Category Archives: Manufacturing

8 Information Management Challenges for UDI Compliance

“My team spends far too much time pulling together medical device data that’s scattered across different systems and reconciling it in spreadsheets to create compliance reports.” This quotation from a regulatory affairs leader at a medical device manufacturer highlights the impact of poorly managed medical device data on compliance reporting, such as the reports needed for the FDA’s Universal Device Identification (UDI) regulation. In fact, an overreliance on manual, time-consuming processes brings an increased risk of human error in UDI compliance reports.

frustrated_man_computer

Is your compliance team manually reconciling data for UDI compliance reports?

If you are an information management leader working for a medical device manufacturer, and your compliance team needs quick and easy access to medical device data for UDI compliance reporting, I have five questions for you:

1) How many Class III and Class II devices do you have?
2) How many systems or reporting data stores contain data about these medical devices?
3) How much time do employees spend manually fixing data errors before the data can be used for reporting?
4) How do you plan to manage medical device data so the compliance team can quickly and easily produce accurate reports for UDI Compliance?
5) How do you plan to help the compliance team manage the multi-step submission process?

Watch this on-demand webinar "3 EIM Best Practices for UDI Compliance"

Watch this on-demand webinar “3 EIM Best Practices for UDI Compliance”

For some helpful advice from data management experts, watch this on-demand webinar “3 Enterprise Information Management (EIM) Best Practices for UDI Compliance.”

The deadline to submit the first UDI compliance report to the FDA for Class III devices is September 24, 2014. But, the medical device data needed to produce the report is typically scattered among different internal systems, such as Enterprise Resource Planning (ERP) e.g. SAP and JD Edwards, Product Lifecycle Management (PLM), Manufacturing Execution Systems (MES) and external 3rd party device identifiers.

The traditional approach for dealing with poorly managed data is the compliance team burns the midnight oil to bring together and then manually reconcile all the medical device data in a spreadsheet. And, they have to do this each and every time a compliance report is due. The good news is your compliance team doesn’t have to.

Many medical device manufacturers are are leveraging their existing data governance programs, supported by a combination of data integration, data quality and master data management (MDM) technology to eliminate the need for manual data reconciliation. They are centralizing their medical device data management, so they have a single source of trusted medical device data for UDI compliance reporting as well as other compliance and revenue generating initiatives.

Get UDI data management advice from data experts Kelle O'Neal, Managing Partner at First San Francisco Partners and Bryan Balding, MDM Specialist at Informatica
Get UDI data management advice from data experts Kelle O’Neal, Managing Partner at First San Francisco Partners and Bryan Balding, MDM Specialist at Informatica

During this this on-demand webinar, Kelle O’Neal, Managing Partner at First San Francisco Partners, covers the eight information management challenges for UDI compliance as well as best practices for medical device data management.

Bryan Balding, MDM Solution Specialist at Informatica, shows you how to apply these best practices with the Informatica UDI Compliance Solution.

You’ll learn how to automate the process of capturing, managing and sharing medical device data to make it quicker and easier to create the reports needed for UDI compliance on ongoing basis.

 

 

20 Questions & Answers about Complying with the FDA Requirement for Unique Device Identification (UDI)

20 Questions & Answers about Complying with the FDA Requirement
for Unique Device Identification (UDI)

Also, we just published a joint whitepaper with First San Francisco Partners, Information Management FAQ for UDI: 20 Questions & Answers about Complying with the FDA Requirement for Unique Device Identification (UDI). Get answers to questions such as:

What is needed to support an EIM strategy for UDI compliance?
What role does data governance play in UDI compliance?
What are the components of a successful data governance program?
Why should I centralize my business-critical medical device data?
What does the architecture of a UDI compliance solution look like?

I invite you to download the UDI compliance FAQ now and share your feedback in the comments section below.

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Posted in Data Governance, Data Integration, Data Quality, Enterprise Data Management, Life Sciences, Manufacturing, Master Data Management, Vertical | Tagged , , , , , , , , , , , , , , | Leave a comment

The Catalog is Dead – Long Live the Catalog?

The Catalog is Dead.

