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Analytics - A core of Wexcore
Analytics is an increasingly important tool to drive growth, enhance productivity, and improve efficiency. As advanced data management and analytics capabilities become the new normal, companies need new expertise to bring their full potential to bear and extract business treasure. Our Analytics Practice combines functional knowledge with advanced analytics capabilities (including web analytic services) to help clients sustain a competitive edge across strategic business functions.
Our Outlook and Approach:
In rapidly changing markets and industries, information is power. We help our clients turn streams of raw data into powerful insights, giving them a competitive edge that yields short-term results and long-term growth.
Big Data Analytics
1) Analytics Transformation
In a competitive market, companies win by being smarter and executing faster and better than their competition. For most companies, smarter, faster, and better means having superior insight into customer needs, behaviours, and profitability. Competing on analytics is increasingly a key capability for all companies, independent of size.
The news is that the growth of digital data has been enormous. Processing "Big Data" requires new types of applications and customized software tools for operational improvement at the individual customer, segment, market, and enterprise levels.
Analytical excellence is an ongoing capability different from transaction processing. It requires more computing horsepower—often more than a company has ever used. It also requires analytical talent that is not available in most organizations. But the benefits and insights are worth the investment. Without analytical capabilities, a company's competitive position will erode.
The biggest challenges companies are facing are a shortage of talent and strategic clarity on how to effectively embed advanced analytics capabilities within their organizations. WEXCORE works with companies to overcome the challenges they face in making this vital transformation. We help organizations develop and grow world-class analytics capabilities by addressing four key areas:
Analytics strategy definition
Operations and process management and optimization
Hardware and tools technology selection
Road Map to Advanced Analytics
Our analytics work begins by assessing the current stage of a client's analytics capabilities across multiple dimensions and mapping these to best practices among industry peers. We focus on the crucial changes to organizational structure, governance processes, and resource plans to address the identified capability gaps and develop a comprehensive transformation plan. We work with our clients to execute this transformation plan, conducting controlled experiments to deliver immediate impact while establishing the road map to apply advanced analytics capabilities on a routine basis to navigate constantly changing and competitive business environments.
Through hands-on, collaborative efforts, we help our clients transform their approach from a focus on reactive analytics to a focus on developing the anticipatory and predictive analytic capabilities that confer growing advantage.
2) Big Data Analytics
Large, successful category leaders such as Wal-Mart, Goldman Sachs, Google, and Amazon have one important thing in common: They analyse data on a scale that has never before been considered possible. Most also analyse types of data that were previously unavailable and aggregate data from a wide variety of sources. In short, they manage Big Data.
From Data to Insights
Big Data is different from simply capturing data in traditional large databases, not only in the tools needed (often non-relational databases) but also in the hardware, and importantly, the analytical capabilities to transform this data into valuable insights. Big Data analytics run on hundreds or thousands of blade servers. Jobs are distributed across intelligent parallel processing grids. The power of this parallel-processing approach means that analytics can be employed operationally in real time for personalization, segmentation, pricing optimization, real-time interactions with clients, and rapid inventory fulfilment, as well as for business intelligence roles such as planning, prediction, and trend analysis.
The potential of Big Data analytics is significant. Superior skills with Big Data analytics can improve sales, increase profitability, and increase customer satisfaction. Conversely, failure to match competitors' capabilities will lead to loss of market share and declining competitiveness.
A Leap Forward
Wexcore's Analytics Practice works with clients to develop a successful road map for developing and improving Big Data analytics. This capability, new for many organizations, requires senior executive level support to succeed. It means deploying the right data management platform, developing the right capabilities, and actively investing in using the best-fit advanced analytics tools. It will often require hiring and training for new skills and affect a company's strategic IT priorities and investments. The large data processing requirements will require strategic plans and operating models for managing the complexity of Big Data analytics.
All told, this is a leap forward for many organizations, but now is the time to gain early expertise and advantage.
