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What is time-series forecasting?
This page provides an non-technical introduction to the notion of time-series forecasting. The purpose is to introduce the concepts in order to help you understand what Lokad is doing and how does it apply to your business.
Time-serie definition
A time-series is a list of dates, each date being a associated to a value (a number). For example, daily temperature measurement represent a time-series.
| Time | Value |
| Jan 1st, 2007 | 89 |
| Jan 2nd, 2007 | 91 |
| Jan 3rd, 2007 | 90 |
Time-series are interesting because many business operations are represented through time-series (daily sales for ex.). Typically, the time-series will represent a set of historical measurements. See below for further discussion.
Forecasting the time-series
The time-series can be represented as a curve that evolve over time. Forecasting the time-series mean that we extend the historical values into the future where the measurements are not available yet.
There are some subtleties in the definition a time-series forecast. For example, the historical data might be daily sales and but you need monthly forecasts. Grouping the values according to a certain period (ex: month) is called time-series
aggregation.
Lokad and Time-Series
Lokad delivers hosted time-series forecasting services. They are many different approaches to time-series forecasting; Lokad is using purely statistical methods (see our
technology for more details).
Our
add-ons let upload your time-series data to Lokad and retrieve the time-series forecasts afterward. In order to get the add-ons working, you need a
Lokad account. Your Lokad account is used to store your time-series data.
Business benefits
What you do with time-series forecasting depend on your business activity. Here below, we list typical ways of using time-series forecasting.
Time-series for Retail
The sales history of each product constitutes a time-series to be forecasted. The sales forecasts are used to optimize the inventory levels. Too much inventory, and your expenses go up. Too few inventory, and sales opportunities are lost in out-of-stock situations. Learn more about
Lokad benefits for retailers.
Time-series for Manufacturers
The production history and/or the inputs consumptions constitute time-series to be forecasted. The inputs consumptions are forecasted in order to minimize the inventory levels. The production history can be forecasted and used as an approximation of the future demand. Forecasting the demand enables to perform efficient capacity planning. Learn more about
Lokad benefits for manufacturers.
Time-series for Customer Services
Customer activities can be represented as time-series (ex: hourly volume customer calls in call centers). Forecasting the customer activity can be used to optimize the staff scheduling. Too much staff, and money is wasted in paying idle staff. Too few staff, and the customer satisfaction drops. Learn more about
Lokad benefits for call centers.