The first article in this series taught us about Big Data, what it is, how it supports analyses, and how it can be helpful when we have to visually depict large volumes of data. In the second article, we addressed nine actual situations from industry of how big data has been used in troubleshooting, maintenance and operations applications.
By Deborah Grubbe
In this, the third and last article of the series, we will address what the total team needs to do to assure themselves of good outcomes with big data analytics. The short answer is that leadership is still needed from everyone; however, the circumstances are more nuanced than one may expect. Big Data cannot improve your financials and operational excellence if you move forward without caution.
Implementing new technologies require a special breed of manager. Some may call it courage to change the status quo while the average supervisor retreats behind the safety of “that is what we always have done before.” However, just stepping forward in an attempt to change the status quo can turn into a serious incident if the managers involved do not carefully consider their implementation path.
In any new technology implementation, it is important to always move forward deliberately with the end in mind. The remainder of this article will examine a few of the leadership “potholes” in a big data implementation from the perspectives of the executive team and the management. Unfortunately, too many assumptions may be made that could cost any organization serious money.
Let’s address five of the many potential leadership opportunities around the technology and your organization and its management: 1) Unintended Consequences, 2) Personnel Changes, 3) Favored Outcome, 4) Technology as a Tool and Not a Crutch and 5) Bench Strength.
One aspect where big data implementations goes wrong is in the correct selection of technology and how the new technology is put into place. Unfortunately, firms will make an investment in a technology with one solution in mind and not be aware of the potential unintended consequences of other aspects of the implementation.
For example, one facility in the author’s experience implemented a more complex control scheme and the implementation was going poorly. The management could not understand why the teams were so slow in grasping the concepts and achieving the promised results. Upon investigation, it was discovered that many of the operations personnel could not read above the 6th grade level, and had trouble interpreting the written instructions. If the management better understood their workforce, they may have decided upon a path that involved more verbal instruction, followed by off line practice and demonstrated proficiency prior to any live implementation. The management team, by not asking appropriate questions or by making poor assumptions, actually had to spend more money than planned and the business cadence was upset for a number of months.
In another big data implementation, there was a key personnel change in the middle of the project. Unfortunately, the implementation lost its champion and it failed. In a post mortem, it was learned that not enough time had been spent building internal understanding with the facility management, and they had little to no understanding of what the technology was doing for them. Sadly, key personnel changes in the middle of IT, Big Data or any type of capital implementation often times causes the project to falter or to “wobble.” The leadership opportunity is to ensure there is a consistent and strong personnel change plan.
Here are some questions to ask yourself and your team:
- How well do you understand your technology needs?
- What decision criteria are you using?
- Are there new criteria for this new technology purchase vs. previous similar buys?
- How do you know, when you are either recommending or purchasing a technology, that you are purchasing the right solution for your need?
- Are you familiar with the full range of technical options and solutions available for the need?
- How much time has been spent investigating those alternative options?
- Are the decision-making criteria balanced, or is someone trying to direct the purchase to a specific vendor or software?
Another issue can occur when there is a “alliance vendor” that has developed a broad solution set that a firm will subscribe to over decades of operation. The vendors generally deliver value for their clients, and a level of mutual collaboration often develops between the vendor and its clients via extended “user group” activities and meetings.
Sometimes the management will not consider a vendor who is not on the corporate approved list. Additionally, a vendor may not be considered where there is no prior experience. What could be lost if the new firm, sometimes a startup, does not have the “track record” to make the sale?
There are too many variabilities on this scenario to outline here in this column; however, the bottom line is quite simple. If you need the technology, you work proactively to find a way to make it work for you. One potential solution is to test the new technology and the new company at one facility to see how the technology and the vendor performs. In one big data implementation, this very scenario led to a satisfied client and a strong business relationship with a brand-new vendor.
Another potential solution is to set up a collaborative relationship between the alliance vendor, the new technology vendor and the owner firm. Additionally, sometimes the firm who owns the operation may purchase the technology, an extended license or work on joint development, depending on the circumstances. There are many options, and the firm’s leadership has to choose the path that works best for their particular situation.
Technology as a Tool and Not a Crutch
Some managers think that technology can be the answer to any problem, and many times that is a correct thought process. However, in some circumstances, a technical implementation can become a recipe for other additional problems.
For example, at one location, a big data implementation was viewed as a key step in the overall plan to reduce fixed costs by eliminating engineering positions. Once the plan became known, one could easily see what was going to happen – and the result was not going to be positive for anyone.
First, the technology would never get a positive report because no one wanted to see their colleagues walk out the gate.
Second, the engineers who were going to be working at the facility would not be able to learn about a new big data technology.
Lastly, the relationship between the managers and the engineering staff broke down. Everyone lost.
That facts are that big data technologies DO change how people do their jobs. Big data technologies do change how work is done. Managerial and operational roles also change in this process, and all of this needs to be considered as executives consider installing big data technologies. One particular change is that there is greater transparency around the data, and that transparency can be an advantage to an organization that operates with “all info on the table.”
However, if there are individuals who operate with hidden agendas, a big data technology can threaten these individuals.
In retrospect, the management would have been better served if they had guaranteed new and upgraded jobs to the individuals who helped them implement the new technology and found other positions for those who were unwilling or unable to make the shift.
In another big data implementation, one visionary manager understood the importance of the technology and wanted it to be implemented on his site. Unfortunately, his bench of technical expertise at his site was very thin, and the folks who were currently capable of implementing the big data project were already overloaded and not able to give the new technology the needed time or expertise. The manager decided to push forward on the implementation in spite of his resource issues, and the big data technology went nowhere because the younger and newer engineers did not have the experience to implement it and the more experienced engineers did not have the time. Lacking a technical champion, the effort floundered.
Technology does not solve all problems, and sometimes new technology creates new problems. In this article, we have examined five reasons why new technology implementations fail. Woven between these five examples is one primary cause — the failure of leadership.
The lesson is clear. If you are a manager, an engineer or an operator, and you are facing a big data implementation, ask a lot of questions about what you think may happen. Your leadership, no matter what your role, will be critical to a successful outcome. Be aggressive in obtaining the right information and be sure you have the right questions. Above all, do not be afraid of the answers, as good leaders always seek truth.
If you would like to read or refer to Parts 1 and 2 of this series, go to www.cpecn.com and use the search term, “OPSS.”
Deborah Grubbe, PE, CEng. is owner and president of Operations and Safety Solutions (OPSS), a global consultancy that works with various industries. Grubbe is a former member of the NASA Aerospace Safety Advisory Panel and worked on the U. S. Chemical Weapons Stockpile Demilitarization. She serves on numerous advisory boards and is an Emeritus Member of the Center for Chemical Process Safety.