Print solution provider Werk II came up with a provocative marketing campaign in 2012. Their ads have been designed like the obituary notice for the “Main Catalog” which is “no longer with us”…

According to the Multi Channel Merchant Outlook 2014 survey, the eCommerce website (not a surprise ;-) ) is the top channel through which merchants market (90%). The social media (87.2%) and email (83%) channels follow close behind. Although catalogs may have dropped as a marketing tool, 51.7% of retailers said they still use the catalog to market their brands.

importance of channels chart

Source: MCM Outlook 2014

The Changing Role of the Catalog

Merchants are still using catalogs to sell products. However, their role has changed from transactional to sales tool. On a scale of 1 to 10, with 10 being the most important, merchant respondents said that using catalogs as mobile traffic drivers and custom retention tools were the most important activities (both scored an 8.25). At 7.85, web traffic driver was a close third.

methods of prospecting chart

Source: MCM Outlook 2014

Long Live the Catalog: Prospecting 

More than three-quarters of merchant respondents said catalogs were the top choice for the method of prospecting they will use in the next 12 months (77.7%). Catalog was the most popular answer, followed by Facebook (68%), email (66%), Twitter (42.7%) and Pinterest (40.8%).

What is your point of view?

How have catalogs changed in your business? What are your plans and outlook for 2015? It would be very interesting to hear points of views from different industries and countries… I’d be happy to discuss here or on Twitter @benrund. My favorite fashion retailer keeps sending me a stylish catalog, which makes me order online. Brands, retailer, consumer – how do you act, what do you expect?

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Posted in B2B, Manufacturing, Master Data Management, PiM, Product Information Management, Retail, Uncategorized | Tagged , , , | 1 Comment

Right Product, Right Customer, Right Place – The Informed Purchase Journey

The Informed Purchase Journey

The way we shop has changed. It’s hard to keep up with customer demands in a single channel, much less many. Selling products today has changed and always will. The video below shows how today’s customer takes The Informed Purchase Journey:

“Customers expect a seamless experience that makes it easy for them to engage at every touchpoint on their “decision journey. Informatica PIM is key component on  transformation from a product centric view to a consumer experience driven marketing with more efficiency.” – Heather Hanson – Global Head of Marketing Technology at Electrolux

Selling products today is:

  • Shopper-controlled. It’s never been easier for consumers to compare products and prices. This has eroded old customer loyalty and means you have to earn every sale.
  • Global. If you’re selling your products in different regions, you’re facing complex localization and supply chain coordination.
  • Fast. Product lifecycles are short. Time-to-market is critical (and gets tougher the more channels you’re selling through).
  • SKU-heavy. Endless-aisle assortments are great for margins. That’s a huge opportunity, but product data overload due to the large number of SKUs and their attributes adds up to a huge admin burden.
  • Data driven. Product data alone is more than a handful to deal with. But you also need to know as much about your customers as you know about your products. And the explosion of channels and touch points doesn’t make it any easier to connect the dots.

Conversion Power – From Deal Breaker To Deal Maker

For years, a customer’s purchase journey was something of “An Unexpected Journey.” Lack of insight into the journey was a struggle for retailers and brands. The journey is fraught with more questions about product than ever before, even for fast moving consumer goods.

Today, the consumer behaviors and the role of product information have changed since the advent of substantial bandwidths and social buying. To do so, lets examine the way shoppers buy today.

  • Due to Google shoppers use 10.4 sources in average (zero moment of truth ZMOT google research)
  •  133% higher conversion rate shown by mobile shoppers who view customer content like reviews.
  • Digital devices’ influence 50% of in-store purchase behavior by end of 2014 (Deloitte’s Digital Divide)

How Informatica PIM 7.1 turns information from deal breaker to deal maker

PIM 7.1 comes with new data quality dashboards, helping users like category managers, marketing texters, managers or ecommerce specialists to do the right things. The quality dashboards point users to the things they have to do next in order to get the data right, out and ready for sales.

Eliminate Shelf Lag: The Early Product Closes the Sale

For vendors, this effectively means time-to-market: the availability of a product plus the time it takes to collect all relevant product information so you can display it to the customer (product introduction time).

The biggest threat is not the competition – it’s your own time-consuming, internal processes. We call this Shelf Lag, and it’s a big inhibitor of retailer profits. Here’s why:

  • You can’t sell what you can’t display.
  • Be ready to spin up new channels
  • Watch your margins.

