will run your business. And BI will let power users crunch it and query it once it’s in order. But when these systems and experts succeed in producing actionable KPIs, the way to get them out of the lab and into the hands of people who can use them is with Klipfolio Dashboard.

ROI calculations make for compelling sales tools, and an important way for the vendor to truly understand the value their product delivers. Here’s the catch though: these calculations are almost always focused only on cost-savings, as opposed to demonstrating revenue increase. In other words, the more challenging question is how do you accurately attribute revenue growth back to your dashboard or BI deployment?

Naturally, at Klipfolio, we are interested in understanding the two sides of an ROI scenario better. Here’s what we’ve done so far, and where we need your help.

Let’s take cost savings first:

It’s relatively straightforward to calculate the costs (investment) of your dashboard project, taking the licensing, support, and labor – and if necessary, hardware and vendor services such as integration and training – and adding these up for Year 1, and then through to Year N. OK, so far so good.

Now, we can tackle the less ambiguous of the benefit aspects: cost savings. For Klipfolio Dashboard, the greatest cost savings will be on labor. For example, a reduction in the time your users require on a daily basis to search for, consolidate, and digest critical data; or how much manual time and effort can be saved for your BI analysts whose job it is to produce reports. This calculation is a fairly simple [number of users benefiting] X [time savings] X [average salary equivalent].

There may be additional cost savings, such as bandwidth reduction (although even substantial bandwidth reduction has been found not to have much of a cost impact), and some one-time savings, such as being able to cancel current software.

OK, so there we have the easy stuff. You can now understand your investment and cost-savings on a Year 1 and Year N basis. Of course, as with any ROI calculation, you want to run it through a sensitivity analysis, weighting success, and partial success and failure, so you have a range of worst case to best case.

Now for the revenue-increase aspect:

This is where we need your help. Here is a quote from Gerard Banaghan, Director at Premier Stationary, who summed our thoughts up quite well: "Klipfolio gives us a minimum of an hour a day saved, but the more important benefits are harder to measure. They're to do with quality and efficiency."

Measuring productivity or revenue gain is difficult. And indeed, you’ll be hard-pressed to find good examples of this type of measurement. Klipfolio Dashboard delivers increased data visibility; it improves information awareness. Customers enthusiastically tell us Klipfolio Dashboard is performing to or above their expectations. For us, this is the missing ROI piece. Have you calculated ROI using performance or revenue gain? If so, how have you done it?

We’re looking forward to hearing from you. Based on these discussions, we will work with Lyndsay Wise at Wise Analytics to expand our understanding, survey all of our customers regarding the ROI that Klipfolio Dashboard is delivering, and then share the results with you.

If you’re like me, and subscribe to a number of BI and Dashboard-related newsletters and industry reports, you've probably noticed the increased discussion around Master Data Management (MDM).

For those of you still wondering, MDM is the name given to the collection of processes required to create and maintain consistent and accurate data. It's a recent term, defined in Wikipedia for only about two years now. And it describes what is an altogether daunting task for most organizations.

So why is it important? And why the discussion now?

Certainly the importance of an MDM initiative is clear—it's a wish list that almost every business intelligence analyst and CIO shares: If only all of our data and fields and naming conventions were consistent.

Lack of consistency is an ongoing challenge in a world of ever-increasing reporting, compliance and data governance requirements. And I believe the sudden increase in discussion has its roots in both the increase in SaaS adoption and generally tighter integration between most enterprise systems. BI and dashboards used to be single-source, homogenous reporting platforms. But that is changing, as customers want to consolidate and understand their data from a holistic end-to-end view. With this trend in mind, you can see where MDM comes into play.

Because MDM is most effective when applied enterprise wide, it’s not an easy task. And it can be very time consuming. It’s also fraught with future risk: How can you accurately predict what your future data and reporting requirements will mean for your fields and data-naming conventions?

