global data, big data, data analysis

In the last year how often did your organization come to a decision point where you wished you had quality data to support what you suspected to be true? If not very often, then you did a great job keeping good data about your business…or you were just not asking the right questions about your business. Either way, the value of having consistent and reliable data that is easy to access is as undeniable a fact as “1 + 1 = 2.” We realize “data” can take a broad (and sometimes vague) meaning so we restrict our focus to master and transactional data, which are the two types of data most prevalent in the running of a business.

You might be thinking, “My business organization runs just fine with the data it has.” That may be true; however, consider for a moment the pain points of dealing with unhealthy data on a consistent basis. Three of the more obvious signs of unhealthy data include the following:


To support any initiative or business decision you will find yourself asking “Where can I get the data?”  Here is where data inconsistency often rears its ugly head.  If your business has inconsistent data, you will get different results depending on (1) who you ask about the source of the data, (2) the time you’re pulling the data, and (3) the source of the data pull.  Intra-data source consistency is just as important as inter-data source consistency.  From these experiences arose the “single source of the truth” mantra.


While it may be easy to identify the source of your data, can you actually touch the data and sample it whenever you need it? It is of no benefit to your business to have good clean data if it is locked up in a vault with no means of access or if you have to jump through hoops and loops to get to it.  Master and transactional data should be easily accessible to a wide base of users who can gain value out of it.


Imagine you’ve found the right source of data and you have access to it. There is often a moment of truth when you start analyzing and reviewing the data and you find that what’s supposed to be there isn’t there.  Master and transactional data sets with large chunks missing are almost as worthless as no data at all.

Why Bother?

We hope that it is somewhat apparent business initiatives or decision-making can easily be taken hostage by unhealthy data. To hammer the point home consider the following three tactical and strategic initiatives that can be encumbered by data issues: LEAN/Sigma, Predictive Analytics, and Advanced Analytics. Nothing can more easily deflate any one of these high-floating initiatives than data health issues.

LEAN Initiatives / Six Sigma projects

How does one define and measure in DMAIC without the requisite data? When it comes to identifying root causes of business problems, you simply cannot guesstimate your way to the end. Limiting the amount of time spent on searching for the right data, or needing to create processes or systems to gather the data.  Healthy data is paramount and without it a Six Sigma project is dead in the water.

Control Tower / Monitoring

The vision of business leaders when implementing control towers is always to create visibility into the health of the business through near real-time reporting of metrics, KPIs, KPPs, etc. The idea here is not to have one single source of data, but rather to have one single source of information and insights. This vision often gets blindsided by data health issues.

Advanced Analytics

By advanced analytics, we mean heavy-duty efforts such as predictive analytics, supply chain simulation (what-ifs), supply chain optimization (what’s best cost-wise, service-wise, etc), and other mathematical and statistical modeling (demand forecasting, etc.). The volume and quality of data required to embark on these efforts are not trivial, their importance to business success is even less so.

You get what you paid for

For the price of admission to the world of healthy data maintenance, your business will get to enjoy all of the following luxurious amenities:

  • Data-driven insights that are easier to come by
  • Greater confidence in business decisions that are backed by data
  • Shorter turn-around time for all variety of data-driven projects: Six Sigma, Control Towers, and Advanced Analytics (predictive analytics, supply chain optimization and simulation)

Written by Desmond Torkornoo and Tim Kachur