How Informatica PIM 7.1 speeds up product introduction and customer experience

“By 2017… customer experience is what buyers are going to use to make purchase decisions.” (Source: Gartner’s Hype Cycle for E-Commerce, 2013) PIM 7.1 comes with new editable channel previews. This helps business users like marketing, translators, merchandisers or product managers to envistion how the product looks at the cutomer facing webshop, catalog or other touchpoint. Getting products live online within seconds, we is key because the customer always wants it now. For eCommerce product data Informatica PIM is certified for IBM WebSphere Commerce to get products ready for ecommerce within seconds.

The editable channel previews helps professionals in product management, merchandizing, marketing and ecommerce to envision their products as customers are facing it. The way of “what you see is what you get (WYSIWYG)” product data management improves customer shopping experience with best and authentic information. With the new eCommerce integration, Informatica speeds up the time to market in eBusiness. The new standard (certified by IBM WebSphere Commerce enables a live update of eShops with real time integration.

The growing need for fast and s ecure collaboration across globally acting enterprises is addressed by the Business Process Management tool of Informatica, which can now be used for PIM customers.

Intelligent insights: How relevant is our offering to your customers?

This is the age of annoyance and information overload. Each day, the average person has to handle more than 7,000 pieces of information. Only 25% of Americans say there are brand loyal. That means brands and retailers have to earn every new sale in a transparent world. In this context information needs to be relevant to the recipient.

  • Where do the data come from? How can product information auto-cleansed and characterizing into a taxonomy?
  • Is the supplier performance hitting our standards?
  • How can we mitigate risks like hidden costs and work with trusted suppliers only?
  • How can we and build customer segmentations for marketing?
  • How to build product personalization and predict the next logical buy of the customer?

It is all about The Right product. To the Right Person. In the Right Way. Learn more about the vision of the Intelligent Data Plaform.

Informatica PIM Builds the Basis of Real Time Commerce Information

All these innovations speed up the new product introduction and collaboration massively. As buyers today are always online and connected, PIM helps our customer to serve the informed purchase journey, with the right information in at the right touch point and in real time.

  1. Real-time commerce (certification with IBM WebSphere Commerce), which eliminates shelf lag
  2. Editable channel preview which help to envision how customers view the product
  3. Data quality dashboards for improved conversion power, which means selling more with better information
  4. Business Process Management for better collaboration throughout the enterprise
  5. Accelerator for global data synchronization (GDSN like GS1 for food and CPG) – which helps to improve quality of data and fulfill legal requirements

All this makes merchandizers more productive and increases average spend per customer.

Find out how the new release of Informatica PIM 7.1 helps you to unleash conversion power on the customer’s informed purchase journey.

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Posted in B2B, B2B Data Exchange, CMO, Manufacturing, Master Data Management, PiM, Product Information Management, Retail | Tagged , , , | Leave a comment

One Search Procurement – For the Purchasing of Indirect Goods and Services

One Search Procurement – for purchasing of indirect goods and services 

Informatica Procurement is the internal Amazon for purchasing of MRO, C-goods, indirect materials and services. Informatica Procurement supports enterprise companies in catalog procurement with an industry-independent catalog procurement solution that enables fast and cost-efficient procurement of products and services and supplier integration in an easy to use self-service concept.

Information Procurement at a glance

informatica-procurement-at-a-glance

Informatica recently announced the availability of Informatica Procurement 7.3, the catalog procurement solution. I meet with Melanie Kunz our product manager to learn from here what’s new.

Melanie, for our readers and followers, who is using Informatica Procurement, for which purposes?

Melanie Kunz

Melanie Kunz: Informatica Procurement is industry-independent. Our customers are based in different industries – from engineering and the automotive to companies in the public sector (e.g. Cities). The responsibilities of people who work with Informatica Procurement differ depending on the company. For some customers, only employees from the purchasing department order items in Informatica Procurement. For other customers, all employees are allowed to order their needs themselves. Examples are employees who need screws for the completion of their product or office staff who ordered the business cards for the manager.

What is the most important thing to know about Informatica Procurement 7.3?

Melanie Kunz: In companies where a lot of IT equipment is ordered, it is important to always see the current prices. With each price changes, the catalog would have to be imported into Informatica Procurement. With a punch out to the online shop of IT equipment manufacturer, this is much easier and more efficient. The data from these catalogs are all available in Informatica Procurement, but the price can always be called on a daily basis from the online shop.

