Tag Archives: asset data

Utility Executives: Don’t Waste Millions in Operating Costs Due to Bad Asset Data

“Trying to improve the quality of asset data when you don’t have a solid data management infrastructure in place is like trying to save a sinking boat with a bailing bucket,” explained Dean Balog, a senior principal consultant at Noah Consulting, in this webinar, Attention Utility Executives: Don’t Waste Millions in Operating Costs Due to Bad Asset Data

Dean Balog from Noah Consulting explains how to improve the quality of mission-critical asset data for asset management / equipment maintenance and regulatory reporting, such as rate case submissions.

Dean has 15 years of experience in information management in the utilities industry. In this interview, Dean and I discuss the top issues facing utility executives and how to improve the quality of mission-critical asset data for asset management / equipment maintenance and regulatory reporting, such as rate case submissions.

Q: Dean, what are the top issues facing utility executives?
A: The first issue is asset management / equipment maintenance. Knowing where to invest precious dollars is critical. Utility executives are engaged in a constant tug of war between two competing priorities: replacing aging infrastructure and regular maintenance.

Q. How are utility executives determining that balance?
A. You need to start with facts – the real costs and reliability information for each asset in your infrastructure. Without it, you are guessing. Basically, it is a data problem. Utility executives should ask themselves these questions:

  • Do we have the ability to capture and combine cost and reliability information from multiple sources?  Is it granular enough to be useful?
  • Do we know the maintenance costs of eight-year-old breakers versus three-year-old breakers?
  • Do our meters start failing around the average lifespan? For this example, let us say that is five years. Rather than falling uniformly into that average, do 30% of our meters fail in the first year and the rest last eight years? Those three extra years of life can certainly help out the bottom line.

Knowing your data makes all the difference. The right capital investment strategy requires combining performance, reliability, and cost data.

Quotations about data challenges faced by utility companies

Quotations about data challenges faced by utility companies

Q. Why is it difficult for utility executives to understand the real costs and reliability of assets?
A. I know this does not come as a shock, but most companies do not trust their data. Asset data is often inaccurate, inconsistent, and disconnected. Even the most basic data may not be available. For example, manufacture dates on breakers should be filled in, but they are not. If less than 50% of your breakers have manufacture dates, how can you build a preventative maintenance program? You do not even know what to address first!

A traditional approach to solving this data problem is to do a big data cleanup. You clean the data, and then before you know it, errors creep back in, and the trust in the data you have worked so hard to establish is lost.

I like to illustrate the pain of this issue by using the sinking boat analogy. Data cleanup is like bailing out the water collecting in the bottom of the boat. You think you are solving the problem but more water still seeps into the boat. You cannot stop bailing or you will sink. What you need to do is fix the leaks, and then bail out the boat. But, if you do not lift up your head from bailing long enough to see the leaks and make the right investments, you are fighting a losing battle.

Q. What can utility executives do to improve the quality of asset data?
A. First of all, you need to develop a data governance framework. Going back to the analogy, a data governance framework gives you the structure to find the leaks, fix the leaks, and monitor how much of the water has been bailed out. If the water level is still rising, you have not fixed all the leaks. But having a data governance framework is not the be-all and end-all.

You also need to appoint data stewards to be accountable for establishing and maintaining high quality asset data. The job of a data steward would be easy if there was only one system where all asset data resided. But the fact of the matter is that asset data is fragmented – scattered across multiple systems. Data stewards have a huge responsibility and they need to be supported by a solid data management infrastructure to ease the burden of managing business-critical asset information.

Webinar, Attention Utility Executives Bad Asset Data

If you are responsible for asset management / equipment maintenance or regulatory reporting, particularly rate case submissions, check out this webinar.

Master Data Management (MDM) ensures business-critical asset data is consistent everywhere by pulling together data that is scattered across multiple applications. It manages and masters it in a central location on a continuous basis and shares it with any applications that need that data. MDM provides a user interface and workflow for data stewards to manage the tangled web of names and IDs these assets are known by across systems. It also gives utilities a disciplined approach to manage important relationships between the asset data, such as an asset’s performance reliability and its cost.

