Advancing Data-Driven Projects in Your Organization

This is a guest post from SSG, an Informatica Elite Partner specializing in Data Integration, DQ, MDM and ILM. The author is , the leader of the SSG Data Management practice.

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Advancing Data-Driven Projects

Data is increasingly becoming the fuel on which the world runs. Whether your objective is sales and marketing efficiency, regulatory compliance, or decreased costs, your success requires the ability to provide clean, safe and connected data to the right stakeholders.

In order for the right people to have the right data at the right time, business and IT need to communicate effectively and collaborate as champions of data. I recently spoke on a panel at the Informatica World Tour in Dallas, explaining how organizations can define and advance their data-related practices.

Here are topic highlights from the panel and my perspective on how to approach enterprise data management.

 

1. What are the primary trends impacting your business today?  

All of our clients want more data at a cheaper transactional price, whether it deals with the Internet of Things (IoT) and big data initiatives, Master Data Management (MDM) or traditional approaches, like data warehousing. People want the data faster than ever and need it now to support their jobs. There are so many self-service options today that you see shadow IT pockets popping up across the enterprise. Using cloud applications, the business can sometimes fire solutions up faster than traditional IT. This puts a lot of pressure on the IT teams to keep up with the industry capabilities and their customer demands.

 

2. What is the leading lesson learned that you would share with companies embarking on data management initiatives?

Get business buy-in and at a high level. Too many companies don’t do this upfront and they embark upon multimillion-dollar data-driven projects that either don’t meet expectations or have to be retooled before completion resulting in significant cost increases, missed expectations, and, most likely, a sacrificial lamb. All because IT drove a project without real business buy-in and sponsorship.

Companies should focus on periodic wins during their data initiatives. If they can pick one small thing to work on, and then show how the data-driven outcome makes a real difference in results, quality, customer satisfaction, etc., business leaders are more likely to identify the return on investment and continue their support. This approach is true for all types of projects including Master Data Management, Big Data, IoT, and Data Warehousing. Think small to get big!

 

3. What types of challenges have you experienced with business and IT working together?

One of the challenges I’ve seen over the years is alignment. IT will want to push something they need for IT related reasons, but the business leaders don’t understand its value to their teams. Without understanding the value of the IT change or enhancement, the business side won’t support the IT effort.

That being said, it’s very important to be able to communicate effectively from both an IT and a business perspective. Business leaders won’t resonate with scary technical acronyms like MDM and ETL. But they will resonate with phrases like, “increased customer engagement” or “reduced communications waste.” Show them how a data initiative will help their teams be more successful and they will jump on board.

 

4. How do you enforce or encourage accountability around the quality of data?

Ownership. If someone at a high level does not place value in data and ensure someone is on-point to manage the data, users won’t be able to trust the data. Without accountability you have no path for success with data-driven initiatives.

 

5. What surprises do you most commonly see with client data initiatives?

The biggest surprises are always the most obvious when looking back. For example, “we should have had buy-in from that leader” or “we needed those options we didn’t purchase” or “I wish we would have allowed more time for testing or initial data load.” The best thing I can recommend is to make sure your team is comprised of people who have already accomplished what you are trying to do. It’s worth it to search the marketplace for a consultant or even hire an employee that has been there and done that. Having experts on your team will help identify these things early where you can mitigate them for future success.

 

6. How much do requirements shift from initial definitions during engagements? How do you respond to changing requirements as the data is understood, i.e. as the organization shifted from traditional analytics to discovery analytics? How do you manage change?

Requirements always change throughout a project. It isn’t for lack of effort. As projects get underway, the teams have a better understanding of how things will work and what needs to change. This is reality and it should be embraced. My advice is to plan for shorter implementation cycles to deliver results faster and to allow for changes to occur in phases as you implement an overall program.

 

7. What does “great data” mean to you?

Great data to me is timely and accurate data that customers can see for decision-making. More than ever, time is money in today’s world. Every year the window of time seems to shrink because of technology advances. As a decision maker, the faster you can make a decision and adjust your business to current realities, the better off you are to ensuring your organization’s success. Great data helps you accomplish that.

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