Users no longer need to leave Informatica Procurement to order items from external online shops. Informatica Procurement now enables the user to locate internal and indexed external items in just one search. That means you do not have to use different eShops for when you order new office stationary, IT equipment or services.

Great, what is the value for enterprise users and purchasing departments?

Melanie Kunz: All items in Informatica Procurement have the negotiated prices. Informatica Procurement is simple and intuitive that each employee can use the system without training. The view concept allows the restriction on products. For each employee (each department), the administrator can define a view. This view contains only the products that can be seen and ordered.

When you open the detail view for an indexed external item, the current price is determined from the external online shop. This price is saved in item detail view for a defined period. In this way, the user always gets the current price for the item.

The newly designed detail view has an elegant and clear layout. Thus, a high level of user experience is safe. This also applies to the possibility of image enlargement in the search result list.

What if I order same products frequently, like my business cards?

Melanie Kunz: The overview of recent shopping carts help users to reorder the same items on an easy and fast way. A shopping cart from a previous order can use as basis for this new order.

Large organizations with 1000s of employees are even more might have totally different needs what they need for the daily business and maybe dedicated to their career level. How do you address this?

Melanie Kunz: The standard assortment feature has been enhanced in Informatica Procurement 7.3. Administrators can define the assortment per user. Furthermore, it is possible to specify whether users have to search the standard assortment first and only search in the entire assortment if they do not find the relevant item in the standard assortment.

All of these features and many more minor features not only enhance the user experience, but also reduce the processing time of an order drastically.

Informatica Procurement 7.3 “One Search” at a glance

One Search Procurement

 

Learn more on Informatica Procurement 7.3 with the latest webinar.

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Posted in Data Integration, Enterprise Data Management, Life Sciences, Manufacturing, Marketplace, Master Data Management, News & Announcements, Operational Efficiency, PiM, Public Sector | Tagged , , , | Leave a comment

How Much is Poorly Managed Supplier Information Costing Your Business?

Supplier Information“Inaccurate, inconsistent and disconnected supplier information prohibits us from doing accurate supplier spend analysis, leveraging discounts, comparing and choosing the best prices, and enforcing corporate standards.”

This is quotation from a manufacturing company executive. It illustrates the negative impact that poorly managed supplier information can have on a company’s ability to cut costs and achieve revenue targets.

Many supply chain and procurement teams at large companies struggle to see the total relationship they have with suppliers across product lines, business units and regions. Why? Supplier information is scattered across dozens or hundreds of Enterprise Resource Planning (ERP) and Accounts Payable (AP) applications. Too much valuable time is spent manually reconciling inaccurate, inconsistent and disconnected supplier information in an effort to see the big picture. All this manual effort results in back office administrative costs that are higher than they should be.

Do these quotations from supply chain leaders and their teams sound familiar?

  • “We have 500,000 suppliers. 15-20% of our supplier records are duplicates. 5% are inaccurate.”
  • I get 100 e-mails a day questioning which supplier to use.”
  • “To consolidate vendor reporting for a single supplier between divisions is really just a guess.”
  • “Every year 1099 tax mailings get returned to us because of invalid addresses, and we play a lot of Schedule B fines to the IRS.”
  • “Two years ago we spent a significant amount of time and money cleansing supplier data. Now we are back where we started.”
Webinar, Supercharge Your Supply Chain Apps with Better Supplier Information

Join us for a Webinar to find out how to supercharge your supply chain applications with clean, consistent and connected supplier information

Please join me and Naveen Sharma, Director of the Master Data Management (MDM) Practice at Cognizant for a Webinar, Supercharge Your Supply Chain Applications with Better Supplier Information, on Tuesday, July 29th at 11 am PT.

During the Webinar, we’ll explain how better managing supplier information can help you achieve the following goals:

  1. Accelerate supplier onboarding
  2. Mitiate the risk of supply disruption
  3. Better manage supplier performance
  4. Streamline billing and payment processes
  5. Improve supplier relationship management and collaboration
  6. Make it easier to evaluate non-compliance with Service Level Agreements (SLAs)
  7. Decrease costs by negotiating favorable payment terms and SLAs

I hope you can join us for this upcoming Webinar!

