Category Archives: Business Impact / Benefits
On Saturday, I got a call from my broadband company on my mobile phone. The sales rep pitched a great limited-time offer for new customers. I asked him whether I could take advantage of this great offer as well, even though I am an existing customer. He was surprised. “Oh, you’re an existing customer,” he said, dismissively. “No, this offer doesn’t apply to you. It’s for new customers only. Sorry.” You can imagine my annoyance.
If this company had built a solid foundation of customer data, the sales rep would have had a customer profile rich with clean, consistent, and connected information as reference. If he had visibility into my total customer relationship with his company, he’d know that I’m a loyal customer with two current service subscriptions. He’d know that my husband and I have been customers for 10 years at our current address. On top of that, he’d know we both subscribed to their services while live at separate addresses before we were married.
Unfortunately, his company didn’t arm him with the great customer data he needs to be successful. If they had, he could have taken the opportunity to offer me one of the four services I currently don’t subscribe to—or even a bundle of services. And I could have shared a very different customer experience.
Every customer interaction counts
Executives at companies of all sizes talk about being customer-centric, but it’s difficult to execute on that vision if you don’t manage your customer data like a strategic asset. If delivering seamless, integrated, and consistent customer experiences across channels and touch points is one of your top priorities, every customer interaction counts. But without knowing exactly who your customers are, you cannot begin to deliver the types of experiences that retain existing customers, grow customer relationships and spend, and attract new customers.
How would you rate your current ability to identify your customers across lines of business, channels and touch points?
Many businesses, however, have anything but an integrated and connected customer-centric view—they have a siloed and fragmented channel-centric view. In fact, sales, marketing, and call center teams often identify siloed and fragmented customer data as key obstacles preventing them from delivering great customer experiences.
According to Retail Systems Research, creating a consistent customer experience remains the most valued capability for retailers, but 55 % of those surveyed indicated their biggest inhibitor was not having a single view of the customer across channels.
Retailers are not alone. An SVP of marketing at a mortgage company admitted in an Argyle CMO Journal article that, now that his team needs to deliver consistent customer experiences across channels and touch points, they realize they are not as customer-centric as they thought they were.
Customer complexity knows no bounds
The fact is, businesses are complicated, with customer information fragmented across divisions, business units, channels, and functions.
Citrix, for instance, is bringing together valuable customer information from 4 systems. At Hyatt Hotels & Resorts, it’s about 25 systems. At MetLife, it’s 70 systems.
How many applications and systems would you estimate contain valuable customer information at your company?
Based on our experience working with customers across many industries, we know the total customer relationship allows:
- Marketing to boost response rates by better segmenting their database of contacts for personalized marketing offers.
- Sales to more efficiently and effectively cross-sell and up-sell the most relevant offers.
- Customer service teams to resolve customers’ issues immediately, instead of placing them on hold to hunt for information in a separate system.
If your marketing, sales, and customer service teams are struggling with inaccurate, inconsistent, and disconnected customer information, it is costing your company revenue, growth, and success.
Transforming customer data into total customer relationships
Informatica’s Total Customer Relationship Solution fuels business and analytical applications with clean, consistent and connected customer information, giving your marketing, sales, e-commerce and call center teams access to that elusive total customer relationship. It not only brings all the pieces of fragmented customer information together in one place where it’s centrally managed on an ongoing basis, but also:
- Reconciles customer data: Your customer information should be the same across systems, but often isn’t. Assess its accuracy, fixing and completing it as needed—for instance, in my case merging duplicate profiles under “Jakki” and “Jacqueline.”
- Reveals valuable relationships between customers: Map critical connections—Are individuals members of the same household or influencer network? Are two companies part of the same corporate hierarchy? Even link customers to personal shoppers or insurance brokers or to sales people or channel partners.
- Tracks thorough customer histories: Identify customers’ preferred locations; channels, such as stores, e-commerce, and catalogs; or channel partners.
- Validates contact information: Ensure email addresses, phone numbers, and physical addresses are complete and accurate so invoices, offers, or messages actually reach customers.
This is just the beginning. From here, imagine enriching your customer profiles with third-party data. What types of information help you better understand, sell to, and serve your customers? What are your plans for incorporating social media insights into your customer profiles? What could you do with this additional customer information that you can’t do today?
