Defining BI Requirements - What

The first task in a BI progam [and the first goal of the BI roadmap] is to identify what the business wants to achieve, and how business intelligence can support that need.

Look for opportunities in your organisation where business intelligence can:

1. improve the quality of day-to-day decision making
2. add value to operational efficiency
3. support tighter collaboration

BI Value Assessment

1. Where can business intelligence be used effectively?
2. Who will use the application?
3. What information do they need?
4. How will the outcomes be measured?

Assessing Where Business Intelligence Will Be Used Effectively

Every organisation is structured differently, but each has a set of core processes that create value streams in the organisation to meet corporate objectives. By reviewing these processes across functional areas and business units we can identify areas where there are:

• Operational inefficiencies - effectiveness in meeting goals in a timely manner
• High costs for the outcomes
• Opportunities not being met
• Poor decision making and/or high volume of decision making
• High reliance on data for operational management or decision making
• Source of key reporting used by other areas of the business

Don't constrain this review to just the normal areas of the business reliant on data, such as executives, finance and marketing. An holistic review of critical functional areas and processes across the entire organisation will quickly uncover many opportunities for consideration. Unlike financial analysis, BI techniques are applicable to 90% of the business. Poor processes can often be significantly improved and better managed with business intelligence capability.

At a retail store - improvements in employee selling performance, loss prevention, and warranty data collection can result from BI.

In a production line - BI can result in better scheduling and managing of the product mix.

In services marketing - BI can support laser targeting of product offerings to better defined customer segments.

In a supply chain - BI can promote more accurate forecasting and better stock utilisation.

Look for areas of the business that are containable for your first effort. Applying business intelligence to functional areas is a great place to launch your business intelligence program. Functional areas are generally:

• Easier to define - their BI applications are more tactical, linked to the management of specific operations and outcomes, rather than strategically impacting the entire organisation.
• The requirements easier to scope - source data often comes from only one or a few OLTP systems as opposed to cross-functional or business-unit level applications that typically combine data from multiple sources.
• The benefits are easier to realise and measure - the success is easier to communicate and showcase to other areas of the business.

Assessing Who Will Use the BI Application

When assessing who will use the application, one must consider both the scope of the project as well as individuals within the scope. It is a fundamental mistake in new BI programs to attempt to rollout BI across several functional areas as a first initiative. Rather, once one functional area recognises the value of BI, the program can be duplicated in other functional areas, and then expanded to cross-functional and business-unit applications.

Assessing Who By Scope

Cross Functional and business unit applications are generally more strategic and focus on high-level planning rather than supporting operational activity.

A typical functional process - Customer Profitability Analysis: revenues and costs are collected and then allocated to specific customers and customer groupings. The BI outcomes help decide customer type/ customer group, pricing or discount structures, customer product differentiation, buying habits, customer retention, and channel profitabilty.

A typcial cross functional process - Product Contribution Analysis: variable costs are collected from all functional areas of the business, not just variable manufacturing costs, and then assigned or allocated to specific products or product lines. The BI outcomes are better understanding of alternative pricing strategies, deletion of unprofitable products or product lines, and new bundling of product offerings.

BI applications used by multiple departments are more difficult to define and obtain agreement on. They typically involve data from multiple functional OLTP systems, and are more difficult to build.

The BI benefits are qualitative [measured by better decisions] rather than quantitative [operational performance improvements], making them more difficult to define, measure and evaluate.

Cross-functional and business-unit applications are more strategic, and do have greater impact on competitive advantage, but are considered a more advanced form of business intelligence.

For these reasons, in spite of corporate strategies and goals being implemented from the top down, business intelligence is typically implemented as a bottom-up process, with performance metrics [KPIs] reflecting the unique function of each business unit.

Assessing Who By Role

The 'who' is revealed through assessment of the information and analysis needs of the different roles and levels in the organization—operators, supervisors, managers, senior managers, and analysts.

As a guide, the lower the job classification, the more need for detailed operational data specific to a functional area. Higher job classifications generally only need summarized data that supports the analysis of trends and patterns within and across functional areas.

For example:

A Telesales channel operator - works at the customer transaction-level with information including customer name and address, product number and description, promotion offer etc. This core information is routinely provided by the company's OLTP system.

The team leader - helps operators with problems and manages team performance - will need hourly summary of transaction data and call management statistics, with access to transaction detail to help resolve an issue.

