Monday, April 27, 2015

Data or Process, Which is More Critical in Decision Making?

Data without process has no meaning; process without data gives no meaning.

Decision making is a daily challenge for most business leaders because organizations become over-complex, hyper-connected, uncertain and ambiguous. What is more important to effecting good decisions within your organization? A sound process? Or the "best" (reliable and relevant) data? What’s your best scenario to make effective decisions?


Data quality is important. If you mine, cleanse and improve the data to produce information, combine that information and visualize it in different ways, then you gain organizational knowledge and from that knowledge, you can make excellent tactical decisions. Knowledge is firmly rooted in context. A database is simply a database and is context agnostic. Data patterns can be viewed over time in the form structured and unstructured data, however, this does not give you knowledge of what is going on only some insights of possible weak signals. These insights need to be vetted before being implemented, and this is where the process of prioritization and selection becomes so critical. The Data -> Information -> Knowledge process should then be cognizant of the right ways to work (Process). Thus, the Data>Information>Knowledge tactics route will encompass all (most) of what you need.


A sound process to frame decision is critical: Part of the problem is in the framing. You need a sound process to frame the decision, spec out your options, weigh them appropriately with the right people, and actually make a decision. The importance of the process becomes critical as decisions become more complex and involve more diverse stakeholders. If you hang around the word data, It’s the process. From an organizational and business optimization point of view - Process is the sequenced series of tasks. What do tasks need to be performed? Next, look at in which sequence these tasks should be performed to generate optimal value. Within the tasks associated with the element of the business decisions, data are fluid in the sense that it is constantly added to or subtracted to dependent on the task.
-Identification of tasks.
-Understanding the tasks and how they should be sequenced.
-How to leverage data associated with tasks optimally to make effective decisions.


Process without data gives no meaning: Processes are governed by data. That does not mean processes should be "super glued" to data. In IT, there’s a tendency to do exactly that. Mainly for engineering methodology and project driven (requirements-driven design) reasons. The result is more often than not duplications of functions and processes. This is resource demanding, time-consuming and costly. If processes are given precedence over data, it can get a much higher degree of reusability and drive down unit cost. The decision at hand and the criteria prescribed should drive the data, with the understanding that scenario analysis may require more iterations of data. With an effective process, if you mine, cleanse and improve the data to produce information, then combine that information and visualize it in different ways, then you gain organizational knowledge and from that knowledge, you can make excellent tactical decisions.
Data without process has no meaning: Lots of data tends to overwhelm our cognitive decision-making processes. In Big Data and cognitive analytics, maybe data enrichment and correlation are on the surf of more data-driven than process driven. But in this case, the process is system flows, and PROCESS (Tasks) is key to identify the purpose of the analytics. Essentially, a process is a collection of tasks assigned to specific roles, designed to convert specific inputs into specific outputs to answer specific questions. More complex processes, such as larger scale prioritization of R&D, capital budgets, strategic options, etc tend to cut across organizational functional boundaries and engross different stakeholders. As to judgment, virtually nothing is certain in business, so judgment must be based on the best information available.


Obviously, both are important, data is the means to the end, not the end. It is critical to frame the right question via sound process, and manage data quality also via an effective process. Making an effective decision is all about to have the right person to leverage the right information, following the right process, to make the right decisions at the right time.













0 comments:

Post a Comment

Twitter Delicious Facebook Digg Stumbleupon Favorites More