We’ve helped hundreds of companies across numerous industries build a total customer relationship view. Merrill Lynch boosted marketing campaign effectiveness by 30 percent. Citrix boosted conversion rates by 20%. A $60 billion global manufacturer improved cross-sell and up-sell success by 5%. A hospitality company boosted cross-sell and up-sell success by 60%. And Logitech increased sales across channels, including their online site, retail stores, and distributors.
Informatica’s Total Customer Relationship Solution empowers your people with confidence, knowing that they have access to the kind of great customer data that allows them to surpass customer acquisition and retention goals by providing consistent, integrated, and seamless customer experiences across channels. The end result? Great experiences that customers are inspired to share with their family and friends at dinner parties and on social media.
Do you have a terrible customer experience or great customer experience to share? If so, please share them with us and readers using the Comment option below.
Improving Order to Cash matters regardless of market cycle
Order to Cash (OTC) matters to today’s CFOs and their financial teams even as CFOs move themselves from an expense and cost reduction footing to a manage growth footing. As the business process concerned with receiving and processing customer sales, having a well-functioning OTC process is not only about preserving cash, but it is also about improving the working capital delivered to the bottom line. This is something which is necessitated by successful growth strategies. Specifically, OTC helps to provide the cash flow needed to quicken collections and improve working capital turnover.
This drives concrete improvements to finance metrics including Days Sales Outstanding (a measure of the average number of days that a company takes to collect revenue after a sale has been made) and the overall cost of collections. It should be clear that a poorly running order to cash process can create tangible business issues. These include but are not limited to the following:
- Accuracy of purchase orders
- Accuracy of invoices
- Volume of customer disputes
- Incorrect application of payment terms
- Approval of inappropriate orders
- Errors in order fulfillment
CFOs tell us that it is critical that they make sure that “good cash management is occurring in compliance with regulation”. It is important as well to recognize that OTC cuts across many of the primary activities of the business value chain—especially those that related to sales, marketing, and services.
How do you improve your order to cash process?
So how do financial leader go about improving OTC? They can clearly start by looking at the entire OTC process from quote order, process order, fulfill order, invoice customer, receive and apply cash, and manage credit and collections. The below diagram shows the specific touch points where the process can be improved—each of these should be looked at for process or technology improvement.
However, the starting point is where the most concrete action can be taken. Fixing customer data fixes the data that is used by each succeeding process improvement area. This is where a single, connected view of customer can be established. This improves the OTC process by doing the following:
- Fixes your customer data
- Establishes the right relationships between customers
- Establishes tax and statutory registrations and credit limits
- Prevents penalties for delivering tax documents to the wrong placeCustomer Data Mastering (CDM) does this in the following way. It provides a single view of customers, 360 degree view of relationships as well as a complete view of integrative customer relationships including interactions and transactions.
CDM matters to the CFO and the Business as a whole
It turns out that CDM does not just matter to OTC and the finance organization. It matters as well to the corporate value chain by impacting the following primary activities including outbound logics, marketing and sales, and service. Specifically, CDM accomplishes the following:
- It reduces costs by reducing invoicing and billing inaccuracies, customer disputes, mailing unconsolidated statements, sending duplicate mail, and dealing with returned mail
- Increases revenue by boosting marketing effectiveness at segmenting customer for more personalized offers
- Increases revenue by boosting sales effectiveness by making more relevant cross-sell and up-sell offers
- Reduces costs by boosting call center effectiveness by resolving customer issues more quickly
- Improves customer satisfaction, customer loyalty and retention because employees are empowered with complete customer information to deliver great customer experiences across channels and touch points
So as we have discussed, today’s CFOs are finding that they need to become more and more growth oriented. This transition is made more effective with a well function OTC process. While OTC impacts other elements of the business too, the starting point for fixing OTC is customer data mastering because it fixes elements of the data portion of this process.
Original article is posted at techcrunch.com
It’s probably no surprise to the security professional community that once again, identity theft is among the IRS’s Dirty Dozen tax scams. Criminals use stolen Social Security numbers and other personally identifiable information to file tax claims illegally, deposit the tax refunds to rechargeable debit cards, and vanish before the average citizen gets around to filing.
