Calumo - Business Intelligence and Performance Management Blog

In business today graphs, charts and gauges often form an important part of measuring and presenting numbers. In our business, which revolves entirely around the presentation of business intelligence and performance management numbers, we see poorly designed graphs and charts on a daily basis.

In order to illustrate (and hopefully prevent) some common design mistakes, we will provide some examples of poorly designed charts, followed by an analysis of the problems and our proposed alternative solution.

The chart below forms part of a presentation we attended, described as “a fantastic presentation of graphics for more visual appeal.”

Our analysis of the problems with this chart:

• The background image is distracting and adds no value
• The gridlines are hardly visible, but do not make it any easier to understand the chart
• The legend uses a lot of space and could be more intuitive to match back to the chart bars
• The bars are unnecessarily thin which makes them harder to see
• The chart has no title
• The Y axis title/units (US$) has been written vertically making it subtly difficult to read.

Our Proposed Solution:

• As a general rule, anything that does not contribute to the meaning of a graph is an unnecessary distraction. Therefore remove the background image and grid lines which are adding no value.
• We considered removing the X and Y axis lines, but decided in the end only to de-emphasize them by changing them from black to light grey.
• We recommend the use of soft, or neutral colours and colours of different saturation. Save bright colours for emphasis only where required. In our solution we could have used colour but used shades of black and grey to highlight that we thought about how our chart would look if it was photocopied or printed in black and white. Imagine how the original solution would look if it had to be faxed.
• The legend has been moved above the chart and ordered in the same sequence as the bars, to ease the process of matching the legend up with the bars.
  Moving the legend provides more space for the chart and allows the bars to be thicker for better visual effect.
• Change the orientation of the Y axis title/units to be horizontal.
• Add a title to the chart

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CALUMO is a three syllable word pronounced Cal (as in the first syllable of calculate) + Lieu (as in “in lieu of” meaning “in place off “) + Mow (as in mow the lawn).

CALUMO is derived from celeusma, a Greek word (but used also in Latin: ke>leuma) meaning the song, chant or command given by the chief oarsmen that gives power and rhythm to the rowers.

In the same vane, CALUMO empowers people facilitating collaboration within an enterprise for unified business performance management.

Some people have told us the name also sounds like calculate from “Cal”; numbers from “umo” derived from numero; and illuminate from “lumo”.

All this is true and reflects a sense of what CALUMO is about, but most importantly we think that people using CALUMO are Business Intelligent.

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We read with great interest recently that Financial Consolidation Applications have reached the Plateau of Productivity on Gartner’s Hype Cycle for Business Intelligence & Corporate Performance Management.

The Gartner Hype Cycle (see fig below) tries to make sense of different emerging technologies starting on the left hand side of the graph and typically travelling from left to right. Following their introduction, technologies can be subject to unrealistic hype bringing them to the “Peak of Inflated Expectations” only to fall into the “Trough of Disillusionment” once reality sets in, before emerging at the right hand side where they finally begin to deliver some of the benefits that were originally promised at the “Plateau of Productivity” (in many cases new technologies never progress far, due to failure along the way).

At CALUMO we provide a rich ecosystem of best-practice solutions based on our core product capabilities. Let’s look at the type of functionality commonly expected in Financial Consolidation Applications as they stand at the Plateau of Productivity.

• Data collection
  • Online over the internet (real-time for collaboration)
  • Mapping (for sites with different ledgers)
  • Validation (stop/proceed based on check-total, variance etc)
  • Online review and approval process at each tier (Workflow)
  • Escalations if late (alerting)
• Journal entries
  • Recurring and manual
  • Automated currency translation gains/losses
  • Automated P&L, Cash Flow, Balance Sheet & notes
  • Intercompany processing
  • Automated balancing
  • Audit trail
• Intercompany eliminations
  • Define intercompany accounts
  • Automated eliminations
  • In balance / out-of-balance reporting
• Foreign currency translation
  • Multiple rate types
  • Define which rate type by account (supports temporal method)
• Consolidation (obviously)
  • Consolidate actuals and budgets
  • Consolidate statistical measures such as headcounts
  • Accommodate different fiscal periods & calendars
  • Wholly owned or minority interest
  • Multi-tier consolidation or hierarchies
  • Revaluations
  • Automated Intercompany eliminations to first common parent
  • Flexible Chart of Accounts
• Financial reporting
  • Results in home or reporting currency
  • Multiple hierarchical reporting
  • Lead schedules for supporting notes
  • Rounding to thousands
  • Allocation of rounding error to specified account

At Calumo we offer a unified architecture for all our modules ranging from Financial Consolidation to BI, Planning and Operational performance management applications. All these are available through a familiar interface (Excel or Internet Explorer) offering the lowest total cost of ownership amongst BPM vendors today.

