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Making Efficient, Data-driven Decisions

Team Name: The EXPO

11/03/2019

MGT-360AE

Introduction

The life of a leader involves countless decision making regardless of if the decisions are simple, complex, or strategic, and sometimes these decisions are vitally important as they may cause an irreversible situation. Some decision making can be well-planned while some have contingencies, so when making a decision, a leader should consider different factors, for instance, time limit, effectiveness, and efficiency. Moreover, when the society reached the Big Data era, many decisions have been made based on actual data analysis. A data-driven decision is a whole process of collecting data, analyzing data, extracting facts from data, and giving a conclusion, so the whole process takes a period of time(Kelsey Miller). By utilizing data, results are logical as compared to guessing or observation, so data-driven decisions are effective. However, a leader could face many different situations, and some cases may be time-sensitive. Therefore, when facing an urgent circumstance, a leader should not only make an effective decision but also it should be timely and efficient. There are different ways for a leader to balance effectiveness and efficiency when making data-driven decisions.

Analysis of Challenge

There are many challenges that affect the data-driven decision making process. One of the challenges faced when trying to make more efficient data driven decisions is that there is too much information that needs to be processed. There is so much data that needs to be analyzed that it is very hard to keep up with it and not get overwhelmed or lost in it. There is lots of new information that needs to be processed everyday, but with one person doing the job it is hard for them to keep up with all the work which slows down the process of getting everything done on time. If one is parsing through the data but spending too much time analyzing the wrong variables (due to a lack of direction), then they will be behind on their deadlines and still come to inconclusive results(Martin, R. L.; Golsby-smith, T.).

Another challenge with data decision making is siloed data. The data that is being analyzed is being done by individuals who are working separately in doing their part of the job(How to Make Data-Driven Decisions Fast (Yes, It's Possible)). There is no communication between the people on what each of them is working on. They are not sharing the information with each other, which is making them take longer to work on something that could be done faster with collaboration.(Martin, R. L.; Golsby-smith, T.) Working individually is also leading to biased data because one person is interpreting the data in one way while another might be interpreting the same data in a different way. The biased data is slowing down the process of making a decision because there is the extra step of comparing data to find what are the things in common that different people have found.

The last challenge is that companies do not have either the right technology or the right people working on the job. A lot of companies are not using the right technology to process the data that they have because they do not know what they should use or some just have an outdated version of their technology (Us, A., Style, L., & Us, C).. There are companies who are still doing things the old fashioned way, and that is not helping them get the job done faster. Another part of it is that they do not have the right people doing the job. Some of the people who are processing the data do not know a lot about what they are doing or supposed to do so that is a problem. If the person does not know how to do their job then that will reduce productivity. The other problem is that some of them are just not being trained to do the job correctly. There are many more challenges to this problem of decision making, but those are the main ones that are causing the problems.

Potential Solutions and Obstacles

When it comes to the challenges of siloed data, one would need to try to influence the company to create a culture of information sharing between people and departments. In order for the business decisions to be data driven, the team would more efficiently come to better solutions by sharing insights within the company.(Proof That Positive Work Cultures Are More Productive). Some obstacles that may arise in opposition to a sharing company culture are that an employee may feel that they are not receiving their due recognition for their hard work if they share their information with their peers. Specifically, if someone is trying to apply for a raise or promotion, they may want to have all the credit for any insights to themselves. A way to combat this obstacle is by making one of the criteria in the employee performance reviews reflect the teamwork and collaboration that the employee participated in. When the employee realizes that it is encouraged and rewarded to work with their peers, they will be more likely to share their information. The shared information would allow the data driven decision process to be both more efficient and more accurate.

Another potential solution in response to the challenge of having a lack of skills in using current company technology is to invest in trainings for the employees.(Us, A., Style, L., & Us, C). The difference between having basic analytical skills and advanced analytical skills in certain tools such as excel, is exponential productivity. A training program would teach folks the proper way to quickly summarize and analyze data using business tools so that they can be more efficient.

An obstacle that could arise to this solution is that the company does not want to spend company time to train the employees because it takes their focus away from their existing projects and deadlines. In order to get around this hesitation, one would need to explain to the executives that the training courses would be an investment in the company. Although it would have an upfront cost for the training, it would create a lot of efficiency in the long run as well as potentially allow for more insights from the data. This would allow one to make faster and more informed conclusions that would impact more timely and effective decision making.

The last potential solution that would fix the challenge of time constraints would be to collaborate with folks on other teams and in other departments.(How to Make Data-Driven Decisions Fast (Yes, It's Possible)).. If at the beginning of a project, one would have a meeting with representation of all the stakeholders, then every voice would offer a different perspective and a mutually beneficial decision would be reached much faster. After having the meeting where a clear goal is set, it would be a much more efficient process of analyzing large amounts of data because there is a specific objective in mind. Having the meeting would also be useful because it would bring into consideration soft data, such as industry predictions or evaluations. Having this scope in mind would allow the decision to take into consideration the external environment which creates a clearer direction and thus faster decisions making.

Conclusion

Overall, we believe that the best solution to reduce the challenges of a leader is to minimize/eliminate siloed data. This will reduce the companies chances of losing potential opportunities for growth as well as strengthen the communication throughout various departments. This is a similar concept to needing more data for a better understanding of the big picture (Lohr), the more information departments have the better decisions they can make moving forward. Furthermore, it will put an end to departments ability to blame another department for simply ‘not knowing’ when an issue arises. When a company communicates, flaws can be fixed expeditiously while increasing the customers’ lifetime value. This solution is also easy to implement and will require little to no spending. Leaders will simply make sharing data apart of the company culture and continue to express the necessity of doing so, as well as following up with employees on how they are collaborating with others during their time of performance reviews. By doing this employees will realize the importance of abolishing siloed data which will allow them to create effective and efficient data driven decisions.

Citation (APA)

Chamorro-Premuzic, T. (2018, October 10). 3 Ways to Build a Data-Driven Team. Retrieved from https://hbr.org/2018/10/3-ways-to-build-a-data-driven-team .

How to Make Data-Driven Decisions Fast (Yes, It's Possible). (2018). Heap. Retrieved 11 November 2019, from https://heap.io/blog/analysis/fast-data-driven-decisions

Lohr, S. (2011, April 23). When There's No Such Thing as Too Much Information. Retrieved from https://www.nytimes.com/2011/04/24/business/24unboxed.html .

Martin, R. L., & Golsby-Smith, T. (2017). Management is much more than a science: the limits of data-driven decision making. Harvard Business Review, (5), 128. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=edsgao&AN=edsgcl.504349258&site=eds-live

Miller, K. (2019, August 22). Data-Driven Decision Making: A Primer for Beginners. Retrieved from https://www.northeastern.edu/graduate/blog/data-driven-decision-making/ .

Proof That Positive Work Cultures Are More Productive. (2015). Harvard Business Review. Retrieved 12 November 2019, from https://hbr.org/2015/12/proof-that-positive-work-cultures-are-more-productive

Us, A., Style, L., & Us, C. (2018). 5 Ways Technology Can Improve Your Business. Localmarketlaunch.com. Retrieved 12 November 2019, from https://www.localmarketlaunch.com/business/5-ways-technology-can-improve-your-business/