The Telesales Channel Manager - oversees the operation - uses multidimensional and hierarchical information to monitor trends in operational performance, with only an occasionally need for customer level detail.

BI systems also make possible easy access to operational information by analysts, senior managers, and executives outside the functional department. This is in sharp contrast to traditional reporting hierarchies that level by level roll information up from the lowest level to supervisor, to manager, to departmental head, to business unit head, divisional head, and finally C-level executives.

With BI, reliance on this slow, scheduled reporting is surpasses by the ability for any authorised user to check trends and drill down to identify the source performance data. Whilst the technology barrier is removed, the political barriers may take some time to overcome. In todays fast paced business environment personal egos are the deadly to corporate performance enhancement. Many senior executives still resist empowering managers with valuable information. Yet by doing so, they better enable their managers to improve operational performance, thereby releasing higher level managers to deal with broader and more timely performance. So don't overlook the political impact or current culture in each of the functional areas you are assessing.

Assessing What Information Is Needed

When looking for BI opportunities in an organization, defining what information would offer the most value is a key requirement. This is achieved by understanding the decisions that must be made at each stage of the process, the raw data available and the measureable outcomes of those decisions. It often helps to start in reverse, at the high level process:

1. Define The Process Measures
2. Define The Activity Measure

Defining the Process Measures

he critical success factors for each core process in the functional area. These are generally measures calulated from transactional data, such as average sales volume, average prices, profitability, etc. Link these outcomes to corporate strategies, goals, and objectives.

Defining the Activity Measures

Activity Measures are the base measures captured at transactional level - sales data, resources employed, cost

The most relevant measures are driven by the functional area and processes for which the BI application is being developed, for example:

• Sales measures - unit sales, amount sales, count of orders, backlog
• Production measures - assembly units, hours, inventory
• HR measures - turnover, tenure, employee satisfaction, absenteeism

It is also important to consider the people impact, by measuring the impact BI has on users.

Defining How The Outcomes Will Be Measured

Defining outcomes relates directly to the roles of the users in the functional area. There are two aspects to this step:

1. Determining the base data required to measure outcomes - this data will be used in terms of dimensions to add context to the data, and thus transform the data into information.
2. Determining the level of data required - based on the business requirements

Define the Dimensions

Dimensions are used to describe the measures, and give them context. For instance, sales by customer group. 'Sales' is the base measure, and 'customer group' is the dimension. At a higher levels, calculated measures such as profitability by customer group.

When deciding on measures, consider how they interrelate and are calculated before defining dimensions such as time, product group, location etc.

Consider where the data is derived, how available it is based on current systems, and what data transformation will be required to access it to provide these measures.

Dont just think on each dimension alone, consider how multiple dimensions can describe a particular measure. Analysis across multiple dimensions simultaneously makes the data useful for analysiss

Dimensions typcially found in BI applications for each functional area include:

• Sales and Marketing—products, customers, demographics (age group, gender), sales channel, geography, promotions, campaigns, sales force, order status, sales type, time
• Human Resources—organizational chart, employees, time, business unit, department
• Operations—shift, time, assembly line, product, manufacturer, warehouse, suppliers
• Finance—currency, account, scenario, time, business unit, department

Define the Level of Detail

For each combination of dimensions and measures, decide how much detail is desired. This is defined as the lowest level of information for each dimension that must be available across different user groups. This is important, because all summarized data can be easily derived from the lowest level of detail.

The level of detail required is driven by the business requirements, yet it must remain practicable. Consider the relative cost and benefits of summarized vs. detailed data.

• Summarized or high-level data tends to minimize the number of data points that you have to analyze, but it does not allow you to see trends at lower levels of detail.
• Detailed, low-level data means that you will need to analyze more data points to identify trends.

This is required to meet the needs of both transactional level users who require detailed data to monitor activity performance, and managers who require summarized data to identify trends.

The key to finding the right balance is by first determining a reasonable level of detail for the lowest level of data required across all users, and then using the BI system to create hierarchical summaries.

Detailed data may also be used for more advanced analytical techniques, such as data mining.

Once the level of data detail is determined from a business requirements perspective, it will still need to be evaluated in terms of the feasibility of accessing the data.

NEXT: Conceptualising Ideas And Collating Information

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