The following is the sixth in a series of conversations about digital innovation and the intelligent technologies powering the intelligent enterprise, with Jeff Janiszewski and Ginger Shimp from SAP North America Marketing. In this blog, they discuss how skillfully managing complex data can deliver the intelligence necessary to empower your enterprise.
Jeff Janiszewski: So, let’s talk about “data intelligence.” In this case, we’re not using the term “intelligence” to mean sophistication ― like an “intelligent device;” we’re talking about insight. The term is analogous to “military intelligence.”
Ginger Shimp: Yeah, but hold up. When you start talking about government intelligence, people start getting a little paranoid.
JJ: Well, actually, I think people understand that sometimes their personal information is used in aggregate and that businesses are serious about protecting that information. However, I think they do get nervous when targeted information comes back at them. For example, this morning I typed the letters B-A-L into my search engine, and it immediately suggested the Baltimore Orioles website. My computer knows that I used to live in Baltimore and that I like baseball. I could have been typing in the word “balloon” or “balance,” but the computer correctly guessed I was looking for the score of last night’s game. That kind of thing can be a little disconcerting.
GS: Sure, but once again, you have to be able to separate fact from fiction. My brother, who lives a very quiet life, believes he can’t go near Washington, DC because the FBI is monitoring him ― he reads a lot of spy novels. Our “Searching for Salaí” podcast gets into the realm of paranoia, but hopefully, people understand that it’s just fiction.
JJ: More importantly, this has nothing to do with how data intelligence is used in a B2B context. For example, suppose a company is being acquired by another company. Obviously, there’s going to be overlap in production, staffing, real estate, and so on. Using data intelligence, a company can determine where there are redundancies or compliance issues. Then they can look at what physical locations need to be retained to best access raw materials, equipment, transportation, human capital, and whatnot. This sort of decision impacts all divisions and functions in a company and has so many variables that it would be beyond human ability to figure it out.
GS: Without question, great data intelligence requires best-in-class software, skilled data scientists, and robust data.
JJ: Once again, we see that truly transformative and sustainable innovation requires the integration of people, data, and technology.
GS: Managing data can be a challenge. Sometimes more data is flowing into an organization than can be processed. Structured data, which is quantifiable and can be arranged in a linear fashion, is relatively simple to deal with. Today, however, more and more unstructured data is being captured. Things like sound files, photographs, maps, or customer comments, defy obvious categorization and are much more difficult to organize.
JJ: Then you have to look at the quality of the data. You have to consider the accuracy. Did it come from a reliable source? Is any of the data missing? Do you need to find the missing data, or can you extrapolate to guess at the missing data? Is there superfluous data, or just plain meaningless data?
GS: And you don’t usually have static data. New data is coming in constantly, and some data will age out and need to be purged. Rules need to be made for the data. If there’s too little of something, more might be automatically added. If there is too much, something may be automatically eliminated.
JJ: Further, with good data intelligence software you can represent information in a meaningful way to spot trends, anomalies, or benchmarks in real time. Ultimately, that information might be sold externally or merged with partner data to make better decisions.
GS: For example, imagine a meteorological service that’s collecting tons of information from satellites and an enormous number of other IoT devices from around the world. The service processes that data into weather reports that are sold to others, such as shipping companies. Now imagine a shipping company that takes those weather reports and combines it with their own supply chain and logistics data. Then they can leverage that data for themselves or perhaps sell it to a wholesale company. Then maybe the wholesale company is connected to a retail company, and so on. If data is being received and implemented in real time, the entire ecosystem runs more efficiently.
JJ: The chain is only as strong as the weakest link. If divisions across a business are working in silos, each with separate data, they won’t be able to work together in real time. Data will have to be retrieved from one division, merged with data from another, and then sent on to the next. This can be even more critical if it causes delays with maintenance, sales, service, and it can even endanger partner relationships.
GS: He who hesitates is lost. Data intelligence in coordination with the other intelligent technologies can give businesses the confidence to make great decisions quickly.
To learn more about SAP Leonardo and data intelligence, visit https://sapinnovate.me/leonardo/.
For a more imaginative experience of how technology has become integrated into our lives, listen to our cool new podcast, Searching for Salaì.
Searching for Salaì is also available wherever you listen to podcasts:
Continue the experience at www.searchingforsalai.com.