We follow a lot of analysts, consultants, and vendors on topics related to data analysis and big data. Many discussions today focus on the shortage of data scientists, without whom, it seems, data analysis cannot be accomplished. There has also been a lot of talk about the lack of applications.
This lack of applications is where things are interesting. The subtle message seems to be that applications are lacking because of the lack of data scientists. However, when we speak with our customers, they know the questions they want answered. In most cases, they have ways they have been cobbling together answers to their questions. For operational issues, these answers are often based on samples of data and tend to come as a result of multiple reports and/or spreadsheets. The challenge for business managers is that these methods of data analysis take time. And the manual elements of correlating results from different reports and tests are subject to some variability depending on the people involved and how much time they have to devote to any particular analysis. And when they have to rely on sampling and extrapolation results degrade.
Big data analysis discussions focus on the kinds of strategic issues that make for good television commercials during major sporting events. How can we use analytics to detect changes to the energy requirements of a large population in order to re-route electricity on the grid? How can we know which past customers of one product are the most likely customers of a new product? Which new markets are the most potentially lucrative? These are great potential solutions and there is even some work that has occurred in these areas. The ones with which I am familiar are all nine figure projects that include top systems integration firms. Unfortunately, that doesn’t work for business managers with daily operational objectives to achieve.
One person in the data analysis world leading the charge on applications and asking the right questions is Ray Wang at Constellation Research. Earlier this summer Ray wrote in his blog three things that demonstrated to me that he is speaking with the same companies. Ray said that business leaders should focus the discussion back to business value. Specifically, the big question is what is the question? Ray has it right when he says that every project needs to start with the following questions:
- What are the questions that need to be asked?
- What are the answers that help us move from data to decisions?
- Can we shift insight into action?
- How do we tie information to business process?
- Who needs what information at what right time?
- How often should this information be updated, delivered, and shared?
Ray goes on to say, “Real-time is irrelevant because speed does not trump fidelity. Quantity does not trump quality. Context is key as we need to shift from real-time to right time data based on roles, processes, location, time, and relationships.”
Based on our experiences speaking with customers and prospects over the past eight months, we’re speaking with the same people as Ray. They’re telling us they know the questions to ask. They’ve shared with us that they know which answers can help them make decisions and take action. And they know exactly how often this information needs to be updated, delivered, and shared. Interestingly to me, the timing isn’t as frequent as I thought.
We’ve designed our new Insights On Demand based on the six questions that Ray says every project should ask at the start. We agree with Ray because our customers agree. And the more that data analysis solutions start with the questions that lead to answers that lead to decisions that lead to action, the more successful everyone will be.