Three ways to modernize and expand your analytics programs

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134113066The cottage industry was based on workers buying raw materials, bringing them home and producing hand-crafted items to sell. The system worked, but was slow, tedious and expensive, producing goods that were affordable only by the rich.

94364066The Industrial Revolution changed all that. The factory system brought machines and workers into factories that reliably and quickly produced mass quantities of items at a much lower cost.

You can easily see the connection to the analytical process. Too often today, the analytics process is run like a cottage industry: Workers get raw data from IT, analyze it in silos and produce predictive insights for their individual business units.

This is traditional analytics and was often "build as you go,” resulting in a hodge-podge of process, infrastructure and data. Too much effort is spent on data preparation and results integration, and not enough on investigation and fine-tuning statistical analysis and models.

Although insights produced by traditional analytics can be excellent, the level of quality is inconsistent. Each analytical process is different, and without consolidation and standardization, the production of analytics can’t easily scale to meet high demand and rapidly changing business needs.

In addition, with traditional analytics, innovation is rare because siloed analysts lack the time for data exploration, “what if” analysis or investigating new modeling techniques and processing technologies.

But there are solutions available to help industrialize and expand your analytics programs. If we apply the factory system to analytics, it’s composed of:

  • An analytics lab to investigate, fail fast and innovate in order to solve emerging business problems through new data modeling and processing techniques.
  • An analytics factory to standardize, consolidate and streamline the infrastructure, data and models through shared and consistent hardware, software and skills.
  • An analytics store to offer self-service analytics to business lines and tailor it easily to a rapidly changing market

These three analytics initiatives may have a direct impact on the cost, efficiency and therefore effectiveness of business analytics. A few mature organizations, especially in the financial services industry, have already invested in this approach. As a result, they’ve cut infrastructure costs in half and doubled the productivity of their analytics process.

To dig further into the benefits of innovation in the analytical process, please look at this Global Data and Analytics executive study and research report from MIT Sloan Management Review and SAS Institute.

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About Author

Marcel Lemahieu

Principal Business Solutions Manager

Marcel Lemahieu is Principal Business Solution Manager at the Analytical Platform CoE from the South West Europe region. Marcel joined SAS France in 2000 to develop the SAS market in France where he successfully contributed to the adoption of the SAS Platform by large French companies. His professional background is a mix of Statistics, IT projects and software sales. He started his career as Statistical Analysts in the Labor Ministry, Statistical Methods manager in a Survey company (BVA), IT Project Manager for a Media group (Havas) and Business Solution Manager at Informix. Marcel Lemahieu offer to SAS customer his long experience of Analytical projects at the French and International level in various industry: Media, Retail, Insurance, Bank, Public Sector. Marcel Lemahieu has a Master of Economic Sciences from Reims University.

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