Failure to Launch: From Big Data to Big Decisions, Page 2

decisions that need to pick up early trends or understand the dynamics of change.

  Some of the most common use cases across industries are as follows:

  Corporate Performance Management

  The most common use of pro-active reporting is around performance management, bringing in more intelligence to traditional scorecards, automatically linking and reporting the changes in key performance indicators across an organization - ranging from financial to customer, organization, and process indicators.

  Channel Management

  With thousands of stores, partners, and employees, large B2C organizations need to monitor sales and service quality / quantity trends. Pro-active reporting facilitates automated tracking of fluctuations at the most micro level, and can provide comprehensive feedback on what to fix and where to fix it - e.g. sales in our store A for product 1 has decreased 5%, because of a new competitor store in the area and out-of-stock issues this month.

  Customer Relations Management

  From key account management to customer value management, pro-active reporting answers various questions, such as which macro customer segments have been churning recently, which micro segments are becoming best targets for cross-sales, which specific corporate accounts are in early stages of a downward trend, etc.

  Product Portfolio Management

  Especially in sectors where product variety is high - such as retail and e-commerce -monitoring sales performance of each and every product closely becomes an almost impossible task. With pro-active reporting, not only is all kept under control, but also the explanation of sales fluctuations for each product is available - e.g. Product A sales dropped 10% because our youth segment started purchasing less in region 1, with increased number of returns and complaints.

  Service Level Management

  Although timeliness and quality of processes are regularly monitored for service level assessment in most leading organizations, very few identify the root cause behind fluctuations automatically. With pro-active reporting, all is identified - from the list of steps causing delays in a specific time frame, specific employees causing the delays, types of applications (e.g. with incomplete documents) causing the delays, etc. In other terms, all findings that are usually obtained only during process redesign efforts become a daily routine with pro-active reporting.

  Getting Started

  Pro-active reporting solution implementations follow a cyclical and continuous process, as follows:

  Step 1. Define the list of KPIs to follow. This list of KPIs depends on the application area and business priorities, and can range from a list of 3-4 indicators to hundreds in complexity.

  Step 2. Define the possible relations between the KPIs. To be defined by the business (with people who work in and around the KPIs as part of their day to day work), the linkages various KPIs have with each other have to be explored and determined. Three main types of causality relations may be defined:

  I - Selective Relations: These relations explain the interaction between KPIs and their sub-sets across various dimensions (such as breakdown of customer acquisition across market segments).

  II - Calculative Relations: These relations represent the mathematical interactions between different KPIs (such as revenue being related to the number of active customers and revenue per active customer).

  III - Deductive Relations: These relations explain the interaction between KPIs and direct / indirect factors correlated to these KPIs (such as sales being related to marketing spend).

  These first 2 steps require detailed brainstorming and discovery sessions, usually involving most (if not all) organizational units, as relations and dependencies usually span across the whole value chain (e.g. supply chain inventory affecting sales as much as marketing).

  Step 3. Build up KPI and relation data. Pro-active reporting mind-set usually brings in additional data requirements to an organization, especially regarding factors affecting each KPI. Building a complete pro-active reporting platform requires the collection of more data, at a finer granularity. Establishing deductive relations on the other hand, usually require detailed regression analysis, in order to quantify the level of correlation in between.

  Step 4. Establish the notification system. Once everything is in place, the next thing is to define which alerts should be delivered to whom within the organization, based on which analysis and with what frequency (e.g. daily, weekly, monthly and even hourly, if used for operational purposes).

  Repeat. Finally, as with all systems, pro-active reporting should be monitored and fine-tuned over time, based on changing business priorities, market conditions and learnings.

  About CIWare

  CIWare stands for Causal Intelligence and is a pro-active reporting solution developed by Forte Wares. Designed with the adaptability to suit various business problems, CIWare enables businesses to make faster and more precise decisions. Automating the whole discovery process, CIWare also saves valuable time and resources, and eliminates the human-error risk in business analysis.

  Unlike traditional BI solutions, CIWare focuses on change in the business - rather than looking at a snapshot of the business indicators, it analyzes their change over time, as well as contribution of various factors to this change.

  For more information please visit www.fortewares.com or email us at [email protected].