 

 

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Posted in Business Impact / Benefits, Business/IT Collaboration, Data Integration, Data Quality, Manufacturing, Master Data Management | Tagged , , , , , , , , , , , , , , | Leave a comment

Margin Killer: How a pair of pants plummeted profits

Recently, I ordered a pair of athletic pants from a high-fashion, online retailer. The pants were a well-known brand and cost $96.00. The package arrived within a few days. However, when I opened the box, I found it did not contain the product I expected. The brand and color were correct, but it was not the style I’d chosen. Disappointed, I wrote the retailer, explaining the issue and requesting the correct product. Then, I returned the incorrect product.

According to recent research, the average vendor’s “cost per return” is $20.00.  That means that my return was a Margin Killer for the retailer.

product-return

Product returns kill margins.

Three days later, the replacement delivery arrived. Whoop there it is… Disappointment number two. It was the exact same incorrect product. Yet another Margin Killer, Return Number 2. Another $20.00 in costs for the retailer. What would it take for this retailer’s logistic team to avoid repeating their error? Could they scan the product? Could they use a QR code, a bar-code or some sort of picture?

I returned the incorrect product for the second time. Eventually, shipment number three reached my home. Can you guess what was in the box? Yes, the same incorrect product, again, for the third time. The Margin Killer: Return Number 3. For this retailer, the math is simple:

Return 1: $20.00
Return 2: $20.00
Return 3: $20.00
Total return cost: $60.00
Revenue = Possibly zero?

Funky side note: When browsing stores downtown on Saturday, I found the correct pants in a SportScheck store, and for ten dollars less! So remember, the modern customer is demanding, always-connected and shopping on an “Informed Purchase Journey”.

So how can I learn more?
If you work in retail technology, you will find rich information about this purchase journey at the Informatica World 2014 conference. The Retail Path track will feature insights from companies like Nike, Avent, Discount Tire, Nordstrom, Geiger, Intricity and Deloitte. Experts will share ways to leverage your data to boost your sales and heighten customer experience. The conference even has a dedicated MDM Day on Monday May 12 with workshops and sessions showing how vendors, distributors, retailers and individuals interact in the “always-on” connected world. Make sure you have a spot by signing up HERE.

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Posted in Manufacturing, Master Data Management, PiM, Product Information Management, Retail | Tagged , , , , | 3 Comments

Death of the Data Scientist: Silver Screen Fiction?

Maybe the word “death” is a bit strong, so let’s say “demise” instead.  Recently I read an article in the Harvard Business Review around how Big Data and Data Scientists will rule the world of the 21st century corporation and how they have to operate for maximum value.  The thing I found rather disturbing was that it takes a PhD – probably a few of them – in a variety of math areas to give executives the necessary insight to make better decisions ranging from what product to develop next to who to sell it to and where.

Who will walk the next long walk.... (source: Wikipedia)

Who will walk the next long walk…. (source: Wikipedia)

Don’t get me wrong – this is mixed news for any enterprise software firm helping businesses locate, acquire, contextually link, understand and distribute high-quality data.  The existence of such a high-value role validates product development but it also limits adoption.  It is also great news that data has finally gathered the attention it deserves.  But I am starting to ask myself why it always takes individuals with a “one-in-a-million” skill set to add value.  What happened to the democratization  of software?  Why is the design starting point for enterprise software not always similar to B2C applications, like an iPhone app, i.e. simpler is better?  Why is it always such a gradual “Cold War” evolution instead of a near-instant French Revolution?

Why do development environments for Big Data not accommodate limited or existing skills but always accommodate the most complex scenarios?  Well, the answer could be that the first customers will be very large, very complex organizations with super complex problems, which they were unable to solve so far.  If analytical apps have become a self-service proposition for business users, data integration should be as well.  So why does access to a lot of fast moving and diverse data require scarce PIG or Cassandra developers to get the data into an analyzable shape and a PhD to query and interpret patterns?

I realize new technologies start with a foundation and as they spread supply will attempt to catch up to create an equilibrium.  However, this is about a problem, which has existed for decades in many industries, such as the oil & gas, telecommunication, public and retail sector. Whenever I talk to architects and business leaders in these industries, they chuckle at “Big Data” and tell me “yes, we got that – and by the way, we have been dealing with this reality for a long time”.  By now I would have expected that the skill (cost) side of turning data into a meaningful insight would have been driven down more significantly.