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Last week we considered how techniques first used in NASA helped retailers plan their inventory. This week we are going to get behind the man and his thinking in a bit more detail.

Rudolf E. Kalman, a graduate research professor emeritus at the University of Florida and ad personam chair at the Swiss Federal Institute of Technology in Zurich is considered the most influential researcher in the field of control and systems theory.
 
During the 1960s, he was the leader in the development of a rigorous theory of control systems. Among his many outstanding contributions were the formulation and study of most fundamental state-space notions (including controllability, observability, minimality, realisability from input/output data, matrix Riccati equations, linear-quadratic control, and the separation principle) that are today ubiquitous in control.

He is best known for the linear filtering technique that he developed in the years 1959-1961 to strip unwanted noise out of a stream of data. The Kalman filter is widely used in navigational and guidance systems, radar tracking, sonar ranging, and satellite orbit determination (as we saw last week at NASA for the Apollo and other missions, for instance), as well as in fields as diverse as seismic data processing, nuclear power plant instrumentation, and econometrics.

The Kalman filter, which is based on the use of state-space techniques and recursive algorithms, revolutionized the field of estimation and forecasting and while some of these concepts were also encountered in other contexts, such as optimal control theory, it was Kalman who recognized the central role that they play in systems analysis.

During the 1970s Kalman also played a major role in the introduction of algebraic and geometric techniques in the study of linear and nonlinear control systems. His work since the 1980s has focused on a system-theoretic approach to the foundations of statistics, econometric modeling, and identification as a natural complement to his earlier studies of minimality and realisability."

In simple terms Kalman filtering addresses an age-old question: How do you get accurate information out of inaccurate data? More pressingly, How do you update a "best" estimate for the state of a system as new, but still inaccurate, data pour in? The Kalman filter applies a sophisticated algorithm designed to strip unwanted noise out of a stream of data. Strangely this “noise” could be as diverse as unusual inventory movements.

As we saw it should come as no surprise that recently the Kalman filter has proven to have a major contribution to planning some lines of inventory allowing retailers to optimize their stocking levels and subsequently significantly reduce inventory.

Not only is the filter able to remove the noise caused for example by a mother buying 12 pink shorts for her daughter’s netball team but is able to manage in an environment of large amounts of data.

The pink short purchase is an aberration or noise and tends to disturb the normal pattern of sales. This purchase would lead to stock model inaccuracies from the typically unsophisticated planning methods currently deployed such as Moving Average.

Kalman filtering also has a way to link the sales over time such that it effectively uses each new observation to update a probability distribution with no need ever to refer back to any earlier observations.

This has the interesting implication to planning in retail where there are typically large data sets. Once the Kalman filter has been tuned with some initial data it does no more work for the millionth estimate than it does for the first. The net result is an algorithm tailored to applications, where data keeps coming in and decisions have to be made quickly.
 
It is easy to see why Retail Planning with Kalman filtering is at forefront of modern inventory management but there are even more techniques emerging that augment this filter to more precisely allow for patterns such as seasonality. The latest filters apply routines that some clever Chinese guys applied to robotic vision, but more of this next week.

I say, till next week, bring on the Summer and bring on the shorts!

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Recently we had a holiday on the NSW Central Coast and needing a few bits and pieces I ventured in to the local department store.

The store was absolutely full of stuff! It reminded me a bit of when I used to go shopping with my Mum 35 years ago at the discount food store with everything everywhere. Talk about retail aversion therapy!

Being in finance with an engineering background I tend to subject ideas to more analysis than a psychiatrist’s couch so I left the shop wondering if it could survive. The overriding impression was that it had far too much stock. Simply, there seemed to be far too much money locked up in “them there” shelves.

Surely there was a better way! I had an inkling that maybe it was the sort of question that requires some serious science. Maybe NASA knows.
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Some terms go out of fashion as the technology becomes mainstream (eg OLAP), only to be replaced by new terms that better describe new capability expected and hopefully being delivered. One such term is BPM (Business Performance Management) which I believe has recently been superseded by Performance Management 2.0. Gartner's definition of these terms will be subtly different from IDC's and finance sees things differently from IT. There is much room for overlap and ambiguity.
 
For many years we used the words "Planning, Analysis, Reporting" as our company tag line to best describe what we did. Today we use "Business Intelligent" as our tag line, which is more esoteric and we hope more thought provoking as well. Here is what we think about and what best describes what we do now:

Performance Management Applications
          o Business Intelligence
                + Reporting
                + Analysis
          o Planning
                + Budgeting
                + Forecasting
                + Modelling
          o Dashboards
                + Scorecards
                + Metrics
          o Financial Consolidation
          o Monitoring
                + Workflow
                + Notification
    * Vertical Applications
          o Retail, Telco, Banking, Construction
          o Consumer Goods,  Freight and Transport
          o Government, Healthcare,  Manufacturing and Industrial
          o Professional Services,  Resources  Utilities.
    * Horizontal Applications
          o Executive Management
          o Finance
          o IT
          o Sales
          o Marketing
          o Human Resources
          o Production & Logistics
    * OLAP
    * ETL

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Gaining and Retaining the customers you want

The telecommunication industry is currently undergoing major change with a business model that is moving away from voice connectivity to virtually every aspect of communications you can imagine. Customer intelligence is required to enable the business to focus on gaining and retaining the customers they really want.

