The advent of IoT and Big Data has given us access to information that we have never have access to before. Once we have access to the data, making use of it requires more than just the click of a button. We need the ability to formulate and ask the right questions, expertise in many areas or the willingness to seek out that expertise, and people with technical skills who may be outside the IT organization.
Asking the right questions
In an online article, Malte Ebach, a Senior Lecturer in biogeography at UNSW Australia, stated that the amount of data is not as critical as the question you ask of the data. Asking the wrong question may lead to unmet goals and inaccurate predictions. According to Ebach, this is what happened when Google Flu Trends asked, “’when will the next flu epidemic hit North America?”” He went on to say that a different question—“‘what do the frequency and number of search terms tell us’” about flu trends—may have led to greater findings. With this in mind, organizations need to find people that can formulate and ask the right questions at the right time.
Engaging the right expertise
Once we have a question, we may need an algorithm to help us answer it. Algorithms take a set of rules or factors into account to answer questions, make recommendations, and carry out actions. One article provided an example of an algorithm that aided in shipping decision-making. It took factors such as weather conditions and customer delivery time flexibility into account to suggest a driver. Similarly, there are algorithms for determining shipping routes and optimizing how trucks are loaded to ease delivery. But as the article states, the right model is needed to have the right algorithm; and certain expertise is required to create that model. Based on the situation, you may need expertise in multiple areas—logistics, mathematics, chemical engineering, economics, and etc. If employees don’t have the right expertise, they should be willing to engage that expertise.
Employing the right technical knowledge
Developing a question and algorithm only get you to a certain point. Next, organizations need to technically implement the method that will answer the question. With this in mind, employees need to do more than use technology; many roles now and in the future will require them to create it, even outside of the IT organization. The growing data science career area is a great example of this. Business units outside of IT may employ data scientists to help them answer their pressing questions, even though data science can be quite technical (including programming in languages like R and Python).
As we move forward, we will absolutely have access to more opportunities to utilize big data coming from multiple sources including IoT. However, in getting there, it is important to ask the right question, with the right model, created by the right experts in conjunction with the right technical implementation.