Big Data, IT Alignment and the Quest for Meaning: A Research Project

by   |   May 8, 2013 4:29 pm   |   0 Comments

Growth has slowed. Profitability is a tough slog. Information Technology (IT) budgets are getting squeezed.  Today, IT organizations are saddled with the costs of maintaining software, but getting funds to start net new projects is difficult. It is made even harder when the IT leaders’ organizations are not aligned with their business counterparts or when the business functions are not aligned to a corporate strategy. Most organizations agree that alignment is critical to success, but they are not clear what alignment looks like.

Yet even with these challenges, the opportunities presented by IT innovations seem to be endless. Cloud computing, parallel processing, new forms of analytics, mobility, and better visualizations offer new answers to solve enterprise problems. The excitement had led to new categories of enterprise solutions entering the market. At the same time, the barriers to the adoption of new technologies are lower. Line-of-business buyers can easily acquire technology through operational budgets and IT organizations are often surprised to find that they need to “integrate” and maintain systems that they did not know existed.

Many companies understand that big data is enabling solutions to gain business benefit that companies never imagined ten years ago, but questions swirl. Questions such as:

  • How can the IT organization morph to tackle new problems if the business is not aligned and there is no clarity around a big data strategy?
  • Is the adoption of these new types of technologies a revolution or an evolution?
  • Do we have a big data problem or is it a big data opportunity?
  • What do the new software packages mean for existing enterprise solutions?
  • And, in the adoption of new techniques using big data processes, do we solve age-old problems like master data management (MDM)?

We at Supply Chain Insights LLC are busy trying to answer these questions. We would love your help. We have designed two studies to help us better understand how leaders should take action:

How well is your organization aligned? Click here for the alignment survey.

Do you have a “Big Data” problem or opportunity?  What does Big Data mean for you? Click here for the big data survey.

The surveys are designed to drive insights to understand how well organizations are aligned on the goals of IT spending, and how they are spending money on new technologies.  We are attempting to correlate the answers on alignment to what is measured and then correlate the answers to financial results.  We want to find out if, why and how much IT and business alignment matters.

We also want to find out if organizations that are better aligned making more or less progress in the adopting of processes to take advantage of the changing nature of data.  (Are they able to increase the use of data in the face of disparate data types, increased data velocity and exploding data volumes?)

We look forward to your response on our two surveys, and we would love to have the opportunity to share the data with you. We keep all answers confidential and report the data in aggregate. We will be working with Data Informed, and its parent company, Wellesley Information Services, to share data from the surveys in a series of blog posts specially designed to serve their readers.

Lora Cecere, the founder of the Supply Chain Insights research firm, is the co-author, with Charles W. Chase Jr., of Bricks Matter: The Role of Supply Chains in Building Market-Driven Differentiation (Wiley, 2012). You can read her blog, Supply Chain Shaman and follow her on Twitter @lcecere.

Related articles on Data Informed:

Guide to Leading Data-Driven Organizations

Guide to Procurement Analytics

Opinion: Supply Chain Leaders Know They Have a Big Data Problem

Opinion: Five Supply Chain Opportunities in Big Data and Predictive Analytics


Tags: , , ,

Post a Comment

Your email is never published nor shared. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>