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RESOURCES CATEGORY: Big Data / Information Discovery

Big Data is Transforming the Retail Industry

Retailers have experienced seismic changes last decade with their ways to engage the customers. People used to only go to brick-and-mortar stores to shop. Now it is the age of omni-channels from stores to ecommerce sites and mobile devices. Customers are also more active and vocal than ever to let their opinion known to their fellow shoppers and retailers through social media sites such as Yelp. This presents huge challenges and opportunities to retailers as an enormous amount of data have been collected and can be analyzed to gain critical insights to support retailers in their endeavors for product innovation, personalized customer experience, cross-channel merchandizing and efficient inventory management. Big Data is a perfect solution to address these challenges, providing the retailers who are forward looking and investing in the technology great competitive advantages.

CHALLENGES

Retail is a highly competitive and thin-margin industry. Customers are becoming more and more sophisticated in how they spend their money. Retailers are facing multitude of challenges to capture large market share and retain customers’ loyalty.

  • Retailers need to be able to anticipate demand, ensure availability of products in the right locations, price the merchandise optimally, attract customers by offering relevant and timely promotions and enhance customer experience with personalized customer services
  • Retailers need to provide a uniform, yet customized, shopping experience across multiple channels such as stores, online and mobile for cross selling and enhanced customer experience
  • Retailers need to know their customers in a holistic fashion in regards to their shopping patterns, product preference, money spent, demographics and past shopping experience
  • Retailers need to be in tune with the market trend and manage its inventory and supply chain to ensure that the right merchandising is available at the right time and right location

To meet these challenges, retailers need to mash up content and data from many disparate data sources, internal and external, and provide an actionable insights for the business to act on. The sheer volume of the data, large variety and uncertain veracity of the content make it a perfect use case for Big Data. Traditional business intelligence technologies just fall short of dealing with these challenges.

Built upon its extensive experience with the retail industry, PREDICTif has developed an innovative set of Big Data technologies to address those challenges to gain critical information, without burdening business users with hard-to-use tools or high IT costs. We are able to accomplish this by Partnering with the leading information discovery and big data technology company Oracle, by delivering highly customized solutions based on Oracle Big Data Discovery (BDD) and Endeca Information Discovery (OEID) technologies. These solutions are described in the below table:

What Why Who
Marketing and Consumer Engagement
  • More relevant and timely recommendations (in store and online)
  • Increased consumer loyalty and advocacy
  • More consistent cross-channel communication
Pinpont the customers that will likely buy through social media, purchase history, customer forums, demographic data, browsing patterns and customer loyalty data
Store Operations and Cross-channel Commerce
  • Improved On Shelf Availability performance
  • Better understanding of store conditions that impact shopper decisions
  • Improved cross-channel understanding of consumer shopping behavior
Determine the right inventory at the right locations for the right channels through trend prediction by analyzing industry news, web browsing patterns, social media and enterprise data
Product Innovation
  • Faster and more consumer-relevant generation of new product concepts
  • More successful new product launches
Create product bundles based on customer transactions, shopping patterns, demographic data, research data and local buzz and make relevant recommendations to customers
Consumer Engagement
  • More consistent cross-channel communication
  • More relevant and timely recommendations (in store and online)
  • Increased consumer loyalty and advocacy
  • Optimized marketing mix across B2B and B2C
Segment customers according to expected buying behavior and then contact them as they wish to be reached, when they are in the right location or they are engaged with personalized real-time offers

Equipped with our long history of successes with the retail industry, PREDICTif will deliver these value-added retail analytics solutions to enable our retail customers to capitalize on the big data solutions. Our engagement will start with a Retail Industry expert who will help produce a solution roadmap based on our pre-built templates and then deploy an implementation team that consists of highly skilled consultants to establish Big Data solutions for consumer insights. PREDICTif has helped transformed retail organizations to gain competitive advantages over their market rivals and achieve significantly high return on investment.

Big Data Unlocks Consumer Insights

Evolution of mobile devices and social media has provided consumers with more channels to make their voices heard about the products and services that they receive. In a typical week – 156 million adult consumers engage social networking on smart phones and tablets according to a recent Nielsen report. That’s nearly 65% of the US population! Rapid adoption of social media outlets such as Facebook, Twitter, Yelp, Pinterest and Tumblr will continue to change the way that we connect with our customers.

