Business Pace Contributes to Data Challenges

The increasing speed and pace of business certainly contributes to several data challenges (quality, timeliness, availability and, most important, usability of the data). As the number of data sources increase and data volumes expand along with the demand from the business to access data on a timelier basis, pressures begin to form on the underlying technology. Many organizations look to technology to solve their data challenges when often these challenges exist because of a lack business support and buy in in the form of things like sponsorship, funding and process of approach.

Outdated technology or a poor technology implementation can certainly increase the number of challenges an organization has to manage, but these are sometimes just the tip of the iceberg. Larger organizations require much more of a transformational change. This transformation should enable the organization and its leaders to think about their data and how they can start managing data as a corporate asset instead of an afterthought. Positioning data in this way can increase sponsorship from leadership; if data provides value to an organization, leadership will be more open to new and innovative approaches to harness that value.

When the business department’s data needs outpace the ability of IT departments or their current technologies, business users are affected by the timeliness and availability of data. Business leaders often view these data challenges as an IT issue or lack of ability to meet the business needs, when the reality is that the organization probably has several dynamics that should be addressed to deliver value to the business. Regardless of technology solution, failure to address these organizational dynamics will result in an organization that continues to struggle. To be successful with data initiatives you must manage the organizational dynamics of the business to implement a successful data and analytics program. Successful data and analytics programs require a combination of people, processes, data, and technology to deliver value to the business.

Data delivers value to the business by solving the organization’s information needs as it relates to effective decision making and the ability to act based on those decisions.  There are many areas where organizations go wrong in the process but by far the most difficult challenge is establishing a collaborative environment where everyone throughout the organization can work together. By involving users and leadership from both business and IT in any technology implementation, an organization can instill a sense of ownership for all parties involved as well as enhance user satisfaction with the finished product. Transforming an organization that has successfully managed organizational dynamics results in a strong partnership between the information technology and business teams where they have a shared vision for their data and analytics program. The vision should align both business and technical strategies to ensure that the data and analytics priorities are aligned to the business strategy and the proposed solutions are in line with the future state information technology architecture.

This process is an exercise in effective leadership which is paramount to the future success of the data and analytics program. There are a few approaches to organizational alignment but the one approach I’ve been successful with is taking a center of excellence approach. There are several steps to this type of approach:

  1. Establishing a virtual group of representatives that consists of leaders from all areas of business and information technology teams. At a high level, they will be tasked with setting the overall vision for the program, leadership, governance, communication, prioritization, change management, and controlling the budget.
  2. There should be an extended team that has a combination of business, information technology, and analytical skills. The business skills team needs to have a very good understanding of the business needs and organization’s business processes. The individuals with business skills will be tasked with prioritization and change management largely driven from the business case justification established for each initiative. 
  3. The IT skills team needs to have a deep understanding of data management and data architecture. The ability to architect a solution that further matures the business intelligence program laying the foundation for future initiatives is critical. 
  4. Lastly individuals with analytical skills who have a combination of both business and information technology skills. These individuals will be responsible for leading the development of the business case and turning the business problems into business intelligence solutions.

This center of excellence approach is a great way to align people, process, data and technology. The resulting business use cases can be taken back to leadership packaged nicely within their chosen business intelligence solution, and leadership will be able to visualize the ROI immediately. This approach will leave organizations with quality data that is available in real or near real time, and since both business and IT have been involved in the process, there is a higher user adoption rate in the new technology. With this collaborative process, it will be easier for IT departments to gain sponsorship from both IT and business leaders and in turn, funding should be more readily available in the future. Most importantly, this centralized approach allows IT departments to react more nimbly to business needs, because they have strong executive sponsorship that understands the value that this type of approach can deliver to the business.

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Mike Sargo

Mike Sargo

Mike Sargo is Chief Data and Analytics Officer and Co-Founder of Data Ideology with over 18 years of experience leading, architecting, implementing, and delivering enterprise analytics, business intelligence, and enterprise data management solutions. Mike is a graduate of both, the University of West Virginia where he earned his Bachelor of Science in Management Information Systems, and of Mountain State University where he earned his Master of Science in Strategic Leadership. He has extensive experience leading enterprise wide preservation and modernization projects focusing on data strategy, analytics roadmapping, solution architecture & design, and implementation.

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