Q. Any other pressing issues facing utilities?
A. Yes. Another big issue is tightening regulations that consume investment dollars and become key inputs into rate case submissions and defenses. One of the complicating factors is the number of regulations is not only increasing, but the regulators are also requiring faster implementation times than ever before. So, utilities cannot just do what they have done in the past: throw more people at the problem in the short-term and resolve to fix it later by automating it “when things slow down.” That day never comes.

Q. How can utilities deal with these regulatory pressures?
A. Utilities need a new approach to deal with regulations. Start with the assumption that all data is fair game for regulators. All data must be accessible. You need to be able to report on it, not only to comply with regulations, but for competitive advantage. This requires the high quality asset information we talked about earlier, and an analytical application to:

  • Perform what-if analyses for your asset investment program;
  • Develop regulatory compliance or environmental reports quickly, because the hard work (integrating the data within your MDM program) has already been done; and
  • Get access to granular, observed reliability and cost information using your own utility’s data – not benchmark data that is already a couple of years old and highly summarized.

Q. What is your advice for utility company executives?
A. If you are the one responsible for signing off on regulatory reports and you do not look good in an orange jumpsuit, you need to invest in a plan that includes people, process, and technology to support regulatory reporting and asset management / equipment maintenance.

  • People – Data stewards have clear accountability for the quality of asset data.
  • Process – Data governance is your game plan.
  • Technology – A solid data management infrastructure consisting of data integration, data quality, and master data management is your means.

If you are responsible for asset management / equipment maintenance or regulatory reporting, particularly rate case submissions, check out this webinar, Attention Utility Executives: Don’t Waste Millions in Operating Costs Due to Bad Asset Data

 Our panel of utility data experts:

  • Reveal the five toughest business challenges facing utility industry executives;
  • Explain how bad asset data could be costing you millions of dollars in operating costs;
  • Share three best practices for optimizing asset management / equipment maintenance and regulatory reporting with accurate, consistent, and connected asset information; and
  • Show you how to implement these best practices with a demonstration.

 

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Posted in Data Governance, Data Integration, Data Quality, Enterprise Data Management, Master Data Management, Partners, Utilities & Energy, Vertical | Tagged , , , , , , , , , , , , , , , , | Leave a comment

How Much Does Bad Data Cost Your Business?

Bad data is bad for business. Ovum Research reported that poor quality data is costing businesses at least 30% of revenues. Never before have business leaders across a broad range of roles recognized the importance of using high quality information to drive business success. Leaders in functions ranging from marketing and sales to risk management and compliance have invested in world-class applications, six sigma processes, and the most advanced predictive analytics. So why are you not seeing more return on that investment? Simply put, if your business-critical data is a mess, the rest doesn’t matter.

Dennis Moore explains the implications of using inaccurate, inconsistent and disconnected data and the value business leaders can gain by mastering it.

Dennis Moore explains the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).

Not all business leaders know there’s a better way to manage their business-critical data. So, I asked Dennis Moore, the senior vice president and general manager of Informatica’s MDM business, who clocked hundreds of thousands of airline miles last year visiting business leaders around the world, to talk about the impact of using accurate, consistent and connected data and the value business leaders can gain through master data management (MDM).

Q. Why are business leaders focusing on business-critical data now?
A. Leaders have always cared about their business-critical data, the master data on which their enterprises depend most — their customers, suppliers, the products they sell, the locations where they do business, the assets they manage, the employees who make the business perform. Leaders see the value of having a clear picture, or “best version of the truth,” describing these “master data” entities. But, this is hard to come by with competing priorities, mergers and acquisitions and siloed systems.

As companies grow, business leaders start realizing there is a huge gap between what they do know and what they should know about their customers, suppliers, products, assets and employees. Even worse,  most businesses have lost their ability to understand the relationships between business-critical data so they can improve business outcomes. Line of business leaders have been asking questions such as:

  • How can we optimize sales across channels when we don’t know which customers bought which products from which stores, sites or suppliers?
  • How can we quickly execute a recall when we don’t know which supplier delivered a defective part to which factory and where those products are now?
  • How can we accelerate time-to-market for a new drug, when we don’t know which researcher at which site used which combination of compounds on which patients?
  • How can we meet regulatory reporting deadlines, when we don’t know which model of a product we manufactured in which lot on which date?