Since the IRS began publishing its “Dirty Dozen” list to alert filers of the worst tax scams, identity theft has continually topped the list since 2011. In 2012, the IRS implemented a preventive measure to catch fraud prior to actually issuing refunds, and issued more than 2,400 enforcement actions against identity thieves. With an aggressive campaign to fight identity theft, the IRS saved over $1.4 billion in 2011 and over $63 billion since October 2014.
That’s great progress – but given that of the 117 million tax payers who filed electronically in 2014, 80 million received on average $2,851 directly deposited into their bank, which is more than $229 billion changing hands electronically. The pessimist in me has to believe that cyber criminals are already plotting how to nab more Social Security numbers and e-filing logins to tap into that big pot of gold.
So where are criminals getting the data to begin with? Any organization that has employees and a human resources department collects and possibly stores Social Security numbers, birthdays, addresses and income either on-premises or in a cloud HR application. This information is everything a criminal would need to fraudulently file taxes. Any time a common business process is digitally transformed, or moved to the cloud, the potential risk of exposure increases.
As the healthcare industry transforms to electronic health records and patient records, another abundant source of Social Security numbers and personally identifiable information increases the surface area of opportunity. When you look at the abundance of Social Security numbers stolen in major data breaches, such as the case with Anthem, you start to connect the dots.
One of my favorite dynamic infographics comes from the website Information is Beautiful entitled, ‘World’s Biggest Data Breaches.’ When you filter the data based on number of records versus sensitivity, the size of the bubbles indicate the severity. Even though the sensitivity score appears to be somewhat arbitrary, it does provide one way to assess the severity based on the type of information that was breached:
|Just email address/online information||1|
|Credit card information||300|
|Email password/health records||4000|
|Full bank account details||50000|
What would be an interesting addition is how many records were sold on the black market that resulted in tax or insurance fraud.
Cyber-security expert Brian Krebs, who was personally impacted by a criminal tax return filing last year, says we will likely see “more phony tax refund claims than last year.” With credentials for TurboTax and H&R Block marketed on black market websites for about 4 cents per identity, it is hard to disagree.
The Ponemon Institute published a survey last year, entitled The State of Data Centric Security. One research finding that sticks out is when security professionals were asked what keeps them up at night, and more than 50 percent said “not knowing where sensitive and confidential data reside.” As we enter full swing into tax season, what should security professionals be thinking about?
Data Security Intelligence promises to be the next big thing that provides a more automated and data-centric view into sensitive data discovery, classification and risk assessment. If you don’t know where the data is or its risk, how can you protect it? Maybe with a little more insight, we can at least reduce the surface area of exposed sensitive data.
An increasing number of companies around the world moving to cloud-first or hybrid architectures for new systems to process their data for new analytics applications. In addition to adding new data source from SaaS (Software as a Service) applications to their data pipelines, they are hosting some or all of their data storage, processing and analytics in IaaS (Infrastructure as a Service) public hosted environments to augment on-premise systems. In order to enable our customers to take advantage of the benefits of IaaS options, Informatica is embracing this computing model.
As announced today, Informatica now fully supports running the traditionally on-premise Informatica PowerCenter, Big Data Edition (BDE), Data Quality and Data Exchange on Amazon Web Services (AWS) Elastic Compute (EC2). This provides customers with added flexibility, agility and time-to-production by enabling a new deployment option for running Informatica software.
Existing and new Informatica customers can now choose to develop and/or deploy data integration, quality and data exchange in AWS EC2 just as they would on on-premise servers. There is no need for any special licensing as Informatica’s standard product licensing now covers deployment on AWS EC2 on the same operating systems as on-premise. BDE on AWS EC2 supports the same versions of Cloudera and Hortonworks Hadoop that are supported on-premise.
Customers can install these Informatica products on AWS EC2 instances just as they would on servers running on an on-premise infrastructure. The same award winning Informatica Global Customer Service that thousands of Informatica customers use is now available on call and standing by to help with success on AWS EC2. Informatica Professional Services is also available to assist customers running these products on AWS EC2 as they are for on-premise system configurations.
Informatica customers can accelerate their time to production or experimentation with the added flexibility of installing Informatica products on AWS EC2 without having to wait for new servers to arrive. There is the flexibility to develop in the cloud and deploy production systems on-premise or develop on-premise and deploy production systems in AWS. Cloud-first companies can keep it all in the cloud by both developing and going into production on AWS EC2.
