final research paper grad 699
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grad699GreatExampleFinalPresentation-A.Navickas12.4.16.pptxBenefits, Barriers, and How to Overcome the Barriers of Using and Implementing Big Data Analytics throughout Supply Chain Management in the Medical Industry
Adelaide Navickas
Harrisburg University
12/04/2016
Presentation Agenda
Introduction
Research Question
Research Methodology
Literature Review
Results
Limitations of the Research, Future Work Planned, and Lessons Learned
Conclusion and References
Introduction
Big Data
Volume
Velocity
Variety
Big Data Analytics
Supply Chain
Procurement/sourcing
Logistics
Operations
Marketing
Author’s Background
Masters in Analytics
Working for Medical Device company in a Customer Care role
As previously mentioned Big Data has frequently been defined as data with high volume, velocity, and variety [5] [6] [7], while Wamba et al. goes on to add veracity and value as key components in the definition of Big Data [2].
BDA is the application of Business Analytics on Big Data. Business Analytics refers to statistical analysis, forecasting, predictive modeling, and optimization techniques
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Research Question
Specific
Benefits
Barriers
How to overcome these
Implementation and continued use
Leadership
Talent Management
Company Culture
Survey supply chain team members
Limitations
Not exhaustive
No suggestions for how to overcome unless provided by survey respondent
Research Methodology
Identified the target respondents.
Wrote the questions and interactive statements for the survey.
Survey was reviewed by two individuals.
Survey was revised based on feedback from previous step.
Three people re-reviewed the survey
Final changes to the survey based on feedback from previous step were made and the questions were uploaded the online survey site SoGoSurvey.
Survey was sent out to potential respondents over a month long period via individual emails.
Data from the survey was exported to an Excel file and analysis of the results was conducted in order to identify common trends among the answers as well as identifying anomalies.
Literature Review
Overview of existing Literature
With the ever-increasing amount of Big Data available to and collected by companies, BDA has emerged as a key tool for businesses looking to gain a competitive advantage, new insights, and added value (full reference provided in paper)
There are many BDA applications that can be applied to all parts of the supply chain. Waller and Fawcett suggest that business and supply chain leaders must understand and use BDA to support decision-making in SCM (full reference provided in paper)
In Sanders’ article, “How to Use Big Data to Drive Your Supply Chain,” the survey used indicated that the majority of executives believe that BDA is a priority for the future, but also admitted there were concerns about the cost and the choices available that would best suit their needs (full reference provided in paper)
Recent literature reviews broke down the current studies by varying categories:
Type of analytics used (predictive, prescriptive, or descriptive)
Types of value creation found by using BDA
Varying other criteria: focus, research approach, method triangulation, data generation, range, timeline, theoretical background, and target audience
Limitations of Existing Studies
BDA is still gaining momentum in the world of SCM. While there are plenty of businesses that are using it, there is very little research on the benefits and barriers associated with continued use of BDA due to its newness
S. F. Wamba et al. brings up the lack of research on how leadership, talent management, technology, culture, data privacy, and decision-making processes impact the use of BDA (full reference provided in paper)
Goal of this presentation is to bridge the gap between formal research and industry usage by providing supply chain executives with the necessary information to understand the benefits of and overcome the barriers to implementing and continuing use of BDA in SCM
Results
General Survey Statistics
Table 1 shows the breakdown of respondents’ industries within the medical field
Majority of responses are from hospitals
But there is a good mix of other industries as well
Breakdown of time using BDA in supply chain
44% of respondents using BDA have only been using it for one to three years
19% have been using BDA for four to six years
15% for seven to nine years
7% for ten to twelve years
8% have been using it for 13 or more years
Table 2 shows the majority of companies with over 1000+ employees are using BDA in their supply chain (20 of 24)
Due to low response rate from smaller companies the author makes no conclusion as to whether or not there is a trend for or against BDA usage in companies of that size
The majority of respondents, regardless of company size, are using BDA (27 of 32)
Table 3 shows the breakdown by component. Please note there is overlap as a company could be using BDA in 1-4 of the components
Marketing is the component of supply chain that uses BDA the least right now
Table 1
Table 2
Table 3
It was also shown through the survey that of the four respondents using BDA in marketing, three were using BDA in all other components as well suggesting that marketing is the last piece of the puzzle when implementing BDA in the supply chain
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Benefits
Of the 27 respondents who use BDA in their supply chain, 26 provided answers that equated to 59 individual benefits
Financial benefits were by far the most prevalent benefit (23 of 59)
Optimization and maximization was the next most frequent benefit (9 of 59)
Better tracking/reporting/insight (8 of 59)
Other common benefits include:
Identifying trends (5)
Better models (4)
Monitoring inventory levels (5).
Reducing excess (2)
Identifying fraud (2)
Increasing process efficiency (1)
Specific Examples
In regards to optimizing human resources, one respondent specifically discussed the use of a system that tracks an employee’s work progress through time, speed and logistical status by way of an RF scanner. Not only did it help improve employee efficiency, but it also allowed that company to pick better locations for items to increase picking efficiency.
“Patient demographic information has been analyzed to determine where our patients come from to assist in marketing. In addition, analyzing data that identifies if a patient was referred to our Health Care system from a smaller organization has allowed us to strategically form alliances with surrounding health care providers that serve as a feeder for patients requiring more complex care than what they can provide. As a result we have maintained steady/or increasing volumes of patients and we are often treating the more critically ill that bolsters our reputation as well as giving us the opportunity to increase revenues.”
