Business intelligence in retail pdf

In Clemen's son, Bernard Joseph, started discounting in Amsterdam Rekenen in Centen, in plaats van Procenten and by there were ten stores in the Netherlands. They were from the German Brenninkmeyer family which traded in linen and textiles since the 17th century from its hometown of Mettingen, Germany.

Significant benefits were identified in terms of employee productivity improvements, reductions in inventory and enhanced management decision making. Even though the company had implemented the SAP ERP system they were still finding it difficult to retrieve information for reporting to support decision making. The reason for this was that the ERP system had not replaced all of their existing systems. The information from the remaining legacy systems was required to be integrated with the information from the ERP system for reporting purposes.

These two systems, although providing some improvements, also caused a number of issues. This resulted in monthly key performance indicator reports being developed and reported via spread sheets. It soon became evident that many of the Business Intelligence reports were not strategically aligned to support executive decision making.

The Development of an Information Management Strategy In the company decided to develop what they termed was an Information Management Strategy which was directly underpinned by Business Intelligence. Figure 1. Project plan of the implementation The Information Management Strategy had six key components that accommodated important inter-related elements and included information hierarchy; strategies that addressed reporting, technology and application level issues; a governance model and the Business Intelligence architecture itself.

Information Hierarchy The Information Hierarchy was designed to determine the information requirements of the organisational stakeholders. The identified performance measures would enhance visibility and accountability, subsequently influencing and changing behaviour.

There were two aspects to the information definitions requirements; Performance Management information Grow the Business and Decision and Operation Support information Manage the Business.

The Performance Management information related to performance measures supporting value-based management that utilised a Balance Scorecard approach. Accordingly, the key performance measures were related to financial and non-financial performance Financial, Assets, Customers, Processes and People.

Notably, the information required was aggregated information used to support high- level management decision making. The Decision and Operation Support information was focussed on operational efficiency. This information reflected business processes and was associated with transactions. This provided more efficient access to information and reports, which in turn facilitated effective decision making. The company identified a number of dependent factors that were associated with Information Hierarchy requirements.

These factors were concerned with gaining buy-in or support from people at the performance management and operations management level. Another factor was the use of the performance measures, which were dependent on the availability and reliability of data used to calculate these measures.

This was to be achieved by the creation of a central repository that stored organizational data by subject area. A change management process was implemented to ensure staff understood these expectations, an issue that was reinforced through staff appraisal and compensation schemes.

Reporting Strategy The Reporting Strategy provided guiding principles and processes for the development and delivery of information to end users.

Criteria were aligned with business justification and the relationship to performance measures. The Efficiency and Preference aspect of the Reporting Strategy was related to report design and distribution. This involved the level of information detail in each report and the level of interactivity required for analysis.

Report design and visualisation guidelines were developed to assist with standardisation and facilitated end user learning. The frequency of when the information was required was also determined. This influenced how the report was distributed and when the information needed to be updated. The Technical Requirements were related identifying and defining the technical infrastructure needed to support the Reporting Strategy. A key requirement of the Reporting Strategy was the development and distribution of strategically aligned reports to the appropriate decision makers.

By using the Information Hierarchy as a reference, the performance measures were able to be identified for the different end users. There are around reports which were implemented in the business intelligence project. The followings are some sample reports. LY and conversion rate per store vs. Business Analyst It was also considered important to provide training for users in Business Intelligence analysis processes.

One of the responsibilities of the governance team was to develop a process to evaluate the reports needed by end users and management. This required extensive user involvement. To act as reference for the evaluation of reports an information template that reflected end user needs was deemed essential. Alternatively, it was also deemed important to document when reporting was not undertaken, and the reasons for this shortcoming. These shortcomings were considered in the design of future reports.

Application Strategy The Application Strategy was responsible for providing the Business Intelligence environment so as to deliver consistent and high quality data to IT applications and the subsequent information to users.

This included the implementation of an Enterprise Data Warehouse EDW to store data that supported the various business units. If you want to have a deeper and personalized knowledge about the aspects, you might probably need an expert in retail analytics solutions who can build an app for retail analytics.

Save my name, email, and website in this browser for the next time I comment. Join fellow entrepreneurs! Get Peerbits' latest articles straight to your inbox. The growing importance of business intelligence in retail analytics. Facebook Twitter LinkedIn Pinterest. With the improvement of the Web, the development of multi-channel operations and evolution of intelligent retail analytics solutions , Organizations must have the capacity to change their plans of action so they can gather constant business data and drive the proficiency of their everyday operations.

The growth rate indeed is massive!! Business intelligence and retail analytics Before, retailers depended on recorded examination to illuminate future basic leadership, and a few information accumulation forms frequently left a considerable measure to be fancied. Few known examples of retail analytics solutions is m2r Adopting Retail mobility solution which provides retail analytics is a powerful way to work towards your retail goals.

How does it work? Leave A Comment. Leave A Comment Cancel reply Comment. Subscribe Us. Related Posts. Although this report is designed to give a general overview, the report gives specific examples of how popular retail companies develop their business intelligence methods in order to make more profitable and efficient decisions for their customers and stakeholders.

