Tag Archives: business value

Fire your Data Scientists – They Don’t Add Value

Data ScientistYears ago, I was on a project to improve production and product quality through data analysis. During the project, I heard one man say: 

“If I had my way, I’d fire the statisticians – all of them – they don’t add value”. 

Surely not? Why would you fire the very people who were employed to make sense of the vast volumes of manufacturing data and guide future production?  But he was right. The problem was at that time data management was so poor that data was simply not available for the statisticians to analyze.

So, perhaps this title should be re-written to be: 

Fire your Data Scientists – They Aren’t Able to Add Value.

Although this statement is a bit extreme, the same situation may still exist. Data scientists frequently share frustrations such as:

  • “I’m told our data is 60% accurate, which means I can’t trust any of it.”
  • “We achieved our goal of an answer within a week by working 24 hours a day.”
  • “Each quarter we manually prepare 300 slides to anticipate all questions the CFO may ask.”
  • “Fred manually audits 10% of the invoices.  When he is on holiday, we just don’t do the audit.”

This is why I think the original quote is so insightful.  Value from data is not automatically delivered by hiring a statistician, analyst or data scientist. Even with the latest data mining technology, one person cannot positively influence a business without the proper data to support them.

Most organizations are unfamiliar with the structure required to deliver value from their data. New storage technologies will be introduced and a variety of analytics tools will be tried and tested. This change is crucial for to success. In order for statisticians to add value to a company, they must have access to high quality data that is easily sourced and integrated. That data must be available through the latest analytics technology. This new ecosystem should provide insights that can play a role in future production. Staff will need to be trained, as this new data will be incorporated into daily decision making.

With a rich 20-year history, Informatica understands data ecosystems. Employees become wasted investments when they do not have access to the trusted data they need in order to deliver their true value.

Who wants to spend their time recreating data sets to find a nugget of value only to discover it can’t be implemented?

Build a analytical ecosystem with a balanced focus on all aspects of data management. This will mean that value delivery is limited only by the imagination of your employees. Rather than questioning the value of an analytics team, you will attract some of the best and the brightest. Then, you will finally be able to deliver on the promised value of your data.

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Posted in Big Data, Business Impact / Benefits, Data Integration, Data Integration Platform, Data Warehousing | Tagged , , , | 3 Comments

Ten Facets of Data Governance

In this video, Rob Karel, vice president of product strategy, Informatica, outlines the Informatica Data Governance Framework, highlighting the 10 facets that organizations need to focus on for an effective data governance initiative:

  • Vision and Business Case to deliver business value
  • People
  • Tools and Architecture to support architectural scope of data governance
  • Policies that make up data governance function (security, archiving, etc.)
  • Measurement: measuring the level of influence of a data governance initiative and measuring its effectiveness (business value metrics, ROI metrics, such as increasing revenue, improving operational efficiency, reducing risk, reducing cost or improving customer satisfaction)
  • Change Management: incentives to workforce, partners and customers to get better quality data in and potential repercussions if data is not of good quality
  • Organizational Alignment: how the organization will work together across silos
  • Dependent Processes: identifying data lifecycles (capturing, reporting, purchasing and updating data into your environment), all processes consuming the data and processes to store and manage the data
  • Program Management: effective program management skills to build out communication strategy, measurement strategy and a focal point to escalate issues to senior management when necessary
  • Define Processes that make up the data governance function (discovery, definition, application and measuring and monitoring).

For more information from Rob Karel on the Informatica Data Governance Framework, visit his Perspectives blogs.

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Posted in Data Governance | Tagged , , , , , , , , , , , , , | Leave a comment

The Inches We Need Are Everywhere

So goes the line in the 1999 Oliver Stone film, Any Given Sunday. In the film, Al Pacino plays Tony D’Amato, a “been there, done that” football coach who, faced with a new set of challenges, has to re-evaluate his tried and true assumptions about everything he had learned through his career. In an attempt to rally his troops, D’Amato delivers a wonderful stump speech challenging them to look for ways to move the ball forward, treating every inch of the field as something sacred and encouraging them to think differently about how to do so.

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Posted in Data Governance, Data Quality, Pervasive Data Quality | Tagged , , , , , | Leave a comment

The Value of Knowing the Value

Ever wondered if an initiative is worth the effort?  Ever wondered how to quantify its worth?  This is a loaded question as you may suspect but I wanted to ask it nevertheless as my team of Global Industry Consultants work with clients around the world to do just that (aka Business Value Assessment or BVA) for solutions anchored around Informatica’s products.

