Tag Archives: MDM
The Surprising Link Between Hurricanes and Strawberry Pop-Tarts: Brought to you by Clean, Consistent and Connected Data
What do you think Wal-Mart’s best-seller is right before a hurricane? If you guessed water like I did, you’d be wrong. According to this New York Times article, “What Wal-Mart Knows About Customers’ Habits” the retailer sells 7X more strawberry Pop-Tarts in Florida right before a hurricane than any other time. Armed with predictive analytics and a solid information management foundation, the team stocks up on strawberry Pop-Tarts to make sure they have enough supply to meet demand.
I learned this fun fact from Andrew Donaher, Director of Information Management Strategy at Groundswell Group, a consulting firm based in western Canada that specializes in information management services. In this interview, Andy and I discuss how IT leaders can increase the value of data to drive business value, explain how some IT leaders are collaborating with business leaders to improve predictive analytics, and share advice about how to talk to business leaders, such as the CFO about investing in an information management strategy.
Q. Andy, what can IT leaders do to increase the value of data to drive business value?
A. Simply put, each business leader in a company needs to focus on achieving their goals. The first step IT leaders should take is to engage with each business leader to understand their long and short-term goals and ask some key questions, such as:
- What type of information is critical to achieving their goals?
- Do they have the information they need to make the next decision or take the next best action?
- Is all the data they need in house? If not, where is it?
- What challenges are they facing when it comes to their data?
- How much time are people spending trying to pull together the information they need?
- How much time are people spending fixing bad data?
- How much is this costing them?
- What opportunities exist if they had all the information they need and could trust it?
Q. How are IT leaders collaborating with business partners to improve predictive analytics?
A. Wal-Mart’s IT team collaborated with the business to improve the forecasting and demand planning process. Once they found out what was important, IT figured out how to gather, store and seamlessly integrate external data like historical weather and future weather forecasts into the process. This enabled the business to get more valuable insights, tailor product selections at particular stores, and generate more revenue.
Q. Why is it difficult for IT leaders to convince business leaders to invest in an information management strategy?
A. In most cases, business leaders don’t see the value in an information management strategy or they haven’t seen value before. Unfortunately this often happens because IT isn’t able to connect the dots between the information management strategy and the outcomes that matter to the business.
Business leaders see value in having control over their business-critical information, being able to access it quickly and to allocate their resources to get any additional information they need. Relinquishing control takes a lot of trust. When IT leaders want to get buy-in from business leaders to invest in an information management strategy they need to be clear about how it will impact business priorities. Data integration, data quality and master data management (MDM) should be built into the budget for predictive or advanced analytics initiatives to ensure the data the business is relying on is clean, consistent and connected.
Q: You liked this quotation from an IT leader at a beer manufacturing company, “We don’t just make beer. We make beer and data. We need to manage our product supply chain and information supply chain equally efficiently.”
A.What I like about that quote is the IT leader was able to connect the dots between the primary revenue generator for the company and the role data plays in improving organizational performance. That’s something that a lot of IT leaders struggle with. IT leaders should always be thinking about what’s the next thing they can do to increase business value with the data they have in house and other data that the company may not yet be tapping into.
Q. According to a recent survey by Gartner and the Financial Executives Research Foundation, 60% of Chief Financial Officers (CFOs) are investing in analytics and improved decision-making as their #1 IT priority. What’s your advice for IT Leaders who need to get buy-in from the CFO to invest in information management?
A. Read your company’s financial statements, especially the Management Discussion and Analysis section. You’ll learn about the company’s direction, what the stakeholders are looking for, and what the CFO needs to deliver. Offer to get your CFO the information s/he needs to make decisions and to deliver. When you talk to a CFO about investing in information management, focus on the two things that matter most:
- Risk mitigation: CFOs know that bad decisions based on bad information can negatively impact revenue, expenses and market value. If you have to caveat all your decisions because you can’t trust the information, or it isn’t current, then you have problems. CFOs need to trust their information. They need to feel confident they can use it to make important financial decisions and deliver accurate reports for compliance.
- Opportunity: Once you have mitigated the risk and can trust the data, you can take advantage of predictive analytics. Wal-Mart doesn’t just do forecasting and demand planning. They do “demand shaping.” They use accurate, consistent and connected data to plan events and promotions not just to drive inventory turns, but to optimize inventory and the supply chain process. Some companies in the energy market are using accurate, consistent and connected data for predictive asset maintenance. By preventing unplanned maintenance they are saving millions of dollars, protecting revenue streams, and gaining health and safety benefits.
