Strategic Decision: The Difference between Data and Good Judgment

Strategic decision making can encourage you to stronger better paths to achieve important goals. When decisions are well thought out they can help you get closer to where you want to be while using much less effort. Understanding the difference between data and the interpretation of that data helps in seeing and then figuring out the choices that lead down varying paths. A few tips may help you think through options and make more accurate choices that help you improving business and career outcomes.

Understanding the data and thinking through the options affords an opportunity to create critical thinking. Critical thinking can be defined as the objective analysis of information and options that leads to a decisive conclusion. To do this well requires that ability to see the possibilities and pick the ones that are not only most likely but also help you achieve your goals. 

Step 1: Define Your Goals: Knowing your goals and what you want to accomplish might be the hardest part of thinking strategically. We may think the data should define our goals but that isn’t always true. Our general direction and goals be a guide to our everyday decisions to ensure we have a framework for interpreting new data. Keeping your long term goals in mind will help you make the daily decisions that help you get there. 

Step 2: Understand the Data: Understand what the data covers and what it doesn't. This requires knowledge of the methods of data collection and the areas that the data has no measurement. Better knowledge of the data will help you stay away from illogical interpretations. 

Step 3: Evaluate the Interpretations: Data is just numbers and letters but there are always multiple interpretations of that data; the most popular isn't always the most accurate. Make sure that you understand all of the most likely interpretations of the information to ensure that the main paths are exposed. This is important if you want the full breadth of options because some of the best one's are not always apparent.

Step 4: Narrow Down the Paths: Based upon logic, experience, risk, and reward narrow down your options to the one or two that will most likely help you achieve your goals. Out of the many possibilities only a few will make any real sense to you. Some can be discarded right away.

Step 5: Select Option and Alternative Option: Among the remaining few options you should select the primary and the secondary option as a strategic action forward. If the primary doesn't work out for some reason you can fall back on your secondary plan. The final selection should include not only your experience, and knowledge, but also sound judgement as this is the selection that will impact a future course of events.

Improving Investment Decisions with Decision Making Models

Investment decisions can have a large impact on society. All investment decisions contain an inherent level of risk. This risk is associated with poor returns, loss of money, missed opportunities or even bankruptcy. Research by Wu , et. al. (2012) creates an analytical hierarchy process-group decision making model (IAHP-GDM) that works to complement group decision-making for more accurate investment decisions. 

The types of risks investment managers make are related to strategy selection, social risks, policy risks, credit risks, economic risks, technology risks, interest rate fluctuation, operational risks, and contract risks (Shen, 2009; Zavadskas, et. al., 2010).  Decision-makers should seek to understand these risks and attempt to encourage the best decisions possible. This can become even more difficult when higher volumes of information create confusion. 

These risks can be heightened when one person makes decisions based upon limited knowledge. In an investor’s perspective decisions move through four components that include problem recognition, information search, evaluation of alternatives and finally investment decisions (Shyng et. al, 2010).  Personal experience can be an enhancer or detractor in terms of bias within these decisions.

Some of the fallacies come from (Kim & Ahan 1997):

1. Lack of time, knowledge and data.

2. Difficult to quantify attributes.

3. A single decision maker that has limited knowledge, expertise, information processing ability, and an uncertain environment.

4. Limited expertise among group decision makers.

Decision-makers may feel pressure to make a decision but do not have the proper information nor do they have the expertise to make these decisions. This creates a problem that causes quick decisions to be made without an accurate analysis. When poor decisions are made they can impact a running chain of events that are difficult to change. 

The authors found that by using an analytical hierarchy process-group decision making model (IAHP-GDM) they were able Analytical Hierarchy Process-group decision making (IAHP-GDM) can foster greater group decision making. Group decision making can lower bias in decisions and help determine alternatives. Decision making models can help analyze those choices for greater accuracy and results.

Wu, W. et. al. Improved AHP-Group Decision-Making for Investment Strategy Selection. Technology & Economic Development of Economy, 18 (2).

Kim, S. H.; Ahn, B. S. 1997. Group decision-making procedure considering preference strength under incomplete information, Computer & Operations Research 24: 1101–1112.

http://dx.doi.org/10.1016/S0305-0548(97)00037-3

Shen, C. (2009). A bayesian networks approach to modeling financial risks of E-Logistics investments, International Journal of Information Technology & Decision Making 8(4): 711–726.http://dx.doi.org/10.1142/S0219622009003594

Shyng, J. et. al. ( 2010). Using FSBT technique with rough set theory for personal

investment portfolio analysis, European Journal of Operational Research 201(2): 601–607.

http://dx.doi.org/10.1016/j.ejor.2009.03.031

Zavadskas, E., et. al. (2010). Risk assessment of construction projects, Journal of

Civil Engineering and Management 16(1): 33–46. http://dx.doi.org/10.3846/jcem.2010.03