Customers can also benefit from the lower up-front costs, maintenance costs and pay-as-you-go infrastructure pricing of AWS. Instead of having to pay upfront for servers and managing them in an on-premise data center, customers can use virtual servers in AWS to run Informatica products on. Customers can use existing Informatica licenses or purchase them in the standard way from Informatica for use on top of AWS EC2.
Combined with the ease of use of Informatica Cloud, Informatica now offers customers looking for hybrid and cloud solutions even more options.
Read the press release including supporting quotes from AWS and Informatica customer ProQuest, here.
At the recent Bosch Connected World conference in Berlin, Stefan Bungart, Software Leader Europe at GE, presented a very interesting keynote, “How Data Eats the World”—which I assume refers to Marc Andreesen’s statement that “Software eats the world”. One of the key points he addressed in his keynote was the importance of generating actionable insight from Big Data, securely and in real-time at every level, from local to global and at an industrial scale will be the key to survival. Companies that do not invest in DATA now, will eventually end up like consumer companies which missed the Internet: It will be too late.
As software and the value of data are becoming a larger part of the business value chain, the lines between different industries become more vague, or as GE’s Chairman and CEO Jeff Immelt once stated: “If you went to bed last night as an industrial company, you’re going to wake up today as a software and analytics company.” This is not only true for an industrial company, but for many companies that produce “things”: cars, jet-engines, boats, trains, lawn-mowers, tooth-brushes, nut-runners, computers, network-equipment, etc. GE, Bosch, Technicolor and Cisco are just a few of the industrial companies that offer an Internet of Things (IoT) platform. By offering the IoT platform, they enter domains of companies such as Amazon (AWS), Google, etc. As Google and Apple are moving into new areas such as manufacturing cars and watches and offering insurance, the industry-lines are becoming blurred and service becomes the key differentiator. The best service offerings will be contingent upon the best analytics and the best analytics require a complete and reliable data-platform. Only companies that can leverage data will be able to compete and thrive in the future.
The idea of this “servitization” is that instead of selling assets, companies offer service that utilizes those assets. For example, Siemens offers a service for body-scans to hospitals instead of selling the MRI scanner, Philips sells lightning services to cities and large companies, not the light bulbs. These business models enable suppliers to minimize disruption and repairs as this will cost them money. Also, it is more attractive to have as much functionality of devices in software so that upgrades or adjustments can be done without replacing physical components. This is made possible by the fact that all devices are connected, generate data and can be monitored and managed from another location. The data is used to analyse functionality, power consumption, usage , but also can be utilised to predict malfunction, proactive maintenance planning, etc.
So what impact does this have on data and on IT? First of all, the volumes are immense. Whereas the total global volume of for example Twitter messages is around 150GB, ONE gas-turbine with around 200 sensors generates close to 600GB per day! But according to IDC only 3% of potentially useful data is tagged and less than 1% is currently analysed. Secondly, the structure of the data is now always straightforward and even a similar device is producing different content (messages) as it can be on a different software level. This has impact on the backend processing and reliability of the analysis of the data.
Also the data often needs to put into context with other master data from thea, locations or customers for real-time decision making. This is a non-trivial task. Next, Governance is an aspect that needs top-level support. Questions like: Who owns the data? Who may see/use the data? What data needs to be kept or archived and for how long? What needs to be answered and governed in IoT projects with the same priorities as the data in the more traditional applications.
To summarize, managing data and mastering data governance is becoming one of the most important pillars of companies that lead the digital age. Companies that fail to do so will be at risk for becoming a new Blockbuster or Kodak: companies that didn’t adopt quickly enough. In order to avoid this, companies need to evaluate a data platform can support a comprehensive data strategy which encapsulates scalability, quality, governance, security, ease of use and flexibility, and that enables them to choose the most appropriate data processing infrastructure, whether that is on premise or in the cloud, or most likely a hybrid combination of these.
Enterprise IT is in a state of constant evolution. As a result, business processes and technologies become increasingly more difficult to change and more costly to keep up-to-date. The solution to this predicament is an Enterprise Architecture (EA) process that can provide a framework for an optimized IT portfolio. IT Optimization strategy should be based on a comprehensive set of architectural principles which ensure consistency and make IT more responsive, efficient, and economical.