The in-depth BI topics that this paper covers is online analytical processing, data mining, and predictive analytics. This report also includes a prototype of a data warehouse and analytics platform that a electronics retail company with a global presence would use to help manage its operations.

This database was originally designed by Microsoft. Retailers such as Walmart, Amazon and Target are businesses that serve the needs of billions of customers every day. Technology has given new advantages to retail outlets throughout the world, which they did not have in earlier years. Chains such as Walmart have made astronomical investments to improve their e-commerce efforts, while also delivering their products efficiently in stores Settles.

The business world has become addicted to data over the past few decades, in all forms in order to take advantage of unseen relationships and correlations between customers, products and many other demographics. Microstrategy is a provider of enterprise software platforms and was founded in Microstrategy gives these organizations an easily integratable product, including the consulting services to help any business implement these specific kinds of BI software in a web interface.

Many retail companies that we know of including Ace Hardware Corporation and the Container Store has chosen Microstrategy to handle their Business Intelligence needs. This report outlines the different needs of retailers and illustrates how Business Intelligence software can help the organization.

All of these areas are extremely useful to store managers in each store and also the CEO of the retail store company. In this day and age, data equals power. Corporations and small business alike are desperate to acquire as much data as possible about their customers, because the more you know about them, the easier it is to sell them goods and services through directed advertising and marketing. It is amazing the wealth of information that can be pulled out of customer demographics and if you are able to take advantage of this, your company will reap the benefits.

This topic covers all portions of retail from conceptualizing the product, to creating the product, to selling it to the consumer, making it imperative for business to take advantage of.

Business Intelligence in the Supply Chain: Having a firm grasp on all aspects of your business from what happens behind the scenes to customer relations is very important. BI provides the tools to drill down into data to find the root cause of problems rather than knowing a general idea of what is possibly going wrong.

A great tool for Supply Chain Management is benchmarking. By comparing your performance to other companies you can see if you are outperforming or underperforming and where you need to improve. Not only is it a good tool to compare externally but it allows you to see how your company is doing internally as well.

While having all of this data is important, it then comes down to management to act on it. Building off of that, dashboards are a fantastic way to quickly see relevant facts and information if constructed correctly. Sales per Hour for store or associate — total labor hours Time Spent in the Store 7 8. Data warehouse stores data to serve different needs in terms of business plan, forecast, market research, outlet sales, Invoices, purchase orders, inventory, transport orders, stock orders, salary advice, re-distribution costs , account receivable, account payable, visual merch audit, production plans and jobs etc.

Output of this layer feeds performance management system of corporate office. BI Applications BI generally supports analytics function of an organization. In a retail-FMCG set-up as retailer-supplier relationship matures, risk sharing occurs among supply chain partners. Partners can be convinced of sharing risk only when the proper information is available across the chain through BI so that they can take right decision at the right time.

Supplier may use this for scheduling production and delivery or determining inventory level. The retailer still submits individual orders and supplier maintain own forecasting system.

In a Continuous Replenishment program CR , supplier delivers at an interval mutually agreed by both the parties. The relationship gradually moves to an on-going relation from a transactional one.

Here, supplier takes over inventory functions that the customer would deal with in a traditional arrangement e. To be successful, VMI and CPFR both needs intensive sharing of not mere data, but the predictive power of the data that resides in the systems of collaborators.

Since the BI has matured form just static reports to on the spot answers via dynamic Dashboard at gives current and updated snapshot of information enabling Real time analysis.

Instead of just showing data, BI gives insights into the data, alerts and root cause analysis that helps in decision making. BI has gained greater integration power, thus enabling data merger for various external and internal sources. It has become a collaborative business planning tool. It arranges the data in a way that it can satisfy specific business query.

Choose the Dimensions: 4. Identify the Facts: 14 Some of them represent the merchandise hierarchy e. The analyst can browse through dimension attributes and we can roll up and drill down using attributes as constraints even if they do not belong to the merchandise hierarchy. Drilling down actually adds one column more. Product Dimension table design should be taken with great care covering almost all necessary attributes to ensure exhaustiveness. Date Dimension: This is a very familiar dimension across all industry.

Qualitative attributes bear more significance for this dimension e. More time series factors like retailing season or fiscal periods can be included to make the design robust as the business needs to slice and dice data by these nonstandard attributes.

Store Dimension: This is the primary geographic dimension which describes every store in a retail chain. Stores can be rolled up using attributes like ZIP code, districts, regions and county etc.

Store dimension is mainly used in the corporate reporting and the necessary components of the store dimension from multiple operational sources assemble generally assembled at headquarters. Promotion Dimension: Common promotion activities are end of the season sales, provisional price reductions, festival offers and coupons etc.

Trade promotion effectiveness is a management concern for achieving volume and profitability. Various promotional measures should be judged individually for a more straightforward administration. As these measures are highly correlated, multi-co linearity factor need to be accounted for decision making.

Spreadsheets 2. Reporting and querying software: tools that extract, sort, summarize, and present selected data 3. OLAP: Online analytical processing 4. Digital Dashboards 5. Data mining 6.