Business Intelligence: Corporate Planning

The connection of business intelligence (BI) and corporate planning is in its infancy stage. This post will discuss how can BI play a bigger role in corporate planning. Remember, a small, medium, or large organization deals with planning differently, so BI solutions are not a one-size-fits-all. Also, this post addresses how can BI include the emerging premise of knowledge management (KM), and how do both support corporate planning.

Advertisements

Corporate Planning

The main difference between business planning and corporate planning is the actors.  They both are defining strategies that will help the meet the business goals and objectives.  However, business planning is describing how the business will do it, through focusing on business operations, marketing, and products and services (Smith, n.d).  Meanwhile, corporate planning is describing how the employees will do it, through focusing on staff responsibilities and procedures (Smith, n.d.).  Smith (n.d.) implied that corporate planning will succeed if it is aligned with the company’s strategy and missions, drawing on the strengths and improving on its weaknesses. A successful and realistic corporate and business plan can help the company succeed.  Business Intelligence can help in creating these plans.  In order to make the right plans, we must make better decisions that help the company out, and data-driven decisions (through Business Intelligence).  Business Intelligence, will help provide answers to questions much faster and quite easily, make better use of the corporate time, and finally aid in making improvements for the future (Carter, Farmer, & Siegel, 2014).

A small, medium, or large organization deals with planning differently, so BI solutions are not a one-size-fits-all.  Small companies have the freedom, creativity, motivation, and flexibility that large companies lack (McNurlin, Sprague, & Bui, 2008).  Large companies have the economies of scales and knowledge that small companies do not (McNurlin et al., 2008).  Large companies are beginning to advocate centralized corporate planning yet decentralized execution, which is a similar structure of a medium size company (McNurlin et al., 2008).  Thus, medium size companies have the benefits of both large and small companies, but also the disadvantages of both.  Unfortunately, a huge drawback on large organizations is a fear of collaboration and tightly holding onto their proprietary information (Carter et al., 2014). The issues of holding tightly to proprietary information and lack of collaboration is not conducive for a solid Knowledge Management nor Business Intelligence plan.

Business Intelligence

Business Intelligence uses data to create information that helps with data-driven decisions, which can be especially important for corporate planning.  Thus, we can reap the benefits of Business Intelligence to make data-driven decisions, if we balance the needs of the company, corporate vision, and the size of the company to help in choosing which models the company should use.  A centralized model is when one team in the entire corporation owns all the data and provides all the needed analytical services (Minelli, Chambers, & Dhiraj, 2013).  A decentralized model of Business Intelligence is where each business function owns its data infrastructure and a team of data scientists (Minelli et al., 2013).  Finally, Minelli et al. (2013) defined that a federated model is where each function is allowed to access the data to make data-driven decisions, but also ensures that it is aligned to a centralized data infrastructure.

Knowledge Management

McNurlin et al. (2008), defines knowledge management as managing the transition between two states of knowledge, tacit (information that is privately kept in one’s mind) and explicit knowledge (information that is made public, which is articulated and codified). We need to discover the key people who have the key knowledge, which will aid in knowledge sharing to help benefit the company.  Knowledge management can rely on technology to be captured and share appropriately such that it can be used to sustain the individual and sustain the business performance (McNurlin et al., 2008).

Knowledge management can also include domain knowledge (knowledge of a particular field or subject).  The inclusion of domain knowledge into a data mining, which is a component of Business Intelligence System has aided in pruning association rules to help extract meaningful data to aid in developing data-driven decisions (Cristina, Garcia, Ferraz, & Vivacqua, 2009).  In this particular study, engineers helped to build a domain understanding to interpret the results as well as steer the search of specific if-then rules, which helped to find more significant patterns in the data (Cristina et al. 2009).

The addition of domain experts helped captured tacit knowledge and transformed it into explicit knowledge, which was then used to find significant patterns in the data that was collected and mined through.  This eventually leads to a more manageable set of information with high significance to the company to which data-driven decisions can be made to support the corporate planning. Thus, knowledge management can be an integral part of Business Intelligence.  Finally, Business Intelligence uses data to create information that when introduced with experience of the employees (through knowledge management) it can then create explicit knowledge, which can provide more meaningful data-driven decisions than if one were to focus on a Business Intelligence Systems alone.

The effectiveness of capturing and adding domain knowledge into a company’s Business Intelligence System depends on the quality of employees in the company and their willingness to share that knowledge.  At the end of the day, a corporate plan that focuses on staff responsibilities and procedures revolving both in Business Intelligence and Knowledge Management will gain more insights and a higher return on investment that will eventually feed back into the corporate and business plans.

References

  • Carter, K. B., Farmer, D., & Siegel C., (2014). Actionable Intelligence: A Guide to Delivering Business Results with Big Data Fast!. John Wiley & Sons P&T. VitalBook file.
  • Cristina, A., Garcia, B., Ferraz, I., & Vivacqua, A. S. (2009). From data to knowledge mining. http://doi.org/10.1017/S089006040900016X
  • McNurlin, B., Sprague, R., Bui, T. (2008). Information Systems Management, 8th Edition. Pearson Learning Solutions. VitalBook file.
  • Minelli, M., Chambers, M., and Dhiraj A. (2013). Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses. John Wiley & Sons P&T. VitalBook file.
  • Smith, C. (n.d.) The difference between business planning and corporate planning. Small Business Chron. Retrieved from http://smallbusiness.chron.com/differences-between-business-planning-corporate-planning-882.html

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s