Business performance management

Business performance management (BPM) is a set of processes that help organizations optimize their business performance. It is a framework for organizing, automating and analyzing business methodologies, metrics, processes and systems that drive business performance.

BPM is seen as the next generation of business intelligence (BI). BPM helps businesses make efficient use of their financial, human, material and other resources.

History
An early reference to non-business performance management occurs in Sun Tzu's The Art of War. Sun Tzu claims that to succeed in war, one should have full knowledge of one's own strengths and weaknesses and full knowledge of one's enemy's strengths and weaknesses. Lack of either one might result in defeat. A certain school of thought draws parallels between the challenges in business and those of war, specifically:
 * collecting data
 * discerning patterns and meaning in the data (analyzing)
 * responding to the resultant information

Prior to the start of the Information Age in the late 20th century, businesses sometimes took the trouble to laboriously collect data from non-automated sources. As they lacked computing resources to properly analyze the data they often made commercial decisions primarily on the basis of intuition.

As businesses started automating more and more systems, more and more data became available. However, collection remained a challenge due to a lack of infrastructure for data exchange or due to incompatibilities between systems. Reports on the data gathered sometimes took months to generate. Such reports allowed informed long-term strategic decision-making. However, short-term tactical decision-making continued to rely on intuition.

In modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have set up repositories to store this data. Improved ETL and even recently Enterprise Application Integration tools have increased the speedy collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. Business intelligence has now become the art of sieving through large amounts of data, extracting useful information and turning that information into actionable knowledge.

In 1989 Howard Dresner, a research analyst at Gartner (until 2005, now Chief Strategy Officer at Hyperion Solutions Corporation), popularized "BPM" as an umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems.

The term "BPM" is now becoming confused with "Business Process Management", and many are converting to the term "Corporate Performance Management" or "Enterprise Performance Management".

What is BPM?
BPM involves consolidation of data from various sources, querying, and analysis of the data, and putting the results into practice.

BPM enhances processes by creating better feedback loops. Continuous and real-time reviews help to identify and eliminate problems before they grow. BPM's forecasting abilities help the company take corrective action in time to meet earnings projections. Forecasting is characterized by a high degree of predictability which is put into good use to answer what-if scenarios. BPM is useful in risk analysis and predicting outcomes of merger and acquisition scenarios and coming up with a plan to overcome potential problems.

BPM provides key performance indicators (KPIs) that help companies monitor efficiency of projects and employees against operational targets.

Metrics / Key Performance Indicators
For business data analysis to become a useful tool, however, it is essential that an enterprise understand its goals and objectives – essentially, that they know the direction in which they want the enterprise to progress. To help with this analysis key performance indicators (KPIs) are laid down to assess the present state of the business and to prescribe a course of action.

More and more organizations have started to speed up the availability of data. In the past, data only became available after a month or two, which did not help managers react swiftly enough. Recently, banks have tried to make data available at shorter intervals and have reduced delays. For example, for businesses which have higher operational/credit risk loading (for example, credit cards and "wealth management"), A large multi-national bank makes KPI-related data available weekly, and sometimes offers a daily analysis of numbers. This means data usually becomes available within 24 hours, necessitating automation and the use of IT systems.

Most of the time, BPM simply means use of several financial/nonfinancial metrics/key performance indicators to assess the present state of the business and to prescribe a course of action.

Some of the areas from which top management analysis could gain knowledge by using BPM:
 * 1) Customer-related numbers:
 * 2) New customers acquired
 * 3) Status of existing customers
 * 4) Attrition of customers (including breakup by reason for attrition)
 * 5) Turnover generated by segments of the Customers - these could be demographic filters.
 * 6) Outstanding balances held by segments of customers and terms of payment - these could be demographic filters.
 * 7) Collection of bad debts within customer relationships.
 * 8) Demographic analysis of individuals (potential customers) applying to become customers, and the levels of approval, rejections and pending numbers.
 * 9) Delinquency analysis of customers behind on payments.
 * 10) Profitability of customers by demographic segments and segmentation of customers by profitability.

This is more an inclusive list than an exclusive one. The above more or less describes what a bank would do, but could also refer to a telephone company or similar service sector company.

What is important is:
 * 1) KPI related data which is consistent and correct.
 * 2) Timely availability of KPI-related data.
 * 3) Information presented in a format which aids decision making
 * 4) Ability to discern patterns or trends from organised information

BPM integrates the company's processes with CRM or ERP. Companies become able to gauge customer satisfaction, control customer trends and influence shareholder value.

Application software types
People working in business intelligence have developed tools that ease the work, especially when the intelligence task involves gathering and analyzing large amounts of unstructured data.

Tool categories commonly used for business performance management include:


 * OLAP &mdash; Online Analytical Processing, sometimes simply called "Analytics" (based on dimensional analysis and the so-called "hypercube" or "cube")
 * Scorecarding, dashboarding and data visualization
 * Data warehouses
 * Document warehouses
 * Text mining
 * DM &mdash; Data mining
 * BPM &mdash; Business performance management
 * EIS &mdash; Executive information systems
 * DSS &mdash; Decision support systems
 * MIS &mdash; Management information systems
 * SEMS &mdash; Strategic Enterprise Management Software

Many of the software applications allow customizations and integration with other enterprise software e.g., Microsoft's solution allows the use of APIs to provide enhancements using third party applications.

Designing and implementing a business performance management programme
When implementing a BPM programme one might like to pose a number of questions and take a number of resultant decisions, such as:
 * Goal Alignment queries: The first step is determining what the short and medium term purpose of the programme will be. What strategic goal(s) of the organization will be addressed by the programme? What organizational mission/vision does it relate to? A hypothesis needs to be crafted that details how this initiative will eventually improve results / performance (i.e. a strategy map).
 * Baseline queries: Current information gathering competency needs to be assessed. Do we have the capability to monitor important sources of information? What data is being collected and how is it being stored? What are the statistical parameters of this data, e.g., how much random variation does it contain? Is this being measured?
 * Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BPM initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
 * Customer and stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers / stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customer benefits be monitored? What about employees, shareholders, and distribution channel members?
 * Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
 * Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will data be collected? Are there any industry standards for this? Is this the best way to do the measurements? How do we know that?
 * Results-related queries: The BPM programme should be monitored to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can it be demonstrated that the BI initiative, and not something else, contributed to a change in results? How much of the change was probably random?