5 More Reasons Why More Data Doesn’t Guarantee Better Decisions

In my last blog, I discussed 5 reasons why more data doesn’t guarantee better decisions. I had picked what I considered my top five from a long list of reasons.

I must have hit a nerve with our readers because the response has been tremendous. So today I’ve incorporated some of that feedback into this list of five more reasons why, with all this data, better decisions aren’t guaranteed.

1. When It Comes to Data, Quality Comes Before Quantity

We seem to take quality for granted. As we continue to evolve as a society with rapid and infinite points of social data consumption, we seem to focus more on quantity. We may argue that a similar trend or mindset may be diluent in the business world where we assume quantity can make up for quality.

It’s true that as quantity increases we can achieve greater depth and perspective. But by the same token, data for the sake of data doesn’t help us either. Data quality (a field on its own) is fundamental for driving consistency and relevancy when it comes to making better-informed decisions.

2. If It Can’t Be Trusted, People Won’t Use It

Untrustworthy data is a frustration that’s prevalent in small, mid-size, and Fortune 500 businesses. The issues that arise from a lack of trust in data are not just limited to leadership roles but affect everyone in the enterprise regardless of their roles or position. The lack of trust breeds a lack of the conformity and standards that are required for robust data-driven decision engines that people can trust and use.

The journey to promoting a culture of data-driven decision makers must start with making data quality a top priority for key data assets and decision engines. Above all, it demands a mindset to see data as a strategic asset. When the data quality is consistently excellent, then it becomes trustworthy.

3. If It’s Not Timely, It’s Too Late

It doesn’t do much good to have all the data we need if it’s not timely. Businesses can no longer afford to wait for traditional transformation cycles that churn data for hours or days. New technologies such as cloud, mobile, and in-memory are fueling this paradigm of demanding more data points faster.

Here is the reality:

  • To compete effectively, you need to get there faster than your competition.
  • To efficiently mitigate risk, you need to proactively eliminate it before it becomes a liability.
  • To grow faster, you need to identify opportunities before they are ripe.
  • To drive profitability, you need to constantly shift and reallocate resources to manage at optimal levels

4. More Data in the Wrong Places May Be Dark or Dusty Data

Dark data (or dusty data) continues to pose a challenge for organizations tapping vast amounts of invaluable deposits in enterprise data vaults. In its simplest form, dark data refers to data that remains unexploited for business value.

Left disintegrated and without the necessary transformations to be turned into cohesive and compatible building blocks to deliver insight, they are often neglected—sometimes not on purpose. Additionally, data extracted from transactional repositories doesn’t automatically generate value unless it’s made available at different points of consumption. Staged but undelivered data is like a meticulously cooked meal sitting in the kitchen and not being delivered to customers in the dining room of a restaurant.

5. More Insight Available but No One Knows It Exists

In real estate, they say, “Location, location, location.” When it comes to data, I often maintain, “Communication, communication, communication.” This means that we need to effectively inform and educate our user community about our data portfolio.

Because if they don’t know, how can they consume? The more we educate our users about what exists and how they can access it, the more likely they are to adopt the existing solutions. We also must successfully articulate the business value proposition. Otherwise, integration of business and technology is a zero-sum gain.

Bottom Line

Each of the ten reasons I’ve covered proves one key point—more data should be guarded with a healthy dose of skepticism.

Strong leadership and critical thinking are key because we need to carefully examine the evidence based on what’s relevant to the question at stake before reaching any conclusion or making any decisions. Only then can we realize the promise of more data—to deliver actionable insight for faster and better-informed decisions.

Connect with me on Twitter @KaanTurnali, LinkedIn and here on the IT Peer Network.

This story originally appeared on turnali.com.

Published on Categories Business LeadershipTags , ,
Kaan Turnali

About Kaan Turnali

Kaan Turnali is the Global Sr. Director Analytics, SAP; recognized industry expert; and contributing author. -- I am passionate about smart integration of technology. Specializing in executive mobile analytics, I help the C-suite drive growth and profitability with business intelligence (BI) solutions. By leading small and agile teams, I create opportunities for innovation with customer-centric solutions built on the principles of design thinking. And thought leadership empowers me to reach larger audiences through storytelling, inspiring conversations that would have been otherwise lost or never started. Connect with me on Twitter (@KaanTurnali), LinkedIn, and at turnali.com.