Here's another interesting point, and possibly cause for some of the recent interest. Generally speaking, Extract Transform and Load (ETL) is a process that acknowledges and deals with the fact that various data warehouses and enterprise applications have different naming conventions and definitions. MDM, on the other hand, deals with the issue of data trust head-on, ensuring data that conforms right from the start. In other words, could MDM eliminate much of what ETL is doing today?

At the end of the day, we all just want “one version of the truth”. And to me, that’s buzz worthy.

A couple weeks ago there was a post about mashups and it triggered a discussion here at Klipfolio about the value of having access to business intelligence information from multiple sources in one location.  It is more than just having everything at your fingertips without spending the time and bandwidth* for going to multiple places, although that is part of it. 

Most enterprise applications come with some form of a dashboard.  While there is some customization available, most of the time users keep the dashboards in the default configuration. And each application presents the data in a different way and style.  Two dashboards presenting the same information might convey them in completely different ways using different visuals.  Likewise, two dashboards from two different enterprise applications will almost certainly not have consistent user interfaces, let alone user manuals.

 Two dashboards using different charts, colors, and threshold values

By pulling all the information into one location the opportunity exists to have a consistent user interface for all of the data that is being accessed.  Not only is this is critical for ensuring that informed decision making is taking place, but it reduces time spent searching for the information, as well as learning the various systems. 

Here is another example. How many times have you seen something formatted in a specific way that skews your perception of it?  Think of a graph where the scale is extremely large or small.  This can make the perception of the data much different than it really is.

 Two graphs with the same information but very different scales skewing the perception

Dashboards in applications operate in the same way.  If the data from different sources are not compared properly it will lead to assumptions and potentially false decision making. And even being aware of the differences, it takes effort to combine them into a consolidated source to provide a realistic view, not to mention the added complexity of performing additional analysis on the data once it has been formatted.

As you know, Klipfolio Dashboard is a platform that pulls data from different sources and gives it a consistent look and feel. More importantly it presents a consistent baseline so that a proper analysis can be performed.  Instead of trying to understand the different colors and graphics used by multiple enterprise applications, dashboards, and other reporting software, it is simplicity and consistency that really helps users understand their KPIs. 

* Look for an upcoming study on bandwidth consumption to compare receiving data with Klipfolio Dashboard to visiting individual sites to access the same information.  Sneak peak: Klipfolio Dashboard uses about 4.9 times less bandwidth compared to typical web application page queries.

There was a pretty even split (42% of respondents saying “Yes”) between those who said their company would be willing to pay a small per-message fee to receive Short Message Service (SMS) alerts from Klipfolio Dashboard on their mobile phone.  While this is not an overwhelming acknowledgment, neither is it an overwhelming disavowal.  Estimates from CTIA claim that 740 billion text messages were sent during the first half of 2009, which equates to 4.1 billion messages sent daily.

SMS is gaining popularity in business applications, as well as for social purposes.  Mobile devices make it easier to write and send messages, especially with the inclusion of physical and virtual qwerty keyboards as opposed to E.161 keypads.  The ability to send messages from PCs to mobile devices also helps to increase the ease of use. Some companies are using SMS to build brand awareness, send discounts and coupons, or even get feedback from clients by including surveys or asking questions which can be responded to with the push of a button.

Receiving SMS alerts is something that companies have already set up, and it is a feature that Klipfolio is investigating and it lends itself perfectly to Klipfolio Dashboard. SMS is a relatively cheap method to use to be notified of when something happens. And it never fails – the moment you are not at your desk monitoring the KPIs is when the threshold or event occurs. SMS provides real-time information so that corrections can be made while there is still time to have an impact. A KPI is only useful if it is important enough to be tracked (otherwise it would not be a KPI, it would just be a PI), and the best KPIs are ones that need to be monitored constantly because they make such an impact on your organization – so why not ensure that you are notified when the KPIs are in jeopardy?