Q. What is the crux of the problem?
A. The crux of the problem is that as businesses grow, their business-critical data becomes fragmented. There is no big picture because it’s scattered across applications, including on premise applications (such as SAP, Oracle and PeopleSoft) and cloud applications (such as Salesforce, Marketo, and Workday). But it gets worse. Business-critical data changes all the time. For example,

  • a customer moves, changes jobs, gets married, or changes their purchasing habits;
  • a suppliers moves, goes bankrupt or acquires a competitor;
  • you discontinue a product or launch a new one; or
  • you onboard a new asset or retire an old one.

As all this change occurs, business-critical data becomes inconsistent, and no one knows which application has the most up-to-date information. This costs companies money. It saps productivity and forces people to do a lot of manual work outside their best-in-class processes and world-class applications. One question I always ask business leaders is, “Do you know how much bad data is costing your business?”

Q. What can business leaders do to deal with this issue?
A. First, find out where bad data is having the most significant impact on the business. It’s not hard – just about any employee can share stories of how bad data led to a lost sale, an extra “truck roll,” lost leverage with suppliers, or a customer service problem. From the call center to the annual board planning meeting, bad data results in sub-optimal decisions and lost opportunities. Work with your line of business partners to reach a common understanding of where an improvement can really make a difference. Bad master data is everywhere, but bad master data that has material costs to the business is a much more pressing and constrained problem. Don’t try to boil the ocean or bring a full-blown data governance maturity level 5 approach to your organization if it’s not already seeing success from better data!

Second, focus on the applications and processes used to create, share, and use master data. Many times, some training, a tweak to a process, or a new interface can be created between systems, resulting in very significant improvements for the users without major IT work or process changes.

Lastly, look for a technology that is purpose-built to deal with this problem.  Master data management (MDM) helps companies better manage business-critical data in a central location on an ongoing basis and then share that “best version of the truth” with all on premise and cloud applications that need it.

Master data management (MDM) helps manage business-critical customer data and creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

Master data management (MDM) helps manage business-critical customer data and creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

Let’s use customer data as an example. If valuable customer data is located in applications such as Salesforce, Marketo, Seibel CRM, and SAP, MDM brings together all the business-critical data, the core that’s the same across all those applications, and creates the “best version of the truth.” It also creates the total customer relationship view across functions, product lines and regions, which CRM promised but never delivered.

MDM then shares that “mastered” customer data and the total customer relationship view with the applications that want it. MDM can be used to master the relationships between customers, such as legal entity hierarchies. This helps sales and customer service staff be more productive, while also improving legal compliance and management decision making. Advanced MDM products can also manage relationships across different types of master data. For example, advanced MDM enables you to relate an employee to a project to a contract to an asset to a commission plan. This ensures accurate and timely billing, effective expense management, managed supplier spend, and even improved workforce deployment.

When your sales team has the best possible customer information in Salesforce and the finance team has the best possible customer information in SAP, no one wastes time pulling together spreadsheets of information outside of their world-class applications. Your global workforce doesn’t waste time trying to investigate whether Jacqueline Geiger in one system and Jakki Geiger in another system is one or two customers, sending multiple bills and marketing offers at high cost in postage and customer satisfaction. All employees who have access to mastered customer information can be confident they have the best possible customer information available across the organization to do their jobs. And with the most advanced and intelligent data platform, all this information can be secured so only the authorized employees, partners, and systems have access.

Q. Which industries stand to gain the most from mastering their data?
A. In every industry there is some transformation going on that’s driving the need to know people, places and things better. Take insurance for example. Similar to the transformation in the travel industry that reduced the need for travel agents, the insurance industry is experiencing a shift from the agent/broker model to a more direct model. Traditional insurance companies now have an urgent need to know their customers so they can better serve them across all channels and across multiple lines of business.

