Category Archives: Customer Services
In our house when we paint a room, my husband does the big rolling of the walls or ceiling, I do the cut-in work. I am good at prepping the room, taping all the trim and deliberately painting the corners. However, I am thrifty and constantly concerned that we won’t have enough paint to finish a room. My husband isn’t afraid to use enough paint and is extremely efficient at painting a wall in a single even coat. As a result, I don’t do the big rolling and he doesn’t do the cutting in. It took us awhile to figure this out, and a few rooms had to be repainted while we were figuring it out. Now we know what we are good at, and what we need help with.
Payers roles are changing. Payers were previously focused on risk assessment, setting and collecting premiums, analyzing claims and making payments – all while optimizing revenues. Payers are pretty good at selling to employers, figuring out the cost/benefit ratio from an employers perspective and ensuring a good, profitable product. With the advent of the Affordable Healthcare Act along with a much more transient insured population, payers now must focus more on the individual insured and be able to communicate with the individuals in a more nimble manner than in the past.
Individual members will shop for insurance based on consumer feedback and price. They are interested in ease of enrollment and the ability to submit and substantiate claims quickly and intuitively. Payers are discovering that they need to help manage population health at a individual member level. And population health management requires less of a business-data analytics approach and more social media and gaming-style logic to understand patients. In this way, payers can help develop interventions to sustain behavioral changes for better health.
When designing such analytics, payers should consider the following key design steps:
- Extend data warehouses to an analytics appliance
- Invest in a big data platform to absorb patients’ social data
- Build predictive analytics for patient behavior
- Bridge collaborative and behavioral analytics with claims to build revenue and profitability
Due to payers’ mature predictive analytics competencies, they will have a much easier time in the next generation of population behavior compared to their provider counterparts. As clinical content is often unstructured compared to the claims data, payers need to pay extra attention to context and semantics when deciphering clinical content submitted by providers. Payers can use help from vendors that can help them understand unstructured data, individual members. They can then use that data to create fantastic predictive analytic solutions.
In a previous life, I was a pastry chef in a now-defunct restaurant. One of the things I noticed while working there (and frankly while cooking at home) is that the better the ingredients, the better the final result. If we used poor quality apples in the apple tart, we ended up with a soupy, flavorless mess with a chewy crust.
The same analogy can be applied to Data Analytics. With poor quality data, you get poor results from your analytics projects. We all know that companies that can implement fantastic analytic solutions that can provide near real-time access to consumer trends are the same companies that can do successful targeted marketing campaigns that are of the minute. The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year.
The business impact of poor data quality cannot be underestimated. If not identified and corrected early on, defective data can contaminate all downstream systems and information assets, jacking up costs, jeopardizing customer relationships, and causing imprecise forecasts and poor decisions.
- To help you quantify: Let’s say your company receives 2 million claims per month with 377 data elements per claim. Even at an error rate of .001, the claims data contains more than 754,000 errors per month and more than 9.04 million errors per year! If you determine that 10 percent of the data elements are critical to your business decisions and processes, you still must fix almost 1 million errors each year!
- What is your exposure to these errors? Let’s estimate the risk at $10 per error (including staff time required to fix the error downstream after a customer discovers it, the loss of customer trust and loyalty and erroneous payouts. Your company’s risk exposure to poor quality claims data is $10 million a year.
Once your company values quality data as a critical resource – it is much easier to perform high-value analytics that have an impact on your bottom line. Start with creation of a Data Quality program. Data is a critical asset in the information economy, and the quality of a company’s data is a good predictor of its future success.
Data has always played a key role in informing decisions – machine generated and intuitive. In the past, much of this data came from transactional databases as well as unstructured sources, such as emails and flat files. Mobile devices appeared next on the map. We have found applications of such devices not just to make calls but also to send messages, take a picture, and update status on social media sites. As a result, new sets of data got created from user engagements and interactions. Such data started to tell a story by connecting dots at different location points and stages of user connection. “Internet of Things” or IoT is the latest technology to enter the scene that could transform how we view and use data on a massive scale.
Does IoT present a significant opportunity for companies to transform their business processes? Internet of Things probably add an important awareness veneer when it comes to data. It could bring data early in focus by connecting every step of data creation stages in any business process. It could de-couple the lagging factor in consuming data and making decisions based on it. Data generated at every stage in a business process could show an interesting trend or pattern and better yet, tell a connected story. Result could be predictive maintenance of equipment involved in any process that would further reduce cost. New product innovations would happen by leveraging the connectedness in data as generated by each step in a business process. We would soon begin to understand not only where the data is being used and how, but also what’s the intent and context behind this usage. Organizations could then connect with their customers in a one-on-one fashion like never before, whether to promote a product or offer a promotion that could be both time and place sensitive. New opportunities to tailor product and services offering for customers on an individual basis would create new growth areas for businesses. Internet of Things could make it a possibility by bringing together previously isolated sets of data.
Recent Economist report, “The Virtuous Circle of Data: Engaging Employees in Data and Transforming Your Business” suggests that 68% of data-driven businesses outperform their competitors when it comes to profitability. 78% of those businesses foster a better culture of creativity and innovation. Report goes on to suggest that 3 areas are critical for an organization to build a data-driven business, including data supported by devices: 1) Technology & Tools, 2) Talent & Expertise, and 3) Culture & Leadership. By 2020, it’s projected that there’ll be 50B connected devices, 7x more than human beings on the planet. It is imperative for an organization to have a support structure in place for device generated data and a strategy to connect with broader enterprise-wide data initiatives.