A little while ago we posted a survey asking about your views on Software as a Service (SaaS).  We’ve compiled the results and want to share some highlights, as well as our interpretation of them.

Not surprisingly, 57% of respondents are currently using SaaS in some form, and almost all respondents plan to adopt more in the future. Over the past few years SaaS has been growing in popularity as a way to let people use software without having a “CD hardcopy”. In many cases SaaS makes sense, and it follows along with the responses of the top reasons for why companies use the services. 

Why use SaaS?

First, there is less involvement from the IT team.  As the user is accessing something that is not installed on their computers, they do not have to get someone from IT to install the program.  And this theory extends from a single user to multiple thousands of users.

As well, there is less maintenance and support.  Updates are performed by the provider, and can be rolled out quickly and efficiently to ensure that issues are resolved, again without IT involvement. Behind the scenes improvements and instant deployment of the updates, reduces the likelihood and visibility of problems; in theory, resulting in a better user experience.

The third top reason for using SaaS is the lower initial cost and commitment.  Most services use a subscription model which helps to make it cheaper on a per-user basis in the near term.  However, as the subscription is renewed periodically, over time the total cost of ownership could be higher than a one-time purchase price, which, interestingly, is the top concern for SaaS solutions cited by almost one-third of survey respondents.

Satisfaction

Overall, users are satisfied with their SaaS experience.  The software is performing the task that it was designed for, but without being invested in the product, many users do not really sit back and consider how well it works.  Reliability captured top marks being the only criteria being considered very satisfactory.  However, users considered performance and usability unsatisfactory.  This is likely due to the fact that there is less customization available when adopting SaaS solutions as you do not own it and are less able to make modifications to it.

Additional Findings

One interesting thing was that security concerns where next to minimal, where only a few years ago these seemed to top everyone’s lists regarding SaaS.

Also of interest, was the fact that although one of the benefits of adopting a SaaS solution was less IT involvement, about three quarters of the respondents indicated that administration of such a solution should be a shared responsibility between Business and IT, but with an IT lead.

Additional Content

This is no shortage of information on SaaS.  One recent white paper is titled “An IT Manager’s Survival Guide in a World of SaaS” and can be downloaded from Spiceworks community.   It provides an interesting look at the change of an IT manager’s success, placing emphasis on ROI and the increased demand to produce more results with fewer resources.  It lists 10 tips for managing your career, many of which are also useful for a successful SaaS implementation

Look at the past decade, and you'll easily see that there are more software licensing options available today than at the turn of the century. (Wow, that sound's ancient!)

The concepts underlying those options aren't new – in essence, a spectrum ranging from owning to renting. And, of course, both ends of the spectrum have their benefits – you save in the long run if you choose to own, while renting distributes your costs for a much more palatable short term. It's just that renting software has become easier and, as a result, much more prevalent of late – something that Lyndsay Wise at Wise Analytics touched on recently in her article "The Cost of Dashboard Deployments".

The question that interests us – and we suspect you as well – is what is the current sentiment? What models do companies prefer? Or, to look at it another way, what type of a licensing model is easiest to get approved?

Let us know what you think. Complete the survey and see the results.

Allan

At a recent Help Desk Institute event, Klipfolio staff had a chance to chat with Call Center and Help Desk staff about the daily challenges they face. Here's what we learned.

• They use a mixed bag of technical solutions. You name it, and someone's using it on the Help Desk. Everything from Heat to Remedy to Parature to Excel. And a lot of shops use a mishmash of these and more.
• There is little consensus on what metrics matter most. Is it "first call resolution" that's key? Wait time? Dropped calls? Or something else?
• Old news is no news. Getting information too late was a common complaint. Knowing you've breached an SLA after the fact doesn't help much.
• Help Desk ROI is difficult to measure. The Help Desk is viewed as a cost center. To get the budgets they need to do the job right, Help Desk personnel have to sell themselves. And that means identifying their ROI.