Informatica has made a tremendous push in this regard with its “Map Once, Deploy Anywhere” paradigm.  I cannot wait to see what’s next – and I just saw something recently that got me very excited.  Why you ask? Because at some point I would like to have at least a business-super user pummel terabytes of transaction and interaction data into an environment (Hadoop cluster, in memory DB…) and massage it so that his self-created dashboard gets him/her where (s)he needs to go.  This should include concepts like; “where is the data I need for this insight?’, “what is missing and how do I get to that piece in the best way?”, “how do I want it to look to share it?” All that is required should be a semi-experienced knowledge of Excel and PowerPoint to get your hands on advanced Big Data analytics.  Don’t you think?  Do you believe that this role will disappear as quickly as it has surfaced?

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Posted in Big Data, Business Impact / Benefits, CIO, Customer Acquisition & Retention, Customer Services, Data Aggregation, Data Integration, Data Integration Platform, Data Quality, Data Warehousing, Enterprise Data Management, Financial Services, Healthcare, Life Sciences, Manufacturing, Master Data Management, Operational Efficiency, Profiling, Scorecarding, Telecommunications, Transportation, Uncategorized, Utilities & Energy, Vertical | Tagged , , , , | 1 Comment

Merchandizers, The Compromise Effect Has Gone – User Reviews Overcome Marketing Manipulation

I was recently boarding a flight in New York and started reading the New York Times. One article jumped out: “User reviews make it harder for marketers to manipulate.” A Stanford University research report proves a wealth of product information and user reviews is causing a fundamental shift in how consumers make decisions.

 Consumers rely more on one another

The latest research from Dr. Simonson and Emanual Rosen is based on an experiment performed decades ago at Duke University. In the experiment participants had to choose from a group of either two or three cameras. The research found that consumers chose the cheaper product when being offered two options, but when given three choices, most went with the middle one. It was called the “compromise effect,” which has been used by marketers to impact buying decisions.

But an updated version of the experiment allowed participants to read product ratings and reviews before choosing one of the three cameras. While a portion of the participants always choose the lowest-priced product, in this new scenario more participants are selecting the most expensive product over the middle-priced product based on customer reviews.

“The compromise effect is gone,” says Dr. Simonson in this New York Times article. The Book “Absolute Value” comes with a more in depth explanation: (http://www.absolutevaluebook.com/).

 product comparison

Imagine if you could own and control both customer opinion and product information? The next wave taking omnichannel commerce to the next level will address information relevancy at every channel and all customer interactions – called Commerce Relevancy.

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Posted in Manufacturing, Master Data Management, PiM, Product Information Management, Retail, Uncategorized | Tagged , , , , , | Leave a comment

Sensational Find – $200 Million Hidden in a Teenager’s Bedroom!

That tag line got your attention – did it not?  Last week I talked about how companies are trying to squeeze more value out of their asset data (e.g. equipment of any kind) and the systems that house it.  I also highlighted the fact that IT departments in many companies with physical asset-heavy business models have tried (and often failed) to create a consistent view of asset data in a new ERP or data warehouse application.  These environments are neither equipped to deal with all life cycle aspects of asset information, nor are they fixing the root of the data problem in the sources, i.e. where the stuff is and what it look like. It is like a teenager whose parents have spent thousands of dollars on buying him the latest garments but he always wears the same three outfits because he cannot find the other ones in the pile he hoardes under her bed.  And now they bought him a smart phone to fix it.  So before you buy him the next black designer shirt, maybe it would be good to find out how many of the same designer shirts he already has, what state they are in and where they are.

Finding the asset in your teenager's mess

Finding the asset in your teenager’s mess

Recently, I had the chance to work on a like problem with a large overseas oil & gas company and a North American utility.  Both are by definition asset heavy, very conservative in their business practices, highly regulated, very much dependent on outside market forces such as the oil price and geographically very dispersed; and thus, by default a classic system integration spaghetti dish.

My challenge was to find out where the biggest opportunities were in terms of harnessing data for financial benefit.

The initial sense in oil & gas was that most of the financial opportunity hidden in asset data was in G&G (geophysical & geological) and the least on the retail side (lubricants and gas for sale at operated gas stations).  On the utility side, the go to area for opportunity appeared to be maintenance operations.  Let’s say that I was about right with these assertions but that there were a lot more skeletons in the closet with diamond rings on their fingers than I anticipated.