With the ease with which customers, looking for the best possible deal, are able move from one operator to the next, high customer churn rates are an ongoing problem. Telco’s must continually find new and effective ways to market products and services to new and existing customers in order to increase revenue, recover acquisition costs, and improve customer loyalty and retention. One of the best ways to do this is to maximize customer value through effective cross-selling and up-selling.

Many Telco’s still struggle to do this, yet the customer data that would help identify good candidates for cross-sell and up-sell campaigns is often available somewhere in the enterprise, but not readily available for methodical and systematic analysis.

Without a complete and clear analysis of customer preferences and behavior, effective customer profiling is impossible. Knowing the answers to questions such as "which customers subscribe to multiple services"? or "Which customers always upgrade to the newest equipment?" lets you profile and discover the attributes of similar customers who could be good candidates for cross-selling and up-selling campaigns.

Cross-Sell and Up-Sell is only a part of a unified Telco business intelligence solution. Other components include:

• Customer retention
• Customer segmentation
• Customer profitability
• Market basket analysis
• Customer loyalty program analysis
• Channel effectiveness analysis
• Call behavior analysis

Unified Telco business intelligence and analytics is only part of the solution. The next challenge is to architect these Telco specific components with scalable business intelligence and performance management technology, compromising data integrated from every source within the organization

Any Telco able to do this can gain real value from their data and efforts - Gaining and Retaining the customers they want.

 

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Quantifying business benefit of Business Performance Management is not trivial. As far back as ’92, Debone & Mclean established a framework for measuring Information System benefit. Their framework saw System Quality (performance, flexibility, ease of use, reliability, response time etc) and Information Quality (timeliness, relevance, usefulness etc) as determinants for System Use and User Satisfaction (see fig below).

How do these drive business benefit?

Well, satisfied users easily finding the quality information they want in a BPM system can make great Individual Impact. Large groups of individuals working together create Organisational Impact.

Let’s take a common BPM application - a retail planning and forecasting system.

In this case it’s been implemented well to user needs with high-uptime that provides flexible what-if analysis from store planning to integrated corporate reports, delivered through an easy-to-use web portal with real-time updates. The system provides timely information from production systems and the flexibility allows the end user to slice and dice from perspectives relevant to them. Bill, a store manager, uses this system on a daily basis for reporting and analysis, while Sue, a regional manager, forecasts the profit impact by substituting one brand with a cheaper version sourced  through the company’s own  supply chain.

Useful stuff, but how do we measure the organisation impact of this BPM system?

One approach, adapted from academic work on ERP system benefit, is to use a Balance Scorecard. Originally developed by Kaplan & Norton, Balance Scorecards are used to measure organisational effectiveness from the activities the organisation engages in - rather than simple financial metrics. The Scorecard framework is useful as it allows us to take a quixotic ideal like organisational benefit and break this into impacts across financial, customer, internal and learning perspectives. By reviewing the impact across various organisational areas and processes, you start to see some cause and effect on the bottom line.

In our retail planning example - from an internal business perspective - the faster (and more automated) information flows between Bill and Sue, the greater the collaboration and the more informed decision making can be. Transparent planning using numerically-based scenario analysis (rather than aerial extraction) with all historical forecasts instantly available improves learning as sales forecasts can be more accurately tracked. Ultimately, the customer receives benefit from lower priced goods – made possible through the accurate and useful information generated in what-if analysis by Sue.  

Hard numbers from soft concepts:

The nice thing about Balance Scorecard is that from when it is first implemented and ultimately used well by the organisation, the system itself creates a ready before and after Polaroid (measurement of success). Of course you should have a fair idea of the type of benefits you expect before you start implementing even if you don’t have a comprehensive measurement tool in place to benchmark against.

A well implemented BPM system will have a range of predicted benefits, but also holds great potential for unforeseen benefits as enhanced collaboration, flexibility and other soft benefits are explored by bright and motivated individuals throughout the organisation.

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Automatic Meter Reading, or AMR, is the technology for automatically collecting data from energy metering devices (gas or electric) and transferring that data to a central database for billing and/or analyzing. This means that billing can be based on actual consumption rather than on an estimate based on previous consumption. It also eliminates the need for each meter to be visually read by a technician, thereby cutting personnel costs.

