Chasing After Big Data Has Its Challenges
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Chasing After Big Data Has Its Challenges

Daniel Erickson, Director of Product Strategy, ProcessPro
Daniel Erickson, Director of Product Strategy, ProcessPro

Daniel Erickson, Director of Product Strategy, ProcessPro

Is use of Big Data on your mind? Are you feeling the pressure to attempt to utilize it? Data certainly can be the fuel and foundation of your company’s future gains and access to data has reached unprecedented proportions. In fact, if you’re not storing, mining, analyzing, and using data generated during your day-to-day operation, you are probably missing opportunities. An Enterprise Resource Planning (ERP) software solution––with its integrated business intelligence (BI), analytics, and reporting functionalities––would help to manage your own valuable data. However, when it comes to using Big Data––copious amounts of data taken from a multitude of disparate sources––the decision to use or not to use presents you with a bit of a conundrum; Big Data’s power to inform is intoxicating and you’d like to take advantage of the value it presents, but there are significant challenges involved in its use. Is chasing after Big Data for you?

According to McKinsey & Company’s 2011 report, “Big data: The next frontier for innovation, competition, and productivity,” manufacturing has historically been a productivity leader, and now the U.S. is entering a new era where Big Data can help to extend gains.1.However, McKinsey economists also believe U.S. businesses aren’t utilizing their data well, and that “many are grappling with how to process an overwhelming volume of data from numerous sources quickly and accurately.” Some companies are considering data management initiatives in order to handle and manage Big Data.

We believe there are three questions you should ask when making a decision about whether or not to pursue a big data initiative:

1. What sources and types of Big Data are relevant to your company?

2. How do we ensure the quality and validity of the data?

3. How can we make this data useful and meaningful to our company?

For example, a spray paint manufacturer might notice a spike in interest in metallic paint, locally, but notice a national trend toward the purchase of chalk paint. Why is this happening, and how is this information meaningful? Big Data may help uncover the underlying reasons for the national and local trends. As in this example, there should be a value attached to the acquisition and consumption of particular data.

If you’re currently managing your business or manufacturing operations with manual procedures, legacy software, or disparate systems, a first step toward better utilization of your data would be to invest in an ERP software solution to centralize and manage your business data. If you’re currently using an ERP solution, you may already understand that an ERP system with business intelligence helps translate your raw data in ways that benefit your company. Your ERP solution may also utilize some Big Data outputs. Yet, your ERP solution is not designed to handle the volume and complexity of storing, mining, analyzing, and using Big Data. Big Data and the proper analytical tools can complement an ERP software solution and broaden your visibility to the factors influencing your business.

When considering the use of Big Data, it’s also important to develop a Data Plan before you invest human and monetary resources. A data plan will help all involved in the project understand their roles, prioritize objectives, identify stakeholders and decision-makers, articulate the implications of data reorganization, develop analytic models, use of data tools, outline ways to assemble and integrate data, and determine how often the data gets refreshed (daily, weekly, monthly, yearly). It’s important to consider who in your company will lead the effort. Perhaps it will be a data scientist, controller, director of information technology, or a technician with interest and experience in data-mining, analytics, and/or business intelligence. There are costs to be considered, such as: personnel involved (whether internal or external), project hours for all involved, a potential loss of efficiency to your operation as resources are tapped for the initiative, the possible utilization of an outside expert, and the investment in an analytics and reporting tool. These costs are often a driving concern for companies and deters many from investing in Big Data. Accessing your ROI before engaging in the Data Plan will give credence to the project.

Reporting and analytical tools, such as business intelligence software, helps with data mining to detect relevant patterns in a database, using various approaches and algorithms to analyze and predict future trends, based upon current and historical data. This data can include: structured data from your ERP system or unstructured data such as social media information (including Google, Facebook, and Amazon), industry trends, political and global politics, agricultural and weather trends, and more.There is an explosion of business intelligence tools, data scientist consultants, and firms offering their services in the marketplace, and it’s easy to become confused and overwhelmed. How do they compare with regard to strengths, range of functionalities, and cost? Cost is certainly an important factor as well as whether or not your business intelligence tool of choice integrates well with other data tools and sources. Purchasing and implementing a new business intelligence tool may not be the best choice for you at this time. Instead you may opt to engage a third-party for performing Big Data analytics. Then, the question becomes what sources you will be leveraging for data.

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