Data. It’s overrated. It’s underrated. It’s unique. It’s important. It’s many, many things depending on who is speaking about it.
Every organization that I have worked for or have consulted with has been obsessed with using data, whether it be to power Watson, hire a chief data office firm, build a data ecosystem, implement Hadoop/Cassandra/HBase/SAP Hana, build a data warehouse, CMDB, collect customer data, analyze market data, and now capture social media data. It’s evident that the industry loves data and is desperate to do something with it. Is the answer to invest millions of dollars implementing big data and data science technologies? After all, the potential use case is massive especially when we are trying to move from a “product-centric” world to a “customer-centric” organization. However, it is still so hard to get to a point where we have actionable data.
So what exactly is actionable data? How can you tell which data is useful and which is not? Data science concepts help. What we fail to recognize is that data touches every part of the organization, which is a seismic shift in the way we think. We need to start thinking about the end goal of the data collected. Why is it relevant? What are you going to use it for? Is it transactional data? How do you take these datasets and make it all manageable?
I recently read an article that said “75 percent of business leaders from companies of all sizes, locations, and sectors feel they’re ‘making the most of their information assets,’ in reality, only 4 percent are set up for success. Overall, 43 percent of companies surveyed ‘obtain little tangible benefit from their information,’ while 23 percent ‘derive no benefit whatsoever.'” The study ultimately concluded that an astounding 55 percent of big data projects are never completed. How scary is that?
Based on the numbers the study shared, the trend is that gathering and then meaningfully utilizing data is difficult. How do we make better decisions and become more innovative from using data? We tend to look at data as a way to validate our point of view. So if our point of view is clouded or skewed, the data is useless. Something else to consider is some organizations’ obsession with collecting information to reach conclusions already known. Data that helps us to become more innovative is worth the time and effort.
We, as an industry, have so much data that we are drowning in it but ultimately does it matter? If we process the data then perhaps we can find information to influence decisions. If we can’t transform it and it cannot affect our choices, it just is not important.
Stop and reflect on that for a moment – you are essentially trying to take a massive amount of structured and unstructured data to reveal insights to drive strategy for a competitive advantage. Do you have people in our organizations who can switch off their current way of thinking to help understand the big data platform? I don’t know.
Something I feel that we are missing is the connection between data and strategy. What is your data source? How is this data relevant to each of your departments? How are you going to use this data to be competitive? In a rush to just collect data, any data, many companies fail to step back and think about their data strategy. The question we tend to forget is what exactly are we trying to solve? If your organization can’t answer that, then the organization shouldn’t commit the resources necessary to jump into a big data project.
What have been your experiences with big data projects? Do you feel that the organization had a well-developed data strategy? Did your organization identify and take advantage of actionable data? Or were you among the majority where your data project just went nowhere? Let me know in the comments below.
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