After talking extensively with a number of department heads in the oil company; starting with the IT folks running half of the 400 G&G applications, the ERP instances (turns out there were 5, not 1) and the data warehouses (3), I queried the people in charge of lubricant and crude plant operations, hydrocarbon trading, finance (tax, insurance, treasury) as well as supply chain, production management, land management and HSE (health, safety, environmental).

The net-net was that the production management people said that there is no issue as they already cleaned up the ERP instance around customer and asset (well) information. The supply chain folks also indicated that they have used another vendor’s MDM application to clean up their vendor data, which funnily enough was not put back into the procurement system responsible for ordering parts.  The data warehouse/BI team was comfortable that they cleaned up any information for supply chain, production and finance reports before dimension and fact tables were populated for any data marts.

All of this was pretty much a series of denial sessions on your 12-step road to recovery as the IT folks had very little interaction with the business to get any sense of how relevant, correct, timely and useful these actions are for the end consumer of the information.  They also had to run and adjust fixes every month or quarter as source systems changed, new legislation dictated adjustments and new executive guidelines were announced.

While every department tried to run semi-automated and monthly clean up jobs with scripts and some off-the-shelve software to fix their particular situation, the corporate (holding) company and any downstream consumers had no consistency to make sensible decisions on where and how to invest without throwing another legion of bodies (by now over 100 FTEs in total) at the same problem.

So at every stage of the data flow from sources to the ERP to the operational BI and lastly the finance BI environment, people repeated the same tasks: profile, understand, move, aggregate, enrich, format and load.

Despite the departmental clean-up efforts, areas like production operations did not know with certainty (even after their clean up) how many well heads and bores they had, where they were downhole and who changed a characteristic as mundane as the well name last and why (governance, location match).

Marketing (Trading) was surprisingly open about their issues.  They could not process incoming, anchored crude shipments into inventory or assess who the counterparty they sold to was owned by and what payment terms were appropriate given the credit or concentration risk associated (reference data, hierarchy mgmt.).  As a consequence, operating cash accuracy was low despite ongoing improvements in the process and thus, incurred opportunity cost.

Operational assets like rig equipment had excess insurance coverage (location, operational data linkage) and fines paid to local governments for incorrectly filing or not renewing work visas was not returned for up to two years incurring opportunity cost (employee reference data).

A big chunk of savings was locked up in unplanned NPT (non-production time) because inconsistent, incorrect well data triggered incorrect maintenance intervals. Similarly, OEM specific DCS (drill control system) component software was lacking a central reference data store, which did not trigger alerts before components failed. If you add on top a lack of linkage of data served by thousands of sensors via well logs and Pi historians and their ever changing roll-up for operations and finance, the resulting chaos is complete.

One approach we employed around NPT improvements was to take the revenue from production figure from their 10k and combine it with the industry benchmark related to number of NPT days per 100 day of production (typically about 30% across avg depth on & offshore types).  Then you overlay it with a benchmark (if they don’t know) how many of these NPT days were due to bad data, not equipment failure or alike, and just fix a portion of that, you are getting big numbers.

When I sat back and looked at all the potential it came to more than $200 million in savings over 5 years and this before any sensor data from rig equipment, like the myriad of siloed applications running within a drill control system, are integrated and leveraged via a Hadoop cluster to influence operational decisions like drill string configuration or asmyth.

Next time I’ll share some insight into the results of my most recent utility engagement but I would love to hear from you what your experience is in these two or other similar industries.

Disclaimer:
Recommendations contained in this post are estimates only and are based entirely upon information provided by the prospective customer  and on our observations.  While we believe our recommendations and estimates to be sound, the degree of success achieved by the prospective customer is dependent upon a variety of factors, many of which are not under Informatica’s control and nothing in this post shall be relied upon as representative of the degree of success that may, in fact, be realized and no warrantee or representation of success, either express or implied, is made.
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Posted in Application Retirement, B2B, Big Data, Business Impact / Benefits, Business/IT Collaboration, CIO, Data Aggregation, Data Governance, Data Integration, Data Quality, Enterprise Data Management, Governance, Risk and Compliance, Manufacturing, Master Data Management, Mergers and Acquisitions, Operational Efficiency, Uncategorized, Utilities & Energy, Vertical | Tagged , , , , , , , | Leave a comment