What strikes me about all these challenges is that they are crying out for real time visibility.

How does Klipfolio help the Help Desk? Well, for starters, we tap into each and every source of relevant data, no matter where it's from or what its format, and combine it to tell the whole story about what's happening.

As for which metrics matter, deciding that is Step One in the Klipfolio process for getting customers up and running. Invariably, we learn that different metrics matter to different people. Help Desk managers, workers, and supervisors all have to focus on different things, so they need different Klips in their dashboards.

Of course, it's the immediacy of a Klipfolio Dashboard that makes it so valuable. By providing the right information to the right people in real time, it lets them work in the present. For Help Desk and Call Center workers this means faster response times for increased customer satisfaction.

As for measuring ROI, what better way to do that than to provide management with stats that show how faster response times have avoided those costly mistakes of the past and kept the company's customers and employees happy.

Help Desk is one of many clear-cut cases where a modest investment in operational dashboards can pay big dividends. If you're a Help Desk or Call Center worker, you should really check out what Klipfolio Dashboard for Help Desk can do for you.

I agree with Thomas Waligum's article, "To Hell with Business Intelligence: 40 Percent of Execs Trust Gut". However, as the CEO of a desktop dashboard software firm that extols the virtues of having operational metrics right in front of you to accelerate and improve decisions, does this not fly in the face of what we're all about?

Maybe not: only 40% of Execs in Waligum’s article go with their guts. That implies that a majority of the Execs do rely on some kind of business intelligence. What we really need to see is a corporate performance comparison between the two camps to judge which approach offers better results. Even among the minority of respondents that do rely on gut instinct, Waligum points out that most of these only do so “because good data was not available.” Rather than endorsing gut-based decision-making over BI, the stats actually suggest Executives only turn to their instincts when they are forced to do so. It sounds like Execs will be only too happy to trade in their stomach-based magic 8 balls for a real-time dashboard on their desktop.

Regardless, it's a good read that makes you think about how you make decisions. I bet readers will agree that it’s not an ‘either-or’ relationship, it’s ‘both-and’.

I rarely ignore my gut (to the horror of some of my colleagues - but I call it experience). But I also use Klipfolio Dashboard obsessively, and rarely ignore what the numbers are telling me.

Klipfolio Dashboard alerts me to issues, early trends, and exceptions - things I almost certainly would not catch as quickly without my dashboard. The numbers don't lie but neither do they tell the whole truth. Business is complex and myriad internal and external variables influence why bookings are up or on-time shipments are down.

The key lesson is that reporting tools, scorecards and dashboards can help us identify opportunities and issues earlier than before. There may be no replacement for gut instinct, but when you pair instinct with hard data, you’ve got a really winning combination.

• They don't leverage client-side computing power
• Their UIs are a mess
• Browser technology is too limiting and is a security risk
• Web app deployment strategy is in the hands of the big browser players
• Perhaps not all employees should have Web access

While there is certainly truth to these criticisms, the reality is far from clear cut. The decision for or against Web apps depends on the business you're running and what your goals are.

Web-based applications, and desktop applications like Klipfolio Dashboard, both have their place. More often than not, Klipfolio Dashboard complements a Web-based solution. IT chooses the Web product for its accessibility, and ease of deployment and management. A desktop dashboard then leverages and extends the solution by increasing the visibility of its metrics and driving increased user adoption.

The use of Web apps will continue to grow. As an enterprise platform Web apps are still in their infancy, though. As the market matures, and as desktop applications integrate more effectively with networked content and become easier to deploy and manage, we'll see business taking a best-of-breed approach to deploying these solutions.

At the end of the day, both Web-based and desktop solutions are improving by leaps and bounds. Each has its sweet spots. And together, they can offer a solution that is better than either one alone.

What are your thoughts?