WHO CARES

Retailers, Restaurants, Consumer Goods Manufacturing and Hospitality are just a few industries that have an urgent need to stay in touch with their customers. Historically they have implemented many touch points such as loyalty programs, consumer care desks and surveys to gain an understanding of the customer sentiment towards their products. While the analytics of the content is valuable, it is now missing a significant component – social media. Additionally, there is no easy way to correlate the consumer sentiment from these content sources with financials, product development and operations to reach a comprehensive understanding of the impact that customer insight has towards its business. Given that typical organizations have data and content stored in disparate systems and managed by different internal departments – there needs to be a better way. Step in Big Data, which is a perfect platform to mash up a set of diverse content, structured and unstructured, and provide a single pane of glass for critical insights.

DISPARITIES

Traditional Business Intelligence (BI) technologies lack the power to handle the data with vast volume and arrays of varieties. The fact that consumers can now simply thumb on their devices and provide their feedback with a wide reach makes it even more critical to understand the impact immediately. Today’s BI platform does not offer the kind of flexibility and self-service capabilities to deal with these challenges. Business’ reliance on an over-burdened IT keeps it slow to address its customers’ concerns and capitalize the opportunities. Big Data is changing the landscape how consumer insights are gathered and leveraged, helping alleviate those disparities in traditional IT infrastructure. As lines of business demands increase – so will the need for relevant data.

PREDICTif brings an innovative set of Big Data technologies to provide business self-service consumer insights tools to gain critical information, without burdening business users with hard-to-use tools or high IT costs. We are able to accomplish this by partnering with the leading information discovery and big data technology company, Oracle

PREDICTif can help retailers, restaurants, hospitality, telecomm, banks and consumer goods manufacturing in the following use cases:

What Why Who
Marketing and Consumer Engagement
  • More relevant and timely recommendations (in store and online)
  • Increased consumer loyalty and advocacy
  • More consistent cross-channel communication
Marketing, Digital Marketing, Marketing Operations, Loyalty Marketing, e-Commerce, Consumer Insights, Store Operations
Store Operations and Crosschannel Commerce
  • Improved On Shelf Availability performance
  • Better understanding of store conditions that impact shopper decisions
  • Improved cross-channel understanding of consumer shopping behavior
Marketing, Digital Marketing, Marketing Operations, e-Commerce, Retail Ops, Supply Chain, Consumer Insights
Planning and Merchandising
  • Improved merchandising
  • More targeted store assortments mapped to shopper basket preferences
  • More relevant real time offers
Merchandising, Category Mgmt, e-Commerce, Consumer Insights, Demand and Supply Planning
Supply Chain
  • Improved On Shelf Availability performance
  • Improved forecasting, replenishment and inventory allocation performance
Retail Sales and Ops, Supply Chain, Consumer Insights, Demand and Supply Planning, Inventory Mgmt
Product Innovation
  • Faster and more consumer-relevant generation of new product concepts
  • More successful new product launches
R&D, Innovation, Marketing, Brand Mgmt, Category Mgmt, Supply Chain, Sales, Regulatory Affairs
Consumer Engagement
  • More consistent cross-channel communication
  • More relevant and timely recommendations (in store and online)
  • Increased consumer loyalty and advocacy
  • Optimized marketing mix across B2B and B2C
Marketing, Digital Marketing, Brand Mgmt, Consumer Affairs, Consumer Insights, Sales, Trade Marketing, Category Mgmt

PREDICTif will leverage our extensive experience through our successes with these industries and deliver value-added Consumer 360 solutions. Our engagement will start with a Consumer Insights expert who will help produce a solution roadmap based on our pre-built templates and then deploy an implementation team that consists of highly skilled consultants to establish Big Data solutions for consumer insights.