Advanced Metering Infrastructure, or AMI, is technology to capture additional data. This can include detection of technical events such as leaks, or reverse flow (reducing the chance of power emergencies and blackouts), but AMI is also used to collect time of use data that can be used for energy use profiling, time of use billing, demand forecasting, rate of flow recording, flow monitoring, etc.

EnergyAustralia call this PowerSmart which they (and others) are progressively implementing throughout their electricity networks. With traditional "flat" pricing, the price you pay for electricity is the same, no matter what time of day or night you use it (with the exception of customers who have special off peak meters and rates, usually for hot water). With PowerSmart, your electricity rates are broken down into three different time periods - Peak, Shoulder and Off Peak. This means you pay for how much electricity you use, based on when you use it. A higher rate is charged during the Peak period, than the Shoulder and Off Peak periods. So your rate is less when the demand for electricity is lower, and more when it is higher. This means you have greater control over your electricity bill. AMI makes it easier for you to keep track of your energy usage which can help you reduce your energy costs and you are provided with an incentive to reduce your energy usage.

Apart from the consumer benefits, AMR and AMI technology is also a completely new source of data for energy retailers to analyse. They could gain unprecedented insight into demand and usage patterns, which could in turn provide enormous business benefits.

For example, the wholesale electricity market is typically characterised by relatively tight supply with huge discrepancies between pre-purchased and real-time prices and the absence of a predictable short-term (e.g., hour-ahead or day-ahead) forward market. With the benefit of AMR and AMI analytics, markets will mature and get more competitive, the level of discrepancy between pre-purchased and real-time prices will narrow and become more sophisticated.

Large wholesale customers, who are also retail suppliers therefore have the best opportunity to exploit and respond to short-term demand. With their new found AMR and AMI analytics, their ability to respond within one hour, or even five minutes with favourable prices highlights the significant opportunity for large, sophisticated customers that will support wholesale market timing and pricing.

These benefits however are only available to those who can overcome the enormous data management and analytics challenges.

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For Retailers, the ever increasing diversity and fragmentation of consumer demographics requires that they analyse customer data at a very detailed, granular-level. They need rigorous timely processes to respond to demand signals and segment customers in a way that's superior to their competition.

By properly aggregating and analyzing retail transactions, that would otherwise offer little insight into the business, data can be transformed into actionable information that can increase sales and profitability, provide competitive advantage and deepen customer and vendor loyalty.

The availability of sophisticated (transactional) data poses the challenge to find a way to effectively harness and leverage massive volumes of data. SQL Server 2005 provides a platform for enterprise-class performance and scalability for analytical number crunching of this nature. Even for writeback, Microsoft claim enhancements to data writeback include a ten-fold performance improvement. With the advent of X64 Servers, these solutions are now even more affordable.

To find out more, about our retail capability, please visit our retail solutions page.

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We are often asked to explain what  BPM is and why it is so important compared to a non-integrated, non-unified approach to business intelligence, reporting, analytics, planning etc.

 

It struck me on seeing the image of the flock of birds below, that one way to answer this was to use pictures. As they say, a picture paints a thousand words.

 

The point of all the images that we’ve chosen is that patterns and meanings can be found and relationships and collaborations possible within the whole.

 

Nature, fractals, tessellations and origami are all fine illustrations of order out of apparent chaos. And so to with BPM, an organisation can gain greater insights through the observation of structures, relationships and patterns of the whole enterprise.

 

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Fig 1: During spring in Denmark, flocks of more than a million European starlings gather in incredible formations such as shown above.

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Fig 2: Origami tessellations take a simple crease pattern unit and repeat this across the paper. Example above by Alex Bateman (can you visualize the spiral pattern?).

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Fig 3: Horocycle 4 - Knots and dynamics - A collaboration between Jos Leys and Prof. Etienne Ghys (hmm, reminds me of fishing with my dad).

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1. It must effect a measurable change in performance.
2. It needs to be applicable to a broad spectrum of organizations.
3. It should be proven in practice.
4. It needs to exploit proven technologies.
5. It must ensure an acceptable level of control and risk management.
6. It has to match the skills and capabilities of the companies in which it is used.

Business Intelligence and Performance Management home.

1. Are you wrestling with poor information quality when making decisions?
2. Do your finance and business users spend a lot of time developing special reports?
3. Are you plagued with "multiple versions of the truth"?
4. Are your decision makers buried in too much information, unable to derive useful insights?
5. Is your Planning and budgeting information not realistic or is it outdated and has lost relevance relevance?

1. Better operating decisions faster.
2. Improved annual planning decisions.
3. Confidence in business process controls and reporting.
4. Improved decisions on strategic direction
5. Savings by reducing time users spend reworking information.
6. Reduce cost of complying with regulation and mitigate enterprise risk.

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