3) Data Visualization
Given the many ways humans can absorb information—seeing, hearing, touching—the ability to operate in and perceive a three-dimensional space is the highest bandwidth method of communication. This is the basis of interest for researchers working on virtual realities. It is also the basis for the increasing importance of data visualization.
Drowning in Data?
Companies are drowning in data, but the use of data has never been more important. As a result, two important trends are making data visualization essential. First, a great deal of data collection and analysis can be automated, creating greater availability of data. Second, the number of users requiring access to use and analyse data is growing as companies become data-driven.
Given the increase in data volumes and the variety of users accessing it, data needs to be presented in ways that make understanding quick and simple. And when questions arise, the ability to drill down into the data or slice the data so that it can be used from a different perspective must be simple, real time, and accessible to non-specialists.
Information: Clearer, More Compelling
Wexcore 's Analytics Practice uses sophisticated visualization solutions to present information more clearly and compellingly, increasing our clients' ability to interact with their models or data. Unlike static and ad hoc reporting tools, which often require significant customization by highly technical users, the interactive dashboards and reporting solutions developed using repeatable visualization approaches allow users to work directly with the data, thereby engaging a broader and more diverse audience in analytics-driven decision-making processes.
Visualization has proven to be indispensable in complexity management projects, optimization assignments, and Big Data projects, helping our client teams identify and explore new pockets of value—the kind that initially may appear counterintuitive but on further inspection can be quite relevant and profitable.
4) Predictive Analytics
Data is not the same thing as insight. Companies need insights that they can turn into action—about customers, processes, costs, suppliers, and their metrics on performance. And the more complex and competitive the market is, the more likely that predictive analytics will be important for growth.
Past is Prologue
The past rarely repeats itself. However, looking at historical patterns can help prepare decision makers to make better choices in the future. Wexcore’s Analytics Practice uses predictive analytics to help clients navigate their increasingly complex organizational structures, supply chains, and customer bases to understand “what’s next” and “what we should do” to capitalize on emerging opportunities. Using techniques such as regression analyses, exploratory analytics, optimization, and simulation, we help clients identify and capture margin improvements, understand and manage risks, capture new growth opportunities, and better manage their existing and future customer segments.
In our predictive analytics projects, we typically follow three steps:
Ensure data relevance and integrity: One-size-fits-all data warehouses typically need to be tailored, which often require additional information sources or cleaning up existing information.
Analyse the drivers: Attempts to verify existing hypotheses and determine so-called “predictability factors” often lead to counterintuitive insights. Exploring these insights through exploratory analytics is a crucial element in predictive analytics.
Model the future: To make things relevant for decision-makers, it is also necessary to project the future based on scenario modelling techniques and/or assumptions. The predictive drivers are then applied to help management make the appropriate decisions.
In each of these steps, we combine technical skills with the appropriate business acumen to simplify appropriately and find innovative solutions to complex challenges. Our pragmatic approach ensures that the causes and effects are well understood and involve all key stakeholders in defining a model with a high level of buy-in. This collaborative working style also helps ensure that client team members are able to take ownership of leave-behind solutions.
Finding the Right Answers
Predictive analytics can provide vital insight into fundamental questions across a broad array of business issues. Some examples include:
Scenario planning: What strategic actions will have the biggest impact on my business?
Risk assessment: How can I mitigate the risk of certain strategies?
Business modelling: How will changes to setups or operating models affect my top and bottom line?
Strategic gaming: How will my competitors or the market react to certain strategic moves?
Real options: How to evaluate major investment alternatives or capital expenditure projects?
Sales and Marketing
Marketing strategy: What offerings should be offered to which customers?
Micromarketing: How can I target customer segments more effectively using both internally available data and new media sources?
Return-on-marketing invested: What marketing or sales approaches will have the greatest impact?
Churn management: Who are my at-risk customers, and what can I do to keep them?
Value chain design: How do I construct my value chain to be most agile, cost effective, and customer oriented?
Network optimization: What are the best network design options based on potential market scenarios?
Resource allocation: How do I best assign assets, resources, and supply sources to respond to volatile or disruptive demand?
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