PREDICTif Solutions to Present at Oracle OpenWorld 2015

EVN

oracle

 

PREDICTif Solutions, a Houston-based technology consulting firm, today announces its upcoming presentation at Oracle OpenWorld 2015. The conference, held from October 25 to 29 at the Moscone Center in San Francisco, CA, will be a premier event for business and IT professionals to learn about Oracle technologies through the interactions with Oracle and its business partners. PREDICTif’s CEO, Jeff Huang, VP of Global Sales, Karl Harrocks and OEID Practice Lead, Jimmy Philip will represent PREDICTif at the conference, meeting customers and Oracle colleagues.“This year we are very excited to have two of our customers, Wilsonart and Cox Automotive, speak on our behalf and share with our customers and partners their successes with PREDICTif. The Wilsonart story is featured on the September issue of Oracle Profit magazine, describing the incredible journey that Wilsonart and PREDICTif travelled together to build a fully integrated EPM, BI and Big Data solution” said Huang.

“PREDICTif has built a lot of successes in our three core practices, EPM, BI and Information Discovery/Big Data last couple of years.” , said Harrocks, “We are excited to leverage this platform to share our extensive experience in Oracle cloud offerings and Big Data Discovery. Whether we’re sharing our knowledge or learning from others, it’s our continuous goal to grow as a thought leader in the age of Big Data and bring this advantage to our customers.”

High-Value Health Check to Enhance Existing BI Solutions

NWS

PREDICTif Delivered a High-Value Health Check to Enhance Existing BI Solutions and Develop a Master BI Implementation Plan

CUSTOMER:

A leading Oil and Gas Equipment services company.

REQUIRED CAPABILITIES

  • Remedied performance and instability issues existed with the BI applications
  • Delivered a master Implementation roadmap for an enterprise BI and FPM architecture

CHALLENGES

The customer has over 25 subsidiaries, many acquired through acquisition. Each subsidiary had built out its own business intelligence (BI) and finance performance management (FPM) solutions using a myriad of BI and FPM products. As one of the leading global equipment service and pipeline construction companies, the customer faced numerous challenges related to instability, inconsistency and slow performance of BI applications. In preparation for the opportunities and demands of becoming part of a publicly held company, the customer needed to expand its BI and FPM architecture beyond the business unit level.  Before further expansion could take place, the customer needed to consolidate their division level BI and FPM initiatives as well as map out a strategy and roadmap to establish an enterprise BI architecture. The existing BI systems presented numerous deficiencies in terms of people, process and infrastructure:

  • All its business units had their own BI and FPM technologies, support teams and project initiatives without an enterprise level governance and standard;
  • There was no single version of truth in terms of data on the enterprise level which rendered the enterprise level reporting and financial consolidation inaccurate and labor intensive;
  • The existing BI infrastructure contained a myriad of technologies and products making support and maintenance difficult and cost of ownership extremely high; and
  • Lack of a BI competency center rendered uneven quality of delivered BI applications that resulted in slow performance and instability.

SCOPE                      

Conducted a health check to identify areas of risks and opportunities, recommend remedial measures, and produce a master implementation plan and a roadmap to build an enterprise level BI architecture.

  • Examined existing BI infrastructure and organizations in terms of people, process and infrastructure to discover areas of risks and opportunities, and more importantly, produce a list of actionable recommendations to improve the overall BI strategy and execution;
  • Reviewed the existing architecture, configurations and codes;
  • Identified bottlenecks that were causing slow performance and instability;
  • Aligned business objectives and priorities with BI initiatives;
  • Created organizational philosophy and culture to support an enterprise BI strategy; and
  • Developed a master implementation plan and roadmap for an enterprise level BI architecture.

SOLUTION

PREDICTif Solutions was engaged to provide a 2-week health check. PREDICTif’s senior architects reviewed the existing BI infrastructure, made recommendations for improvement and delivered a master implementation plan for rolling out BI to the entire enterprise.

Based on PREDICTif’s standard health check agenda and customer priorities, PREDICTif and the customer created a detailed agenda before the engagement. The agenda addressed both tactical and strategic aspects of the customers business. The tactical aspects were to analyze the existing BI solutions to identify areas of risk and opportunity as well as provide recommendations on both. The strategic aspect was to understand the customer’s business priorities and deliver an enterprise BI implementation plan.