To do either of these things you need a solid information management plan to manage clean, consistent and connected information. It takes a commitment but the pays offs can be very significant.
Q. What are the top three business requirements when building an information management and integration strategy?
A: In my experience, IT leaders should focus on:
- Business value: A solid information management and integration strategy that has a chance of getting funded must be focused on delivering business value. Otherwise, your strategy will lack clarity and won’t drive priorities. If you focus on business value, it will be much easier to gain organizational buy-in. Get that dollar figure before you start anything. Whether it is risk mitigation, time savings, revenue generation or cost savings, you need to calculate that value to the business and get their buy-in.
- Trust: When people know they can trust the information they are getting it liberates them to explore new ideas and not have to worry about issues in the data itself.
- Flexibility: Flexibility should be banked right into the strategy. Business drivers will evolve and change. You must be able to adapt to change. One of the most neglected, and I would argue most important, parts of a solid strategy is the ability to make continuous small improvements that may require more effort than a typical maintenance event, but don’t create long delays. This will be very much appreciated by the business. We work with our clients to ensure that this is addressed.
Beyond our wildest expectations—not to mention our original room reservations—the Third MDM Day event on February 19th was a tremendous success, a “three-peat” if you will. Expecting 100 attendees, we had nearly 500 registrations and a crowd of 350 who braved the weather, including a quarter of whom traveled from outside the tri-state area, to join us in New York City for a wall-to-wall day of MDM discussion and presentations.
I have the pleasure of boasting that Informatica was positioned as a leader on the latest Forrester Wave™ Report covering MDM Solutions. We are so pleased in fact, that we want to share the report with you – for free.
Click on the link below to receive a free copy of the full Forrester Research report, The Forrester Wave™: Master Data Management Solutions, Q1 2014.
The report used a combination of four data sources to assess the strengths and weaknesses of selected solutions:
- Hands-on lab evaluations
- Vendor surveys
- Product demos
- Customer reference calls
The vendors were chosen based on product fit, customer success and Forrester client demand. The report evaluated vendors on 65 criteria which were grouped in three high-level categories – current offering, strategy and market presence.
Informatica was noted for our strength in mastering and integrating data. The report noted that we “define the master domain across the data ecosystem.” In their interviews with customers, Forrester reported, “Customers purchasing Informatica MDM are often looking for an out-of-the-box solution to solve particularly complex business challenges impacted by master data.” They noted that Informatica’s specialization “helps customers link master data management to business outcomes.”
As a service provider, we were particularly pleased with the results of Forrester’s calls with our clients. After all, the proof of a truly superior product is in its day-to-day, real-world operation. The reports states, “Informatica continues to compete and increasingly closes sales in head-to-head reviews. Clients state its strengths are configurability, scalability, performance, and understanding of the business impact.”
But please, read it for yourself! We want to share this good news by offering a free copy of the Forrester Wave™ Report, Q1 2014. We have built a great team here at Informatica and we proudly believe that the study results support our approach and performance.
Want to see why Informatica is riding high about the results? Click here.
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.
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?
“Opportunity for the large community to share experiences, lessons learnt, and help those that are starting the MDM journey get on the right track.”
Next month, Informatica will host its third MDM Day conference. Our past two events in Las Vegas and London have been huge successes thanks to the active participation of our customers, partners, and colleagues. The conference is structured to provide opportunities for you to share your ideas, provide guidance to our product management team, and learn from other customers’ MDM and PIM journeys.
When: February 12th, 8:30 AM – 5:00 PM
Where: Westin Times Square
How: Register Here
I recently had a lengthy conversation with a business executive of a European telco. His biggest concern was to not only understand the motivations and related characteristics of consumers but to accomplish this insight much faster than before. Given available resources and current priorities this is something unattainable for many operators.
Unlike a few years ago – remember the time before iPad – his organization today is awash with data points from millions of devices, hundreds of device types and many applications.
One way for him to understand consumer motivation; and therefore intentions, is to get a better view of a user’s network and all related interactions and transactions. This includes his family household, friends and business network (also a type of household). The purpose of householding is to capture social and commercial relationships in a grouping of individuals (or businesses or both mixed together) in order to identify patterns (context), which can be exploited to better serve a customer a new individual product or bundle upsell, to push relevant apps, audio and video content.
