In Part 1 of this blog series, we looked at how far analytics have come since the limited days of “siloed” data tools. However, any tool is useless without both a purpose and a skilled user. In this second installment, we will be examining 1) abundance, scarcity, and data accessibility in analytics, and 2) how analytics improves an organization’s ability to measure, understand, and make decisions based on data.
Abundance, Scarcity, and Data Accessibility
Currently, total global energy consumption is roughly 16 terawatts a year, and this is expected to rise to 20 terawatts by the year 2020. A large part of this demand is supplied by the burning of fossil fuels, leading to air quality declines and other environmental problems. While 16 terawatts may seem like a lot of energy, what if we told you that this amount of solar energy hits our planet’s surface every eighty-eight minutes or so? Once again, this seems like an abundance of energy. However, very little of that energy is currently being accessed. Due to this limited access, our world is experiencing an energy scarcity that leads to higher energy prices and fossil fuel dependency.
A similar situation can also exist when it comes to data analytics. The amount of digital data in our world currently doubles in size every two years. By the year 2011, there were as many bits of data in our world as there are stars in the universe. On the surface, that might seem like a staggeringly abundant amount of data. However, if this abundance is not met with efficient data access and analytical use, it will ultimately lead to scarcity. And the same is true with data as with solar energy, in that less than 0.5% of all the data created is ever analyzed or used to drive actions.
Again… the problem is not a lack of abundance, but a lack of accessibility.
Abundance in data analytics is fostered by:
High computing power
Opportunities for business value
One the other hand, scarcity occurs when an organization has:
Lack of analytics skills
Uncertainty in leadership
A reluctant culture that is not data-driven
Security/Privacy fears and/or poor practices
Measure. Understand. Decide.
When data is met with the science of analytics, scarcity is overcome by abundance. As a result, such organizations benefit from a dramatically improved ability to measure, understand, and decide:
Identify key performance indicators
Set goals/target values for performance
Carefully and persistently monitor actual values
Determine leading indicators
Forecast performance measure
Identify important attributes
Create custom groups
Blend disparate data sources
Drill into details
Build taxonomy and ontology
Identify creative choices
Achieve transparency in how decisions are made and who made them
Provision: simulation, optimization, experimental design, and driver-based planning
Extreme “devil’s advocacy,” allowing for better testing and evaluation of arguments/decisions
In Part 3 of this blog series, we will discuss the many resources and capabilities of data analytics.