The two week agenda was filled with workshops, interviews and document reviews during which, PREDICTif’s architects met customer’s personnel from numerous areas of the business to discuss business objectives, current BI architecture and business user concerns. Conversations focused on areas such as data quality, data governance, data modeling, report requirement gathering processes, architecture, support/maintenance and technology best practices. The architects also discussed future plans, business initiatives, short term and long term business goals as well as technological direction in the BI and FPM arena.

The PREDICTif resources combined our own set of BI and FPM best practices and standards with information gathered from the discussions in order to produce a  set of documents:

  • The tactical health check deliverable is in the form of a Microsoft Word document and a Microsoft PowerPoint presentation both of which outlined areas of opportunity, improvement and identified risks as well as the necessary steps to mitigate those risks.
    • In this case, the PREDICTif architects discovered that the BI architecture was not designed appropriately for the increased number of users and business cases which caused significant degradation of performance and stability;
    • The customer did not have a well defined data governance process that was accepted by all business units. It resulted in poor data and metadata modeling as well as an overall lack of data quality and transparency;
    • The architects made recommendations to improve the Bi architecture in terms of performance and stability; and
    • The architects applied PREDICTif developed and tailor-made data governance and data modeling best practices to the customer’s business and IT environment.
  • A master BI implementation plan and roadmap was delivered in order to consolidate the dispersed BI architecture as well as establish an enterprise level BI infrastructure.
    • The implementation plan entailed a multi-phased project plan that detailed the sequence of activities, dependencies and high-level estimate of effort as well as timelines;
    • It illustrated a 18-month BI architecture evolution through the phases of implementation;
    • The roadmap also considered the trend and best-in-class BI technologies; and
    • The implementation plan included the steps to establish an enterprise level BI competency center and governance process.

RESULTS

PREDICTif delivered considerable value to the customer’s return on the software and IT infrastructure investment. The health check’s findings and recommendations significantly improved both the performance and the stability of the customer’s existing BI architecture. The implementation plan provided a clear roadmap to establish an enterprise level, world class BI architecture.

  • The improvement decreased the rendering time of a complex report from an average of 6 min to less than 30 seconds, greatly increasing the productivity;
  • The upgrade and addition of hardware and software instance increased the overall uptime from 95% to that of 99% which was a requirement of the business;
  • The customer completed all three phases of PREDICTif’s recommended implementation plan and the overall BI initiatives continue to gain adoption and approval from the business use population.

Flexible financial and operations reporting solution for Texas Grocer

NWS

A Texas grocer engages PREDICTif to deliver a flexible financial and operations reporting solution

CUSTOMER:

A regional chain of grocer, pharmacy and retail.

REQUIRED CAPABILITIES
Manage financial and operation reporting with different rules for different accounts, as well as for different business units; but with one final standardized output. Handle multiple hierarchies, centralized security and quick response times.
CHALLENGES

Operating over 100 supermarkets in both metropolitan and rural areas of Texas and Louisiana, the customer faced numerous challenges related to its financial and operational reporting as the company became reliant upon an inefficient, highly customized reporting application. The application was based on an antiquated and unsupported technology, Query 2000. Further compounding the difficulties associated with reporting on a customized system was the fact that the customer had no dedicated vendor support or experienced technical resources which in and of itself resulted in multiple technical limitations:

  • Difficult to create and maintain the reports;
  • Manual process required to generate reports;
  • No scheduling capabilities;
  • Reports couldn’t be published which causes duplication and inaccurate reports;
  • Was difficult to modify and reuse existing report templates;
  • Lack of templates resulted in longer cycles to develop new reports;
  • Generation of reports was slow as they were directly processed out of AS400 Mainframes;
  • There was no alerting and bursting capability to detect and manage business significant
  • events;
  • Legacy solution was burdensome as it related to the creation of ad hoc reports;
  • Did not support the customer’s data retention schedule and data cleansing; and
  • Newly developed reports can not be tested by users to ensure accuracy.

SCOPE

The objectives were to provide the customer the capability to accurately report on a timely basis, reuse templates and achieve self sufficiency after the project.