In other industries, there is an urgent need to get a lot better at supply-chain management or to accelerate new product introductions  to compete better with an emerging rival. Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data, particularly in industries undergoing rapid transformation, or with rapidly changing regulatory requirements.

Q. Which business functions seem most interested in mastering their business-critical data?
A. It varies by industry, but there are three common threads that seem to span most industries:

Business leaders are starting to make the connection between transformation failures and bad data.

Business leaders are starting to make the connection between transformation failures and a more critical need for the best possible data.

  • MDM can help the marketing team optimize the cross-sell and up-sell process with high quality data about customers, their households or company hierarchies, the products and services they have purchased through various channels, and the interactions their organizations have had with these customers.
  • MDM can help the procurement team optimize strategic sourcing including supplier spend management and supplier risk management with high quality data about suppliers, company hierarchies,  contracts and the products they supply.
  • MDM can help the compliance teams manage all the business-critical data they need to create regulatory reports on time without burning the midnight oil.

Q. How is the use of MDM evolving?
A. When MDM technology was first introduced a decade ago, it was used as a filter. It cleaned up business-critical data on its way to the data warehouse so you’d have clean, consistent, and connected information (“conformed dimensions”) for reporting. Now business leaders are investing in MDM technology to ensure that all of their global employees have access to high quality business-critical data across all applications. They believe high quality data is mission-critical to their operations. High quality data is viewed as the the lifeblood of the company and will enable the next frontier of innovation.

Second, many companies mastered data in only one or two domains (customer and product), and used separate MDM systems for each. One system was dedicated to mastering customer data. You may recall the term Customer Data Integration (CDI). Another system was dedicated to mastering product data. Because the two systems were in silos and business-critical data about customers and products wasn’t connected, they delivered limited business value. Since that time, business leaders have questioned this approach because business problems don’t contain themselves to one type of data, such as customer or product, and many of the benefits of mastering data come from mastering other domains including supplier, chart of accounts, employee and other master or reference data shared across systems.

The relationships between data matter to the business. Knowing what customer bought from which store or site is more valuable than just knowing your customer. The business insights you can gain from these relationships is limitless. Over 90% of our customers last year bought MDM because they wanted to master multiple types of data. Our customers value having all types of business-critical data in one system to deliver clean, consistent and connected data to their applications to fuel business success.

One last evolution we’re seeing a lot involves the types and numbers of systems connecting to the master data management system. In the past, there were a small number of operational systems pushing data through the MDM system into a data warehouse used for analytical purposes. Today, we have customers with hundreds of operational systems communicating with each other via an MDM system that has just a few milliseconds to respond, and which must maintain the highest levels of availability and reliability of any system in the enterprise. For example, one major retailer manages all customer information in the MDM system, using the master data to drive real-time recommendations as well as a level of customer service in every interaction that remains the envy of their industry.

Q. Dennis, why should business leaders consider attending MDM Day?
A. Business leaders should consider attending MDM Day at InformaticaWorld 2014 on Monday, May 12, 2014. You can hear first-hand the business value companies are gaining by using clean, consistent and connected information in their operations. We’re excited to have fantastic customers who are willing to share their stories and lessons learned. We have presenters from St. Jude Medical, Citrix, Quintiles and Crestline Geiger and panelists from Thomson Reuters, Accenture, EMC, Jones Lang Lasalle, Wipro, Deloitte, AutoTrader Group, McAfee-Intel, Abbvie, Infoverity, Capgemini, and Informatica among others.

Last year’s Las Vegas event, and the events we held in London, New York and Sao Paolo were extremely well received. This year’s event is packed with even more customer sessions and opportunities to learn and to influence our product road map. MDM Day is one day before InformaticaWorld and is included in the cost of your InformaticaWorld registration. We’d love to see you there!

See the MDM Day Agenda.

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Posted in Business Impact / Benefits, Business/IT Collaboration, Customers, Data Quality, Informatica World 2014, Master Data Management | Tagged , , , , , , , , , , , , , , , , , , | Leave a comment