Many companies are investing heavily in analytics and business intelligence. But some are beginning to wonder whether these efforts will ever return the value they were hoping for. Analytics yield zero value — until they're used to improve decisions. Hence the importance of what we call decision analytics.
Most existing analytics is like turbocharging your rearview mirror. It captures detailed customer and market data, usually combining online and offline activities. It summarizes the data, with statistical tools to identify and visualize interesting patterns. Descriptive analytics can yield useful insights, but it's limited to understanding the past.
Some companies are looking at what their data says about the future. They apply statistical forecasting methods to extrapolate trends from historical data, for example, estimating future demand, and projecting changes in markets. These results can yield more value, a GPS or Sat Nav to help the company visualize possible futures. But, it's not yet actionable — using the wheel to choose your direction.
The ultimate goal is to use the insights from the data to take action — to steer your organization in a more profitable direction. To make this practical, you need tools that focus on key business decisions: To allocate marketing dollars, set prices, enter new markets, design new products, and plan capacity. Descriptive and predictive analytics are essential, but they don't take you the whole way. Typically, you need to combine the data and forecasts into a model of ROI to clarify the costs and benefits of alternative routes. When you drive through the fog of uncertainty, exploration of alternative scenarios and probabilistic risks lets you discover robust and flexible decisions. For complex decisions, you may need optimization tools to find the most rewarding strategies.
Data versus judgment?
Some analysts aim to substitute data for judgment in business decisions. Certainly, large quantities of data, from online and offline sources, along with powerful analytic tools, can greatly improve the information available for effective decisions. But, however much data we have and however sophisticated our tools, they won't eliminate uncertainty. Markets are increasingly volatile. The competitive landscape evolves rapidly. Customers leave. New markets appear. New technologies cannibalize old ones. In these situations, insights from data are not enough. The intuition and judgment of experienced executives, sales managers, and market analysts are more important, not less. You need tools that let you combine the most informative descriptive and predictive analytics with the expert judgment of your best people.
Decision analytics at Lumina
Lumina has specialized in decision analytics since it was founded in 1991. Our experienced consultants have assisted many organizations toward improving their decision processes, helping them gain real value from their investments in analytics. Our first step is often to help you identify which kinds of business decisions can be most easily improved by judicious use of focused analytics.
We can build on your existing tools, develop tools customized to your needs, or train your staff to develop and extend tools themselves.
Analytica was designed from its inception to build flexible decision analytics tools: Its influence diagrams provide a visual way to build and navigate models. They clearly distinguish decisions, objectives, data, and uncertain variables. Analytica offers intelligent forecasting methods with stepwise regression to find the most informative predictors automatically. It integrates Monte Carlo simulation to treat risk and uncertainty. Scenario and sensitivity analysis help you find out what matters and why.
- Analytica Enterprise integrates your existing data sources and analytics tools. It scales flexibly to handle multi-dimensional hypercubes and huge datasets.
- Analytica Optimizer includes state-of-the-art solvers for challenging optimization problems.
- Analytica Cloud Player lets you deploy decision tools on the web in seconds for easy access and collaborative analytics.
Click here to see an excellent example of decision analytics using Analytica for media advertizing.
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