  • Deliver a financial reporting solution that leverages the TM1 9.4 OLAP engine and Cognos BI 8.4 report studio;
  • Automate the report process and make it easy for business users to create new and ad-hoc reports;
  • Provide training and knowledge transfer so that business users are self independent in terms of support and enhancement; and
  • Implement alerting and bursting capabilities to manage critical business events and support data retention process

SOLUTION

The customer acquired IBM’s Cognos BI 8.4 and TM1 9.4 to address the constraints of the legacy solution. The IBM Cognos suite provided the customer the flexibility to generate and reuse reports as well as the ability to automate report generation and alert/burst functionality for significant events.

After a thorough vendor selection process, PREDICTif was selected to implement an end-to-end reporting solution for the customer. The project encompasses the entire life cycle of software installation, configuration, customization, testing, implementation, user groups training and knowledge transfer. PREDICTif delivered the solution under budget and before the planned completion date.

  • Developed a comprehensive project plan with detailed scope and timelines;
  • Created business requirements documentation and technical requirements documents for the project;
  • Installed and configured Cognos 8.4 on DEV, QA and Production with QA and production being multi-server environments to improve performance and ensure redundancy (3 application servers, 2 web servers and 1 content server);
  • Converted all existing Query 2000 reports to Cognos reports using Report Studio, Query Studio, Analysis Studio and built cubes using Framework Manager Models;
  • Created 45 additional complex reports;
  • Developed and delivered the ability to create Ad hoc reporting;
  • Completed ETL Mapping (Fact builds and Dimension Builds) function using Data manager;
  • Designed and implemented a Datamart for the customer’s HR Department;
  • Consolidated/replaced a quandary of spreadsheets into one single company wide data entry by utilizing TM1;
  • Used F5 load balancers to conduct thorough load balance and fail-over testing to ensure the performance and robustness of the BI solution;
  • Provided thorough documentation of all the reports and user manuals; and
  • Offered training to both power users and end users on Query Studio, Report Studio and Analysis Studio.

RESULTS

PREDICTif’s TM1 solution streamlines the customer’s financial and operational reporting process and enables the customer to have accurate information at hands in order to make critical and timely business decisions.

  • The number of hours spent generating consolidated financial statements was reduced substantially allowing more time for analysis;
  • Multiple disparate business units were brought together under one streamlined reporting process, with a standardized company-wide output;
  • The comprehensive training and detailed documentation that the customer’s personnel received equipped the customer with the knowledge to support and maintain their system with minimal assistance from its IT support; and
  • PREDICTif helped establish best practices and project methodology within the customer’s organization that will benefit the customer in its future BI implementation projects.

Business Intelligence (BI)

BLG

Business intelligence (BI), once a competitive differentiator, is now a commodity. Most companies have implemented BI solutions that provide historical reporting, dashboarding, metrics and scorecarding for past events. Companies know what has happened but the ability to know what will happen will be the competitive advantage that companies need to excel in this volatile and ultra-competitive environment. Predictability is the next step in the evolutionary process of Business Intelligence.

Traditional Business Intelligence and data warehousing focus on strategic, long term decision support. While strategic Business Intelligence continues to be a requirement to support long range vision, Predictive Business Intelligence (PBI) takes business Intelligence beyond a process that has traditionally looked backwards and has been reactive in nature. PBI empowers the enterprise in realizing competitive advantages and provides the business with the necessary agility to meet the challenges of today’s rapidly changing business environment by mitigating risks and maximizing opportunities. PBI greatly improves both long term strategic decision making and near team operational decisions.

The ability to make Predictive strategic decisions will separate enabled companies from their competition enabling them to capitalize on opportunities and reduce exposure to risk. Statistical analysis on operational and transactional data will provide insightful information on business trends and enable the business to make strategic decisions quickly and more effectively. For example, when a retail chain is determining whether to establish a presence in an unfamiliar territory, it could utilize growth data from other locations and combine it with the local data as well as current projection data to provide support for the decision making. The data might be sketchy and sparse, but statistical analysis will offer a sound basis for decision making. Other examples can be found in oil & gas exploration or pharmaceutical development projects for instance. These projects often entail long development cycles and considerable up-front cost the outcome of which has significant impact on the overall performance of the business. Predictive decision making will enable those companies to analyze more data in order to gain a complete view of the business cases and leverage proven statistical models to aid those impactful decisions. The completeness and quality of the data analyzed are critical to determine the accuracy of the prediction. Although companies in these verticals go to great lengths to develop elaborate risk management models to address common concerns, predictive business intelligence In support of existing risk management processes, provides a richer set of data and more interactive analysis to ensure a better outcome.

