Data, data and more data
Today the word “Data” is used in everyday jargon within businesses of all sizes. With the emergence of social media, applications over the internet and telecommunications, the world is generating unprecedented amounts of data. This is in addition to the ever increasing volume of internal data our organizations are generating. Everyone wants to get their hands on more data, with a feverish desire to enable better and better insights and answers to business questions.
Somehow, the notion that if we could just gain access to more data, we would find a silver bullet that would lead to the next breakthrough in solving business challenges. This notion is actually not a bad aspiration for businesses at all. In fact it is downright admirable to see organizations embrace the promise of the unlimited insights that can be gained from these new data resources we humans are generating.
We set a trap for ourselves by diving in head first, without planning on how to use this data. IT departments spend an inordinate amount of time evaluating the next best tool that emerges in the marketplace. It is a temptation that often cannot be resisted even though it would be more prudent to have a plan in place first, with goals aligned between technology and business customers.
Stop the data collection avalanche and ask questions
With so much data available, shouldn’t we step back for a second and ask ourselves:
- Is all this data really useful to me and my organization?
- Is the data timely and accurate?
- What do I need to do to get the answers that will best benefit our business decisions?
- Do I know if we have all the information available to paint the complete picture?
- Will the context be relevant when we present data to decision makers?
As you can see, the data collection paradigm can shift quickly when we stop and analyze our use of all the data that is available to us.
What is the downside?
In many instances, organizations that put a high priority on data collection before analyzing its potential use often end up with a data liability. A liability can be defined as an entity, event or a transaction that incurs a cost that is payable over a period of time. Data liabilities may be easy to spot in some cases, but are not so obvious in others. For instance, have you encountered any of the following “situations” before?
- When you want a question answered, it results in a treasure hunt by an army of analysts to find the data that you need.
- You have a genius programmer in your IT department who is the “go-to guy”. He writes very complex code to answer questions for you, and you fear that if he leaves, it would create a crippling void.
- Your IT resources are consumed with hardware issues and need to spend a great deal of time and money to keep the current infrastructure running.
- A crucial business decision is made based on unreliable data, which results in a loss of revenue and unnecessary time spent on corrective (and reactive) actions.
Make data your ally
If you know your organization has data liability issues, it is not the end of the world. With some planning, this liability can be turned into an asset. The definition of asset is an entity, event or a transaction that generates earnings, profit, revenue or opportunity.
Businesses should spend less time collecting data and more time analyzing data. This can be made easier if the context surrounding the data is clear. Having well documented and readily available metadata can avoid endless meetings to decipher the data or its accuracy. Business analysts should be just as proficient with the data tools as they are in ensuring the accuracy of the data they are analyzing.
Some basic principles to consider when turning your data into an asset are:
- Data is not an IT function – its ownership and reliability is the responsibility of the entire organization. Before acquiring additional data, evaluate if you are truly utilizing existing data assets.
- Ensure that the goals of the business and its IT partners are aligned at the highest levels of management. Common goals drive data requirements and solutions which are well-aligned, resulting in reliable data assets.
- Resist the temptation to play with every new tool in the market. Evaluate tools and technologies best suited to your business and culture.
- Build and re-evaluate a data roadmap, including elements like Reporting, Dashboard and Scorecard, Business Intelligence (BI), Analytics, Big Data etc. Lacking a plan up front could result in considerable inefficiencies for your IT resources as they react to the minutia of everyday data issues, rather than driving business value through the creation of data assets for your company.
- Strongly consider Master Data Management (MDM), Data Warehouse (DWH), Data Governance (DG) and Data Quality (DQ) initiatives.
Simply put, before taking on additional challenges, evaluate and leverage your existing data assets. In the next of our series on data, we will talk more about data governance and what that really means to an organization.