The rationalization, standardization, and consolidation process helps organizations understand their current EA maturity level and move forward on the appropriate roadmap. As they undertake the IT Optimization journey, the IT architecture matures through several stages, leveraging IT Optimization Architecture Principles to attain each level of maturity.
Level 1: The first step involves helping a company develop its architecture vision and operating model, with attention to cost, globalization, investiture, or whatever is driving the company strategically. Once that vision is in place, enterprise architects can guide the organization through an iterative process of rationalization, consolidation, and eventually shared-services and cloud computing.
Level 2: The rationalization exercise helps an organization identify what standards to move towards as they eliminate the complexities and silos they have built up over the years, along with the specific technologies that will help them get there.
Depending on the company, Rationalization could start with a technical discussion and be IT-driven; or it could start at a business level. For example, a company might have distributed operations across the globe and desire to consolidate and standardize its business processes. That could drive change in the IT portfolio. Or a company that has gone through mergers and acquisitions might have redundant business processes to rationalize.
Rationalizing involves understanding the current state of an organization’s IT portfolio and business processes, and then mapping business capabilities to IT capabilities. This is done by developing scoring criteria to analyze the current portfolio, and ultimately by deciding on the standards that will propel the organization forward. Standards are the outcome of a rationalization exercise.
Standardized technology represents the second level of EA maturity. Organizations at this level have evolved beyond isolated independent silos. They have well-defined corporate governance and procurement policies, which yields measurable cost savings through reduced software licenses and the elimination of redundant systems and skill sets.
Level 3: Consolidation entails reducing the footprint of your IT portfolio. That could involve consolidating the number of database servers, application servers and storage devices, consolidating redundant security platforms, or adopting virtualization, grid computing, and related consolidation initiatives.
Consolidation may be a by-product of another technology transformation, or it may be the driver of these transformations. But whatever motivates the change, the key is to be in alignment with the overall business strategy. Enterprise architects understand where the business is going so they can pick the appropriate consolidation strategy.
Level 4: One of the key outcomes of a rationalization and consolidation exercise is the creation of a strategic roadmap that continually keeps IT in line with where the business is going.
Having a roadmap is especially important when you move down the path to shared services and cloud computing. For a company that has a very complex IT infrastructure and application portfolio, having a strategic roadmap helps the organization to move forward incrementally, minimizing risk, and giving the IT department every opportunity to deliver value to the business.
March 20th 2015 was the official start of spring and to be honest, it couldn’t have come soon enough for us folks in the North East. After a long, cold and snowy winter we’re looking forward to the spring thaw and the first green shoots of burgeoning life. Spring is also the time that we like to tackle new projects and start afresh after our winter hibernation.
For those of us in technology new spring projects often reflect the things we do in everyday life. Naturally our mind turns at this time to spring cleaning and spring training. To be honest, we’d have to admit that we haven’t scrubbed our data in three months so data cleansing is a must, but so too is training. We probably haven’t picked up a book or attended a seminar since last November. But what training should we do? And “what should we do next?”
Luckily, Informatica is providing the answer. We’ve put together two free, half day training seminars for cloud application owners and Salesforce practitioners. That’s two dates, two fantastic locations and dozens of brilliant speakers lined up to give you some new pointers for what’s coming next in the world of cloud and SaaS.
The goals of the event are to give you the tools and knowledge to strengthen your Salesforce implementation and help you delight your customers. The sessions will include presentations by experts from Salesforce and our partner Bluewolf. There will also be some best practices presentations and demonstrations from Informatica’s team of very talented engineers.
Just glance at the seminar summary and you’ll see what we mean:
Session 1: Understand the Opportunity of Every Customer Interaction
In this session Eric Berridge, Co-founder and CEO of Bluewolf Inc. will discuss how you can develop a customer obsessed culture and get the most value from every customer interaction.
Session 2: Delight Your Customers by Taking Your Salesforce Implementation to the Next Level
Ajay Gandhi, Informatica’s VP Product Marketing is next up and he’s going to provide a fabulous session on what you look out for, and where should you invest as your Salesforce footprint grows.