Allan

The KlipFolio desktop dashboard and Serence listings on Wikipedia have just been updated and we’d love to hear your feedback. Better yet, maybe you can improve on the dashboard data that’s there. All the appropriate pages we could think of have been updated but here are the two big ones:

http://en.wikipedia.org/wiki/Klipfolio
http://en.wikipedia.org/wiki/Serence

If you’ve got a desktop dashboard fact or an informative tidbit that you think should be included, by all means add it to the appropriate listing. Maybe you’ve bumped into an online article on branded desktop applications, executive dashboards, or enterprise widgets that mentions us? Even if it just discusses desktop dashboards in general, the more objective reference material we have the better. Alternatively, if you don’t want to Wiki your day away, just drop us a line with your idea and we’ll add it for you.

Does your KlipFolio dashboard need a daily dose of Wiki?
If you love your Wiki in the morning, check out these three Wiki Klips for your desktop dashboard.

Brian O'Grady

We just got back from the Web 2.0 show and wanted to give our impressions of the show. Here's our impression of the conference in four words: packed, infrastructure, APIs, and enterprise.

Packed

The conference was packed, prompting Tim O'Reilly to comment that the Web 2.0 moniker has gone far beyond his expectations for attracting people. In the first evening, so many people were in the exhibit hall it wasn’t possible to move between the booths.

Infrastructure

There was an interesting talk by Jeff Bezos on Amazon’s EC2 platform, which stands for their Elastic Compute Cloud. Combined with their Simple Message Queue service and Simple Storage (S3) storage, Amazon is positioning itself as the computing platform for hosting scalable web applications. In other words, if you want to build a Web 2.0 company, use Amazon’s infrastructure to host your applications. Interestingly, SalesForce.com also has a similar message with their Apex programming language. You can build you SalesForce.com applications using Apex, run your application on SalesForce.com server infrastructure, and sell your applications through the ApexExchange exchange.

I predict we will see similar offerings from Google and Microsoft in the coming months.

In looking at this infrastructure trend, I get the strong feeling there will be a whole new segment of small, fast moving companies who are very good at combining data from multiple sources using such platforms to get to market quickly (and cheaply).

APIs

Speaking of data, many of the interesting talks were around data, the rise of APIs and their business models. I particularly liked John Musser’s (programmableweb.com) presentation, accessible in PDF from here.

Enterprise

There was a lot more enterprise activity at the show than previous Web 2.0 conferences. There were the usual crowd of wikis and collaborative software, but I noticed a lot more companies (RSS Bus, Dapper, Kapow, Denodo, and Strike Iron) offering enterprise tools to create APIs from your data sources.

Many data today is trapped in web-based applications that don’t offer an API. Using tools from these companies, you can create a REST or RSS API to extract data and mashup with other applications.

KlipFolio can read data from any HTTP request (REST or RSS) and alert you on the desktop when it changes. We see this trend towards APIs and mashups creating more opportunities for integrating KlipFolio into the enterprise.

Many of you participated in our KlipFolio user survey last year. A massive undertaking, which asked all types of questions that helps us get a better sense of who and where you are and how you're using KlipFolio. We received over 3000 responses. Here are some of the highlights!

We ran the same survey in 2004. Here is a quick note on what's changed and what has stayed the same.

The overwhelming majority of KlipFolio users are still male, however, the age distribution has moved up a notch - over half of users are now between 25 and 50. English continues to be the choice of language with about half of our users, but European languages are gaining to make up the bulk of the balance. Unchanged from 2004, KlipFolio is being used every day, generally for personal interests and almost three-quarters have between 5 and 20 Klips. Users still lean towards being early adopters (but not quite as much as in 2004), using the internet a few hours each day.

Just before the holidays, Newsweek published a much talked about article entitled, The year of the widget? But it was the question mark punctuating the title that really told the story. Taking a look at all of the discussion it generated, people were not really united about any one thing. What shall we call these things? Will there be consolidation among vendors, and for that matter, are any of the widget shops actually making money? Is this web 2.0? What is the true rate of adoption? And the list goes on...