How far will your investment stretch?

As these solutions typically involve multiple core business processes stretching over multiple departments and leveraging a legion of technology components like ETL, metadata management, business glossary, BPM, data virtualization, legacy ERP, CRM and billing systems, it initially sounds like a daunting level of complexity.  Opening this can of worms may end up in a measurement fatigue (I think I just discovered a new medical malaise.) (more…)

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Posted in Business Impact / Benefits, Business/IT Collaboration, CIO, Master Data Management, Operational Efficiency, Scorecarding | Tagged , , , , | Leave a comment

Data Virtualization Quick Tips

The ability to create abstract schemas that are mapped to back-end physical databases provides a huge advantage for those enterprises looking to get their data under control.  However, given the power of data virtualization, there are a few things that those in charge of data integration should know. Here are a few quick tips.

Tip 1:  Start with a new schema that is decoupled from the data sources. (more…)

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Posted in Data Services | Tagged , , , , | Leave a comment

Dear Santa…

Back in the good ol’ days, Santa Claus received letters and post cards from children all over the world.  When telephones and faxes became commonplace, they were also used to contact Santa.  In addition to those traditional methods, children today can also use the internet to send emails, Twitter, Facebook and even LinkedIn to notify Santa of their wish list. (more…)

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Posted in Business Impact / Benefits, Enterprise Data Management | Tagged , , , , | Leave a comment

(Data) Champions Are Everywhere

I recently had the opportunity to meet with the board of directors for a large distribution company here in the U.S.  On the table for discussion were data quality and data governance, and how a focus on both could help the organization gain competitive advantage in the market.  While I was happy to see that this company had tied data quality and data governance to help meet their corporate objectives, that’s not what caught my attention.  Instead, what impressed me the most was how the data quality and data governance champion had effectively helped the rest of the board see that there WAS a direct link, and that with careful focus they could drive better business outcomes than they could without a focus on data at all.  As it turns out, the path to success for the champion was to focus on articulating the link between trusted data — governed effectively — and the company’s ability to excel financially, manage costs, limit its risk exposure and maintain trust with its customers. (more…)

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Posted in Business/IT Collaboration, CIO, Data Governance, Data Quality, Data Warehousing, Pervasive Data Quality, Profiling, Scorecarding | Tagged , , , , , , , , , , , , | 1 Comment

Building A Business Case For Data Quality: The Steps

Building A Business Case For Data Quality, 3 of a 7-part series

Let’s look at the steps in more detail for building a business case for data quality using the bottom-up approach. Where do you start? You need to find a sponsor—someone who instinctively knows there is a problem and wants help in quantifying it. Marketing knows it has duplicate customer records and wants to get a better handle on them. You should look at these systems or business processes that work with the customer data. You must assess how the data in these systems is used within marketing. For example, what is the data used for, what critical decisions are made based on this data, and how many people use it to make decisions? The more users or the more critical the decision, the more likely this data is a candidate for evaluation. Also look at more than the initial decision support system and data. Look at any systems that get data from the decision support system. Data flow diagrams are always helpful in assessing this but usually difficult to find. (more…)

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Posted in Customers, Data Quality | Tagged , , , , , , , | Leave a comment

Understanding The Need for Quality Master Data

Of my recent series of papers on the value of data quality improvement, the first focused on the economic or financial aspects of data quality improvement. One of the goals of the paper was to show that if you iteratively drill down along the different economic value dimensions to look at the use of information that contributes to organizational success, you can establish a link between data failures and business or operational process success. For example, when looking at cost reduction as the high level value dimension, we see that when attempting to reduce the spend associated with particular products through better negotiations with vendors, duplicate product entries in the supplier catalog reduced the ability to do accurate review of costs of each item as well as classes of items. This inconsistency impacted the ability to achieve the cost reductions.

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Posted in Data Governance, Data Quality, Enterprise Data Management, Master Data Management | Tagged , , , , | Leave a comment

Inaugural Gartner MDM Summit In London A Major Hit

Europe might have started a little later than the U.S. with master data management, but if the inaugural Gartner MDM Summit for EMEA is any indication, it’s catching up quickly. Well over 350 registrants attended the event in London in early February, with strong representation from the UK, France, the Netherlands and other EMEA countries. Gartner Research VP Andrew White called the event a “major hit,” and I have to agree. (more…)

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Posted in Master Data Management, Pervasive Data Quality | Tagged , , , , , , , , , , , , , , , , , , | 1 Comment