Session 3: Anticipate Your Business Needs With a Fresh Approach to Customer Analytics
The seminar wraps up with Benjamin Pruden, Sr. Manager Product Marketing, at Salesforce. Ben’s exciting session touches on one of the hottest topics in the industry today. He’s going to explain how you can obtain a comprehensive understanding of your most valuable customers with cloud-analytics and data-driven dashboards.
I’m sure you’ll agree that it’s a pretty impressive seminar and well worth a couple of hours of your time.
The New York event is happening at Convene (810 Seventh Ave, 52nd and 53rd ) on April 7th. Click here for more details and to reserve your seat.
The San Francisco event is a week later on April 14th at Hotel Nikko (222 Mason Street). Make sure you click here and register today.
Come join us on the 7th or the 14th to learn how to take your cloud business to the next level. Oh, and don’t forget that you’ll also be treating yourself to some well-deserved spring training!
The emergence of the business cloud is making the need for data ever more prevalent. Whatever your business, if your role is in the sales, marketing or service departments, chances are your productivity depends a great deal on the ability to move data quickly in and out of Salesforce and its ecosphere of applications.
With the in-built data transformation intelligence, the Data Wizard (click here to try the Beta version), changes the landscape of what traditional data loaders can do. The Data Wizard takes care of the following aspects, so that you don’t have to:
- Data Transformations: We built in over 300 standard data transformations so you don’t have to format the data before bringing it in (eg. combining first and last names into full names, adding numeric columns for totals, splitting address fields into its separate components).
- Built-in intelligence: We automate the mapping of data into Salesforce for a range of common use cases (eg., Automatically mapping matching fields, intelligently auto-generating date format conversions , concatenating multiple fields).
- App-to-app integration: We incorporated pre-built integration templates to encapsulate the logic required for integrating Salesforce with other applications (eg., single click update of customer addresses in a Cloud ERP application based on Account addresses in Salesforce) .
Unlike the other data loading apps out there, the Data Wizard doesn’t presuppose any technical ability on the part of the user. It was purpose-built to solve the needs of every type of user, from the Salesforce administrator to the business analyst.
Despite the simplicity the Data Wizard offers, it is built on the robust Informatica Cloud integration platform, providing the same reliability and performance that is key to the success of Informatica Cloud’s enterprise customers, who integrate over 5 billion rows of data per day. We invite you to try the Data Wizard for free, and contribute to the Beta process by providing us with your feedback.
For those hoping to push through a hard-hitting analytics effort that will serve as a beacon of light within an otherwise calcified organization, there’s probably a lot of work cut out for you. Evolving into an organization that fully grasps the power and opportunities of data analytics requires cultural change, and this is a challenge organizations have only begin to grasp.
“Sitting down with pizza and coffee could get you around can get around most of the technical challenges,” explained Sam Ransbotham, Ph.D, associate professor Boston College, at a recent panel webcast hosted by MIT Sloan Management Review, “but the cultural problems are much larger.”
That’s one of the key takeaways from a the panel, in which Ransbotham was joined by Tuck Rickards, head of digital transformation practice at Russell Reynolds Associates, a digital recruiting firm, and Denis Arnaud, senior data scientist Amadeus Travel Intelligence. The panel, which examined the impact of corporate culture on data analytics, was led by Michael Fitzgerald, contributing editor at MIT Sloan Management Review.
The path to becoming an analytics-driven company is a journey that requires transformation across most or all departments, the panelists agreed. “It’s fundamentally different to be a data-driven decision company than kind of a gut-feel decision-making company,” said Rickards. “Acquiring this capability to do things differently usually requires a massive culture shift.”
That’s because the cultural aspects of the organization – “the values, the behaviors, the decision making norms and the outcomes go hand in hand with data analytics,” said Ransbotham. “It doesn’t do any good to have a whole bunch of data processes if your company doesn’t have the culture to act on them and do something with them.” Rickards adds that bringing this all together requires an agile, open source mindset, with frequent, open communication across the organization.
So how does one go about building and promoting a culture that is conducive to getting the maximum benefit from data analytics? The most important piece is being about people who ate aware and skilled in analytics – both from within the enterprise and from outside, the panelists urged. Ransbotham points out that it may seem daunting, but it’s not. “This is not some gee-whizz thing,” he said. “We have to get rid of this mindset that these things are impossible. Everybody who has figured it out has figured it out somehow. We’re a lot more able to pick up on these things that we think — the technology is getting easier, it doesn’t require quite as much as it used to.”