 

PREDICTif help find an enterprise dashboard & scorecard solution for energy company

NWS

A global integrated energy company seeks PREDICTif’s help to find an enterprise dashboard and scorecard solution to track KPIs

CUSTOMER:

A global major integrated energy company.

REQUIRED CAPABILITIES

  • An Enterprise Level Dashboard and Scorecards that tracks KPIs against Refinery Actual, Planned, and Scheduled Metrics with reduced data latency and enhanced ease of use

CHALLENGES

As one of the world’s largest integrated energy companies, our customer conducts business in every aspect of the crude oil and natural gas industry, including exploration and production, manufacturing, marketing and transportation, chemicals manufacturing and sales, geothermal energy, and power generation. Our customer sought an enterprise solution to track key financial and operational KPIs.

  • The customer did not have Metrics for key performance indicators in critical financial and operation categories;
  • Unable to track down any change in the key metrics and identify the contributing factors to the change;
  • No dashboarding capabilities to provide a snapshot view into operational performance at world wide refineries; and
  • There was 1-2 day of data latency, and as a result, the reports did not contain up-to-date information.

SCOPE

The customer’s requirement was to create an enterprise level dashboard that tracked key KPI’s against their Actual, Planned and Scheduled Metrics. The scope also included the creation of dashboards and scorecards to give a high level representation of critical operational data.

  • Increase visibility — create dashboards that allow the business a high-level view of  granular data in order to get to timely address business problems immediately;
  • Increase accountability — assigns owners for each metric as well as the accompanying responsibility for performance;
  • Increase focus — concentrate on priorities and eliminate distractions;
  • Improve communication — communicate results and actions taken to manage performance; and
  • Improve collaboration — use metrics to link together people, departments and processes.

SOLUTIONS

After evaluating several world class solutions, IBM Cognos BI was selected for a number of reasons – one of which being IBM Cognos BI provides a highly customizable and informational dashboard and scorecard solution. Cognos metrics studio, metrics designer and framework Manger version 8.4 provide needed metrics functionality to meet the requirements. PREDICTif was engaged to provide an end-to-end BI solution and develop Refinery Metrics and Balanced Scorecards using Cognos Metrics Studio/Metrics Designer 8.4.

  • Analyzed existing requirements for the need to created metrics, metrics types, planned values, actual values, charts and various scorecards;
  • Installed and configured Metrics Studio and Metrics Designer on the existing Cognos BI 8.4 environment;
  • Used Framework Manager to initially model a package that will be used to as a source for creating the metric designer package;
  • Created various Metrics and Metrics Types (Actual Vs Scheduled, Actual Vs Planned, Planned Vs Scheduled etc) and compared the different metrics;
  • Developed customized Report Studio Reports to be used as part of this metrics analysis;
  • Used Metric Designer to create a metric package for use in Metrics Studio;
  • Used Custom calendar and performed various admin tasks like pushing data into staging area and then into metric store etc;
  • Developed a balanced scorecard based on the various metrics created earlier; and
  • Trained Administrators, BA’s and Developers to maintain this metrics model and package and also them on used metric studio.

RESULTS

PREDICTif delivered a Cognos BI solution that increased the visibility to significant business events and enhanced the customer’s ability to detect and resolve business issues and maximize market opportunities.

  • The Cognos BI Dashboard provided a consolidated view of refinery operational metrics from all of the customer’s worldwide refinery units;
  • The Scorecard solution offered insight into operational issues and enabled teams to design and implement measures to resolve issues;
  • The data integration solution significantly reduced the latency and delivered up-to-date information to business users; and
  • The customer was able to support and upgrade the solution independently after PREDICTif provided extensive and specific training and detailed documentations.
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