“Add Value to Your Organization by Leveraging the Benefit of Big Data..!”
Our Strategy: Better Targeted Customer Marketing, Improve Product Analytics, Business Planning, Supply Chain Management, Fraud, Waste & AbuseIncrease Revenue & Lowering Cost through increasing productivity
Our business analytics faciliate realization of business objectives throug reporting of data to analyse trends, creating predictive models to foresee future problems and opportunities and analsing/optimzing business process to enahnce organizational performance.
Descriptive analytics, also called business reporting, uses the data to answer the question of “what happened and/or what is happening?” It includes simple standard/periodic business reporting, ad-hoc/on demand reporting as well as dynamic/interactive reporting (OLAP, slice/dice, drill-down/roll-up, etc.). The main output of descriptive analytics is the identification of business opportunities and problems.
Predictive analytics uses data and mathematical techniques to discover explanatory and predictive patterns (trends, associations, affinities, etc.) representing the inherent relationships between data inputs and outputs. In essence, it answers the question of “what will happen and/or why will it happen?” Enablers of predictive analytics include data mining, text mining, Web/media mining and statistical time series forecasting. The main outcome of predictive modeling is an accurate projection of the future happenings and the reasoning as to why.
Prescriptive analytics uses data and mathematical algorithms to determine a set of high-value alternative courses-of-actions or decisions given a complex set of objectives, requirements, and constraints, with the goal of improving business performance. These algorithms may rely solely on data, solely on expert knowledge, or a combination of both. Enablers of prescriptive analytics include optimization modeling, simulation modeling, multi-criteria decision modeling, expert systems and group support systems. Thema in outcome of prescriptive modeling is either the best course of action for a given situation, or a rich set of information and expert opinions provided to a decision maker that could lead to the best possible course of action.View our industrial applications in Big data analytics and our Data Visualization techniques Big Data Analytics for Industrial Applications
Are your firm still struggle to make decision that better match supply and demand. We enable you to apply analytics to every level of supply chain, from raw material sourcing to production and distribution. Our analytical techniques would enable your firm to enhance demand forecasting methods, detect supply chain disruptions and improve communications in supply chain that often global.
In particular guires help to track strategic, tactical, and operational decision [The Supply Chain Operations reference (SCOR) model developed by the Supply Chain Council (www.supply-chain.org)] using a variety of analytical tools. If your industry is concerned with generating accurate demand forecasts to drive planning (long, mid and short term) and inform resource allcation, we help you to make accurate decision at all levels of supply chain. We apply wide analytical techniques.
The techniques includes descriptive Analytics (to map supply chain and visualization) to derive information from the significant amuonts of data and answeres the question of “what is happening within your firm” or “what happened”. We present simple standard/periodic business reporting, ad-hoc/on-demand reporting as well as dynamic/interactive reporting (OLAP, slice/dice, drill-down/roll-up, etc). By applying these analysis helps in the identification of business opportunities and problems
Predictive Analytics in supply chains derived demand forecasts from past data and answers the question of what wil be happening – Time series methods (e.g. moving average, exponetial smoothing, autoregressive models), Linear, non-linear and Logistic regression; Data-mining techniques (e.g., cluster analysis, market basket analysis)
Prescriptive analytics derives decision recommendations based on descriptive and predictive analytical models and mathematical optimization models.
Models we apply: Analytic hierarchy process, Game theory (e.g., auction design, contract design) – Mixed integer linear Programming (MILP), Non-linear programming (Network flow algorithms, MILP and Stochastic dynamic programming). In addition to the above, guires enables to apply analytics techniques in various areas such as auction, sales and operations planning, transportation and distribution planning, invenoty management, dynamic pricing and revenue management, manufacturing scheduling and workforce scheduling.
We apply various analytics methods to would benefit your firm. A multinominal logit model: This model would enable retailers to understand how marketing mix decision – price and promotion decision in particular –influence the sales and market shares of the product you sell. Conjoint analysis: This analysis capture consumer prefereces and measuring tradeoffs by estimating the consumer part-worth utilities for each attribute level of a product. Guires is pioneer in analysing various types of conjoint analysis such as rankings, ratings, and choice based alternative exists. In addition, even for new product development market share model, conjoint analysis and DCA have been applied.
Market potential for new products: Due to the fuziness exists based on the jury of expert opinion, which would significnatly affect the predictive accuracy of developed market.
Financial and Accounting:
In the financial industry, we apply revenue and profit forecasting, prediction of loan default, fraud detection and identifying money laundering, among others. In addition, we also enable to examine the effects of financial reports on stock prices, the cost of capital and other basic economic factors. We group behavioural data and statitistical techniques to identify the right type of customer for your product and service. We use existing data and collect new data to identify
Data Visualization techniques
Data Visualization techniques used at GuiRes offers solution to support rapid integration and interpretation of complex data and to discover new trends. Our statistician team graphically analyzes the complex set of data to facilitate corporate communication that would discover new opportunities, find fresh evidence to support decisions, track performance and analyze market attractiveness. GuiRes supports visualization analysis to wide range of industries such as travel and tourism, retailing, media and telecommunication and online, government, consumer goods, banks and consultancies and advertising.