Descriptive vs Diagnostic vs Prescriptive vs Predictive Analytics
Data is the Key to Survival
It’s clear that data is becoming a critical business asset, central to the success of every company. Companies that don’t evolve and embrace the data revolution will be left behind. A recent study found that 79% of executives say that companies who don’t embrace data will “lose market strength and may face extinction.”
Data leads to analytics – descriptive, diagnostic, predictive and prescriptive. But, the first step is what is the business case and are you working with operational data or consumer data?
What is Data and What Can I Learn from It?
Data includes many things you may be tracking right now:
- Operational Data – finance and production reports, such as cash-flow reports and budgets, sales figures, staff productivity report, etc.
- Consumer Data – customer behavior, customer profiles, level of brand awareness, and level of engagement through website and content, etc.
Each of these offers a lot to your business, but together, they are powerful:
Better business decisions – market and consumer intelligence
- Grow revenues
- Consumer loyalty
- Better products and services
Better business operations – internal company intelligence
- Reduce expenses, overhead, and risk
- Run the business
- Process optimization
Types of Data Analysis
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Analysis methods range in complexity and in what questions they can answer:
- Descriptive Analytics—what has happened (in the past this was called Key Performance Indicators or KPIs)
- Diagnostic Analytics—why did it happen (in the past new data, often qualitative would be collected to understand what happened and this is still the best method today)
- Prescriptive Analytics—what should happen (in the past this was called adaptive software engines that adapt and prescribe what a customer needs)
- Predictive Analytics—what will happen (in the past this was called modeling or forecasting models)
- Preventative Analytics—what early data signs are indicating a decrease in performance or an increase in risk (in the past this was often manual, but sophisticated statistics can flag early warning signs)
Data analysis can give you answers that help you maximize profit and make the right decisions for your business. In addition, you can put your data to work with prescriptive and predictive analytics that produces actionable data findings that can generate revenue:
- Demand/sales forecasting
- Market and external factors forecasting
- Competition analysis
- Lead lifetime value
- Customer acquisition
- Customer service escalation
- Customer retention/churn prediction
- Price optimization
But you have to ask the right questions, use the correct information, and apply the right analytics to find the right answer accurately.
That’s How Horizon Can Help
We use an active scientific process for gathering the right data, doing the right analysis, arriving at the right answer that includes:
- defining clear objectives
- applying well-thought-out analysis design and methods
- extracting and collecting good data
- using the correct analysis
- drawing the right conclusions, predictions, and extrapolations
Despite the large amount of data that already exists within a company, more often than not the intelligent collection of additional data is necessary and when combined with existing data, is often the difference in maximizing profit. Horizon has significant experience in the intelligent design and collection of data.