Let’s add another layer of complexity by understanding not only who a subscriber is, who he knows and how often he interacts with these contacts and the services he has access to via one or more devices but also where he physically is at the moment he interacts. You may also combine this with customer service and (summarized) network performance data to understand who is high-value, high-overhead and/or high in customer experience. Most importantly, you will also be able to assess who will do what next and why.
Some of you may be thinking “Oh gosh, the next NSA program in the making”. Well, it may sound like it but the reality is that this data is out there today, available and interpretable if cleaned up, structured and linked and served in real time. Not only do data quality, ETL, analytical and master data systems provide the data backbone for this reality but process-based systems dealing with the systematic real-time engagement of consumers are the tool to make it actionable. If you add some sort of privacy rules using database or application-level masking technologies, most of us would feel more comfortable about this proposition.
This may feel like a massive project but as many things in IT life; it depends on how you scope it. I am a big fan of incremental mastering of increasingly more attributes of certain customer segments, business units, geographies, where lessons learnt can be replicated over and over to scale. Moreover, I am a big fan of figuring out what you are trying to achieve before even attempting to tackle it.
The beauty behind a “small” data backbone – more about “small data” in a future post – is that if a certain concept does not pan out in terms of effort or result, you have just wasted a small pile of cash instead of the $2 million for a complete throw-away. For example: if you initially decided that the central lynch pin in your household hub & spoke is the person, who owns the most contracts with you rather than the person who pays the bills every month or who has the largest average monthly bill, moving to an alternative perspective does not impact all services, all departments and all clients. Nevertheless, the role of each user in the network must be defined over time to achieve context, i.e. who is a contract signee, who is a payer, who is a user, who is an influencer, who is an employer, etc.
Why is this important to a business? It is because without the knowledge of who consumes, who pays for and who influences the purchase/change of a service/product, how can one create the right offers and target them to the right individual.
However, in order to make this initial call about household definition and scope or look at the options available and sensible, you have to look at social and cultural conventions, what you are trying to accomplish commercially and your current data set’s ability to achieve anything without a massive enrichment program. A couple of years ago, at a Middle Eastern operator, it was very clear that the local patriarchal society dictated that the center of this hub and spoke model was the oldest, non-retired male in the household, as all contracts down to children of cousins would typically run under his name. The goal was to capture extended family relationships more accurately and completely in order to create and sell new family-type bundles for greater market penetration and maximize usage given new bandwidth capacity.
As a parallel track aside from further rollout to other departments, customer segments and geos, you may also want to start thinking like another European operator I engaged a couple of years ago. They were trying to outsource some data validation and enrichment to their subscribers, which allowed for a more accurate and timely capture of changes, often life-style changes (moves, marriages, new job). The operator could then offer new bundles and roaming upsells. As a side effect, it also created a sense of empowerment and engagement in the client base.
I see bits and pieces of some of this being used when I switch on my home communication systems running broadband signal through my X-Box or set-top box into my TV using Netflix and Hulu and gaming. Moreover, a US cable operator actively promotes a “moving” package to help make sure you do not miss a single minute of entertainment when relocating.
Every time now I switch on my TV, I get content suggested to me. If telecommunication services would now be a bit more competitive in the US (an odd thing to say in every respect) and prices would come down to European levels, I would actually take advantage of the offer. And then there is the log-on pop up asking me to subscribe (or throubleshoot) a channel I have already subscribed to. Wonder who or what automated process switched that flag.
Ultimately, there cannot be a good customer experience without understanding customer intentions. I would love to hear stories from other practitioners on what they have seen in such respect
Gartner Estimates Growth for MDM Market and Positions Informatica as a Leader in The Magic Quadrant for Customer Data Solutions
Over the last few weeks I’ve been saying that the incredible popularity of our MDM-related events is a sign that MDM is a vital and growing market. Now I consider it reassuring that analysts agree. It’s also reassuring to see Informatica positioned as a Leader in the Magic Quadrant for Master Data Management of Customer Data Solutions, a position that Informatica has held for four years in a row.
In Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, analysts Bill O’Kane and Saul Judah estimates that the total software revenue for packaged MDM solutions was $1.6B in 2012, an increase of 7.8% from 2011, as compared with a 4.7% rise for the overall enterprise software market. Further, O’Kane and Judah estimate that the MDM of customer data solutions market segment was worth $527M in 2012, an increase of 5.4% from 2011. The analysts go on to say that the customer MDM market is far from mature, and that just 40% of the organizations surveyed by Gartner were beginning MDM initiatives.
One of MDM’s most important benefits is a single view of the customer across company departments and siloed systems. In this Magic Quadrant report, the analysts describe some of the business drivers for obtaining this view. For the banking and life sciences sectors, the analysts include “Compliance and risk management drivers, such as ‘know your customer,’ anti-money laundering and counterparty risk management in the banking sector, and Sunshine Act compliance in the life sciences sector.” I believe that many other industries could similarly benefit from trusted customer interactions. Another set of drivers they list are “cost optimization and efficiency drivers,” and finally, “revenue and profitability growth drivers,” explaining that examples of such drivers include “initiatives to improve cross-selling, upselling, and retention.”
Finally, the analysts observed a trend which we believe supports Informatica’s view of the importance of all-encompassing MDM solutions that can manage master data across enterprise. As noted in the report, “Many organizations have now invested in creating a new central system to master their customer data, with the majority (an estimated 80%) of organizations buying packaged MDM of customer data solutions, as opposed to building the capability themselves.”
To learn more about Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, see our press release or download the full report. After reading the report, please share your thoughts below.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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/).
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.
Do you know what year the first steam engine locomotive was invented? 1804. It traveled 9 miles in two hours. Now, you and I would be pretty upset of we boarded a train and it took 2 hours to go 9 miles. But, 200 years ago, this was a huge innovation and led to the invention of the modern day train and railway.
Tremendous Growth In Demand for Rail Travel Puts Pressure on Rail Infrastructure
Today, Britain is experiencing tremendous growth in demand for rail travel. One million more trains and 500 million more passengers travel by train than just 5 years ago. Over the next 30 years passenger demand for rail will more than double and freight demand is expected to go up by 140%. This puts tremendous pressure on the rail infrastructure.
Network Rail is in the modern-day rail business. Employees work day and night running, maintaining and updating Britain’s rail infrastructure, including millions of assets, such as 22,000 miles of track, 6,500 crossings, 43,000 bridges, viaducts and tunnels. Improving the rail network provides faster, more frequent and more reliable journeys between Britain’s towns and cities.
Network Rail is investing more in the rail infrastructure than in Victorian times. In the last six months, they spent about $25 million a day! In a recent news release, Patrick Bucher, group finance director said, “We continue to invest record amounts to deliver a bigger, better railway for passengers and businesses across Britain. We are also driving down the cost of running Britain’s railway to help make it more affordable in the years ahead.”
Employees Need to Trust Asset Information to Pinpoint and Fix Problems Quickly
To pinpoint and fix problems quickly, keep their operating costs low and maintain a strong safety record, Network Rail’s employees need to trust their mission-critical asset information, such as:
- What is the problem?
- Where is it?
- What equipment, tools and skills are needed to fix it?
- Who is closest to the problem that could fix it?
Difficult to Make Sense of Asset Information Scattered across Applications
Similar to many companies their size, Network Rail’s mission-critical asset information was scattered across many applications, which made it difficult for employees to make sense of asset information and the interaction between assets.
The asset information team recognized the limitations of employees depending on an application-centric view of their business. To operate more efficiently and effectively, they needed clean asset information, consistent asset information, and connected asset information.
Investing in Rail Infrastructure AND the Information Infrastructure to Support It
Network Rail now uses a combination of data integration, data quality, and master data management (MDM) to manage their mission-critical asset information in a central location on an ongoing basis, to:
- make sense of asset information,
- understand the relationships between assets, and
- track changes to asset information.
In a news release, Patrick Bossert Director of Network Rail’s Asset Information services business said, “With more accurate and reliable information about assets and their condition our team can make better business decisions, enable innovation in our asset management policy, planning and execution, and improve rail-system-wide investment decisions that benefit the rail industry as a whole.”
If you work for a company that revolves around mission-critical asset information, ask yourself these questions:
- Can our employees makes sense of our asset information?
- Can they easily see relationships between assets and how they interact?
- Can they see the history of changes to asset information over time?
Or are are they limited by an application-centric view of the business because asset information is scattered across in multiple systems?
Have a similar story about how you are managing your mission-critical asset information? Please share it in the comments below.