The benefits identified by respondents were varied but did have common themes. Of the 27 respondents who use BDA in their supply chain, 26 provided answers that equated to 59 individual benefits.
Financial benefits were by far the most prevalent benefit. Such benefits were identified 23 separate times. These financial benefits included lowering the cost of devices or distribution, reducing costs through better negotiating and review of contracts, reducing labor costs through the balancing of human resources, and lowering freight bills.
Optimization and maximization was the next most frequent benefit listed encompassing nine of the 59 benefits. Examples include optimizing item location within a warehouse, optimizing inventory levels as well as human resources, maximizing sales through better service levels, and increasing patient volume with targeted marketing.
The third most frequent benefit was found to be better tracking/reporting/insight and was mentioned in eight of the 59 benefits. Examples include providing leadership with a big picture view of daily operations, providing information on clinical use of products which leads to standardization of product decisions, tracking compliance with contracts, and a better notification system to remind employees of what is coming next.
Other common benefits include identifying trends (5), better models (4), and monitoring inventory levels (5). Trends were mentioned to be found in customer behavior, expenses, operational, and financial categories. Models mentioned were used for a centralized supply chain (for multiple hospitals) and predictive analytics. One example described using models to predict usage spikes so that they could be proactive in their procurement as opposed to reactive. The last few benefits included reducing excess (2), identifying fraud (2), and increasing process efficiency (1).
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Barriers for companies not yet using BDA
5 respondents’ barriers:
A current model that is more granularly focused
A lack of data analysts
A lack of proper systems (mentioned by three of the five respondents)
Resources needed for implementation
High cost involved in system add-ons
No noted ways to overcome these barriers by these respondents
However, similar barriers were listed by the respondents who had implemented BDA along with ways to overcome those barriers
Barriers and How to Overcome Them
Barriers
Of the 27 respondents using BDA, 26 of them provided 52 individual barriers
The largest category was data integration (11 of 52)
Companies are working with data in inconsistent formats across multiple systems that may or may not initially pair successfully with each other
Data Accuracy (9) and Data Validation (8)
Shared between 12 respondents – 5 of which listed both barriers
Data accuracy barriers included not trusting the data source (customers, physicians, nurses), knowing data was manually entered (always a chance for human error), and not trusting the system it is being pulled from to provide consistent results
Data validation barriers included manual checks of the data to make sure results and reports were accurate, questioning the data rather than the analysis, and having to validate the source data used in the analytics
Remaining barriers:
Technology for data manipulation (4), technology for data storage (3), database reporting logic (3), calculation accuracy (3), data security (2)
10 other individual barriers
Methods to get past them (if provided)
4 of 11 respondents who faced data integration barriers overcame them
By developing a system to standardize data collection, enforcing policy and procedure, persistence, or creating an automated process making data more readily available
7 of 12 respondents who faced data validation and data accuracy barriers overcame them
By revising reporting tools, educating staff who uses the data about the value of the data and its accuracy, trial and error, continued use of the data allowing for regular adjustments that provide better information, or developing a system that allowed for more data to be collected at a greater depth so that it could be cross-validated across datasets
workforce resistance to their actions being tracked and measured, HIPAA (Health Insurance Portability and Accountability Act) limitations, lack of human resources, building an effective business case to show leadership the benefits of implementing BDA, pushback from suppliers on pricing benchmarks, internal stakeholder pushback, data volume, steep learning curve, end-user pushback, and the ability to drill down into the data
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Leadership, Talent Management, & Company Culture
50% of responses mentioned leadership
A quarter of these had a lack of leadership support
The remaining three-quarters noted that they had strong leadership buy-in and support which continues to help their team provide benefits to their company
40% discussed the need for strong human resources with analytical skills (talent management)
It was noted that it is important to hire people with BDA experience and for the focus of their role to be solely on BDA
More than 2/3 already had a strong analytics team while the other 1/3 is searching for better human resources
40% also wrote about how company culture played a role in their BDA usage
3 of 9 truly felt that their company culture helped support BDA usage in their supply chain
2 of 9 don’t have a strong positive or negative connotation
4 of 9 felt culture was hindering their BDA usage and found it particularly difficult trying to work together with other departments
24 of the 27 respondents using BDA answered this question.
This was the last question of the survey and may not have been worded very clearly because 6 of the 24 who answered did not directly mention leadership, talent management, or company culture in their response.
Limitations of the Results, Future Work Planned, Lessons Learned
Future Work Planned:
More research specifically on how talent management, leadership, and company culture affect BDA use in SCM in the medical industry
Lessons Learned:
Don’t rely on one person or company to distribute a survey – take responsibility yourself
More respondents were using BDA than initial assumption (this is good in the author’s humble opinion)
Many respondents had barriers that they had solved, but there were also others that hadn’t solved theirs yet – it was nice to see that they were still persevering and not just giving up
Limitations of Results:
Results are specific to the 32 respondents
While there were a variety of regions and industries presented the small sample size makes it hard to say that the results would be consistent with a larger group
Thank you!
References and appendices are provided in the paper with the same title as this presentation
