Big Data and Cloud Solutions: Implications for Sourcing

Many enterprises are searching for ways to unlock value through data analytics and the use of big data analytical techniques. To do this, enterprises can draw on multiple internal and external sources of data and processing, potentially involving internally hosted data sets, cloud-based processing solutions and traditional externally sourced or outsourced services. These complex projects can create equally complicated contractual relationships. The challenge for sourcing lawyers is to ensure that sourcing procedures and contract terms are adapted to address this complexity.

Big data involves drawing data from a potentially wide variety of data sets that, historically, were not designed to be combined. Big data applies analytical tools and processes to those data sets to see if meaningful correlations and relationships exist. Value is created when actionable insights are drawn from the analysis. The data sets can be drawn from either:

• Separate systems within a single enterprise (for example, from CRM and ERP systems).
• External systems and data sources (for example, market analytics firms, geospatial records, government records and weather systems).

Underpinning big data are the key enablers of cheap and massively scalable computing power and an exponentially growing ecosystem of networked (and therefore potentially accessible) data.

In a big data project, a company may wish to gain insights about its customers by analysing browsing and purchase data drawn from many sources. For example, the company might analyse data from:

• Its internal systems.
• Customer interactions managed by an outsourced call centre.
• Demographic or geographic data drawn from independent websites and data sources.

If the company requires third party expertise to conduct the project, it can engage consultants or take advantage of the many analytics-as-a-service solutions that have emerged. These range from specific data or transaction types to generic capabilities in enterprise platforms including SAP, Oracle and Microsoft.

The company may also wish to use several different cloud-based solutions in conducting its project. For example, the company can:

• Collect data from CRM systems, website comments, social media sites and other systems often hosted in the cloud.
• Store the data collected in a public cloud to obtain optimal pricing and scalability.

These cloud-based solutions raise important issues that should be addressed in the sourcing process.

This article provides checklists of issues that the company should consider when conducting a project of this nature.

Download: Big Data and Cloud Solutions: Implications for Sourcing