Some key analytics solutions we offer revolve around DDDM.

Data-driven decision making (or DDDM)

This is a process which involves collecting data, extracting patterns and facts from that data, and utilizing those facts to make inferences that influence decision-making. Therefore it is the process of making organizational decisions based on actual data rather than intuition or observation alone.

To effectively utilize data:

  1. KNOW YOUR MISSION:
    We take time to understand the business, the industry and then try to gather the business questions that need to be answered in order to achieve a goal. This helps us to gather the right data and strategically build the right analytics solution.
  2. IDENTIFY DATA SOURCES:
    The next thing we do is understand the data sources of our clients, some may be internal or external. These play a key role in the entire life of a project. We coordinate with various stakeholders and other web APIs to get access to the data we need.
  3. IDENTIFY DATA SOURCES:
    The next biggest task we undertake is cleaning the data and this takes up most of our time. Most analysts understand the “80/20 rule” where 80% of the time is spent on data cleansing and 20% on analysis.
  4. IDENTIFY DATA SOURCES:
    The next biggest task we undertake is cleaning the data and this takes up most of our time. Most analysts understand the “80/20 rule” where 80% of the time is spent on data cleansing and 20% on analysis.
  5. IDENTIFY DATA SOURCES:
    Once we have thoroughly cleaned the data, we begin to analyze the information using statistical models. This is when we start testing different models such as linear regressions, decision trees, random forest modeling.
    We then decide how to present the information in order to answer the question at hand. There are three different ways to demonstrate your findings:
    • Descriptive Information: Just the facts.
    • Inferential Information: The facts, plus an interpretation of what those facts indicate in the context of a project.
    • Predictive Information: An inference based upon facts and advice for further action based on your reasoning.
  6. DRAW CONCLUSIONS:
    This is the final stage of our project that involves coming to a conclusive answer to the question at hand. We prepare effective presentations and storytelling techniques to present findings with key stakeholders making sure the questions are answered as effectively as possible. The conclusions drawn from our analysis will ultimately help your organization make more informed decisions and drive strategy moving forward.
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Predictive Analytics

Predictive analytics goes beyond simple analysis to provide insights in what can be expected in the future and how to get the best outcomes. We have a vast experience in predictive statistics and always follow the highest professional or regulatory standard in our process. Some of the projects involve:

  • Lifetime Value
  • Fraud detection
  • Segmentation
  • Pricing Applications
  • Retention
  • Price elasticity and price optimization
  • Campaign Analytics / Optimizing campaign spending
  • Improve direct marketing response
  • Up-selling and cross-selling potential
  • Credit Analytics – Predicting profit/loss or the likelihood of defaulting
  • Forecasting

Kendooit Labs offers various statistical forecasting services for improving the operational performance of your company. Whether you need an outsourcing partner to develop and run your forecasts, or just need help in improving your existing forecasting process, we can help.

Experience & Application: Statistical Forecasting Applications

  • Sales forecasting
  • Accounts Receivable
  • Bad debt forecasting
  • Demand forecasting
  • Maintenance forecasting
  • Data Mining

PKendooit Labs is ready to mine through your large complex data sets and uncover patterns that your business needs going into the future.

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