The key to evolving corporate culture to becoming more analytics-driven is to identify or recruit enlightened and skilled individuals who can provide the vision and build a collaborative environment. “The most challenging part is looking for someone who can see the business more broadly, and can interface with the various business functions –ideally, someone who can manage change and transformation throughout the organization,” Rickards said.
Arnaud described how his organization – an online travel service — went about building an espirit de corps between data analytics staff and business staff to ensure the success of their company’s analytics efforts. “Every month all the teams would do a hands-on workshop, together in some place in Europe [Amadeus is headquartered in Madrid, Spain].” For example, a workshop may focus on a market analysis for a specific customer, and the participants would explore the entire end-to-end process for working with the customer, “from the data collection all the way through to data acquisition through data crunching and so on. The one knowing the data analysis techniques would explain them, and the one knowing the business would explain that, and so on.” As a result of these monthly workshops, business and analytics teams members have found it “much easier to collaborate,” he added.
Web-oriented companies such as Amadeus – or Amazon and eBay for that matter — may be paving the way with analytics-driven operations, but companies in most other industries are not at this stage yet, both Rickards and Ransbotham point out. The more advanced web companies have built “an end-to-end supply chain, wrapped around customer interaction,” said Rickards. “If you think of most traditional businesses, financial services or automotive or healthcare are a million miles away from that. It starts with having analytic capabilities, but it’s a real journey to take that capability across the company.”
The analytics-driven business of the near future – regardless of industry – will likely to be staffed with roles not seen as of yet today. “If you are looking to re-architect the business, you may be imagining roles that you don’t have in the company today,” said Rickards. Along with the need for chief analytics officers, data scientists, and data analysts, there will be many new roles created. “If you are on the analytics side of this, you can be in an analytics group or a marketing group, with more of a CRM or customer insights title. Yu can be in a planning or business functions. In a similar way on the technology side, there are people very focused on architecture and security.”
Ultimately, the demand will be for leaders and professionals who understand both the business and technology sides of the opportunity, Rickards continued. Ultimately, he added, “you can have good people building a platform, and you can have good data scientists. But you better have someone on the top of that organization knowing the business purpose.’
I live in a small town in Maine. Between my town and the surrounding three towns, there are seven Main Streets and three Annis Roads or Lanes (and don’t get me started on the number of Moose Trails). If your insurance company wants to market to or communicate with someone in my town or one of the surrounding towns, how can you ensure that the address that you are sending material to is correct? What is the cost if material is sent to an incorrect or outdated address? What is the cost to your insurance company if a provider sends the bill out to the wrong ?
How much is poor address quality costing your business? It doesn’t just impact marketing where inaccurate address data translates into missed opportunity – it also means significant waste in materials, labor, time and postage . Bills may be delivered late or returned with sender unknown, meaning additional handling times, possible repackaging, additional postage costs (Address Correction Penalties) and the risk of customer service issues. When mail or packages don’t arrive, pressure on your customer support team can increase and your company’s reputation can be negatively impacted. Bills and payments may arrive late or not at all directly impacting your cash flow. The cost of bad address data causes inefficiencies and raises costs across your entire organization.
The best method for handling address correction is through a validation and correction process:
When trying to standardize member or provider information one of the first places to look is address data. If you can determine that John Q Smith that lives at 134 Main St in Northport, Maine 04843 is the same John Q Smith that lives at 134 Maine Street in Lincolnville, Maine 04849, you have provided a link between two members that are probably considered distinct in your systems. Once you can validate that there is no 134 Main St in Northport according to the postal service, and then can validate that 04849 is a valid zip code for Lincolnville – you can then standardize your address format to something along the lines of: 134 MAIN ST LINCOLNVILLE,ME 04849. Now you have a consistent layout for all of your addresses that follows postal service standards. Each member now has a consistent address which is going to make the next step of creating a golden record for each member that much simpler.
Think about your current method of managing addresses. Likely, there are several different systems that capture addresses with different standards for what data is allowed into each field – and quite possibly these independent applications are not checking or validating against country postal standards. By improving the quality of address data, you are one step closer to creating high quality data that can provide the up-to-the minute accurate reporting your organization needs to succeed.