It sounded a lot like the pre-chasm chatter we heard back when RSS started making news (again) 5 years ago (see Moore, Chrossing the Chasm). For that matter, what are the chances that you, reading this post, aren't an early adopter?

The biggest story about widgets is yet to be told. But we don't think it'll be this year, and we don't think it'll even be about widgets.

Let's say I have an enterprise application out of which I want to pull some data for display in a widget. Obviously, that data is going to be secured, so two things need to happen: first, my widget canvas needs to support secure data access, and second, I need to trust my widget engine to access my enterprise applications on my behalf.

Desktop-based widget engines like KlipFolio and Skinkers are already used for delivering sensitive data. They support encrypted, password-protected data retrieval, and they store encrypted credentials on the user's machine.

While other widget platforms have focused on offering increasingly GUI-rich interfaces, KlipFolio has concentrated on keeping things small, consistent, and secure. We're not about running Yet another Clock Widget (YACW) on your desktop; rather, it focuses on providing a very small, efficient dashboard to save you time and effort.

We target our product for the every-day users, but we've built it secure enough for deployment both internally and externally by corporations to access sensitive data, such as our recent use of KlipFolio Branded for American Express.

We're glad that Richard and Charlie are pointing out that security of the platform is important for business uses of a widget.

This is for our German contingent ... I'm fluent in German, so I often come across posts from German users that I can enjoy, and this one I quite liked.

Der AS bastelt sich ein RSS-Radar

He goes through a great description of how he sets up KlipFolio, fights with his computer that is about to die, and finally reaches what he calls his "feed-monster" creation - lovingly referred to of course, his Frankenstein creation of Klips.

Three unrelated articles caught my attention today - all somewhat related to KlipFolio though. Two I will share with you today, and the third one I will save for a later post.

The first is an interview with Jackob Nielsen, sharing his thoughts on RSS and Blogs. Have a read. It's a good article, a reality check to where we are today, however it does not acknowledge the trend towards this emerging technology. People who are blogging, using RSS, talking about social software are early adopters, and this crowd will influence the future of mainstream.

The second one is a blog by Dan Farber about the explosion and trends of social start-ups. It's interesting just to explore all of the new services / companies / ideas. Just like the social web, here is an interesting parallel pulled from the story:

The most promising sites based Web 2.0 and social networks are those where the structure emerges over time and the results of interaction are more persistent, according to Andrew P. McAfee, an associate professor with the Technology and Operations Management Unit at Harvard Business School. "Wikipedia needed structure over time, for arbitration, tracking changes and making decisions, but it didn't presume to know what the problems are or how to solve them in advance," McAfee told me.

More to come on the third article later ...

We suspect that for many users, Widgets have a short shelf life.

That's because there are different types of users. One group of users wants to decorate and personalize their desktop with appealing tools, such as analog clocks, battery levels, pictures, and web cams.

Another much larger group wants to save time and effort monitoring changes to remote content.

Check out this comparison between Yahoo Widgets and Google Gadgets.

http://forevergeek.com/geek_resources/yahoo_widgets_vs_google_gadgets.php

Both are good widget platforms. And some widgets can be very useful. What we thought was very interesting was the author's conclusions

So I usually run both, system resources permitting. I tend to use [Yahoo] Widgets more frequently, as they are more easily accessible. But really, after the novelty has worn out, these usually tend to serve only as eye candy, unless you have some compulsive need to have your information available on hand all the time.

We think the author's "after the novelty has worn out" comment is correct. Most people will try out widgets because they look cool (hey, don't we all want a cool desktop). However, after a while, they realize they have installed 11.1 MEG of software so they can see a clock on their desktop. Nice eye candy, but eventually they uninstall it to reclaim their system's resources.

What most people really want, as the author pointed out, is "to have your information available on hand all the time."

For Serence, that's our target user: someone who wants to save time and effort monitoring multiple sources from their desktop.