A comprehensive Internet of Things strategy would leverage speed and context of data to the advantage of business process owners. Timely access to device generated data can open up the channels of communication to end-customers in a personalized at the moment of their readiness. It’s not enough anymore to know what customers may want or what they asked for in the past; rather anticipating what they might want by connecting dots across different stages. IoT generated data can help bridge this gap.
How to Manage IoT Generated Data
More data places more pressure on both quality and security factors – key building blocks for trust in one’s data. Trust is ideally truth over time. Consistency in data quality and availability is going to be key requirement for all organizations to introduce new products or service differentiated areas in a speedy fashion. Informatica’s Intelligent Data Platform or IDP brings together industry’s most comprehensive data management capabilities to help organizations manage all data, including device generated, both in the cloud and on premise. Informatica’s IDP enables an automated sensitive data discovery, such that data discovers users in the context where it’s needed.
Cool IoT Applications
There are a number of companies around the world that are working on interesting applications of Internet of Things related technology. Smappee from Belgium has launched an energy monitor that can itemize electricity usage and control a household full of devices by clamping a sensor around the main power cable. This single device can recognize individual signatures produced by each of the household devices and can let consumers switch off any device, such as an oven remotely via smartphone. JIBO is a IoT device that’s touted as the world’s first family robot. It automatically uploads data in the cloud of all interactions. Start-ups such as Roost and Range OI can retrofit older devices with Internet of Things capabilities. One of the really useful IoT applications could be found in Jins Meme glasses and sunglasses from Japan. They embed wearable sensors that are shaped much like Bluetooth headsets to detect drowsiness in its wearer. It observes the movement of eyes and blinking frequency to identify tiredness or bad posture and communicate via iOS and android smartphone app. Finally, Mellow is a new kind of kitchen robot that makes it easier by cooking ingredients to perfection while someone is away from home. Mellow is a sous-vide machine that takes orders through your smartphone and keeps food cold until it’s the exact time to start cooking.
Each of the application mentioned above deals with data, volumes of data, in real-time and in stored fashion. Such data needs to be properly validated, cleansed, and made available at the moment of user engagement. In addition to Informatica’s Intelligent Data Platform, newly introduced Informatica’s Rev product can truly connect data coming from all sources, including IoT devices and make it available for everyone. What opportunity does IoT present to your organization? Where are the biggest opportunities to disrupt the status quo?
62% of global consumers switched service providers due to poor customer service experiences (Accenture Global Consumer Pulse Survey)
Issues with keeping everyone happy have been around since the beginning of trade and as trading has evolved, the underlying rule remains the same – keep the customers happy! Retailers who move beyond just selling to the customer and focus on creating the shopping experience customers want will see higher retention rates and increased spend per shopper.
Other factors like good quality of the products and competitive pricing play a huge role as well but taking care of the consumer is even more important. At the end of the day, shoppers have more options and opportunities to purchase from your competitors.
While multi-channel commerce has gown, many people are shopping not because they really need the products but because they like the experience of shopping. The better the experience is (which includes an amazing customer service) the more likely it is that the customer will come back and make a purchase in store or online. However, if they run into issues with the retailer, not only will they complain and never come back but they will tell their friends, damaging your brand and hurting the bottom line.
News of bad customer service reaches more than twice as many ears as praise for a good service experience. (Help Scout)
Today retailers realize the importance of great customer service and that’s why they train their staff to be friendly and helpful to the customers at all times. Studies have shown that people are reacting very positively to this kind of treatment and not only are they more willing to spend more money but also remain a customer a long a time.
People want to be treated right but they also want to feel important. That’s why retail businesses nowadays go an extra step and use technology and access more data like past purchases, preferences and trends to enhance the customer experience. Even if a customer had a bad experience smart retailers are leveraging customer insights to turn any bad situation around fast. Customer service representatives can responsive to any situation with all the information they need in real time or a highly personalize offer can be delivered to their smartphone.
A 5% increase in customer retention produces more than a 25% increase in profit. (Bain & Co.)
Retailers also have access to different social channels where they can influence and respond to what their customers are saying about their services and products and can use this instant feedback to make changes quickly and precisely.
In today’s world retail businesses have a great advantage compared to the ones that were operating even 5-10 years ago and if they are prompt in addressing concerns they can minimize the negative affect on their operations very easily. Each satisfied customer is not only going to spend money but they are going to advocate for the retailer which is a very powerful thing in business in the long run.
That’s why today successful retail businesses are turning data into insight to make sure that any problems and concerns are addressed promptly and efficiently, and deliver the experience customers desire.
As we renew or reinvent ourselves for 2015, I wanted to share a case of “imagine if” with you and combine it with the narrative of an American frontier town out West, trying to find a new Sheriff – a Wyatt Earp. In this case the town is a legacy European communications firm and Wyatt and his brothers are the new managers – the change agents.
Here is a positive word upfront. This operator has had some success in rolling outs broadband internet and IPTV products to residential and business clients to replace its dwindling copper install base. But they are behind the curve on the wireless penetration side due to the number of smaller, agile MVNOs and two other multi-national operators with a high density of brick-and-mortar stores, excellent brand recognition and support infrastructure. Having more than a handful of brands certainly did not make this any easier for our CSP. To make matters even more challenging, price pressure is increasingly squeezing all operators in this market. The ones able to offset the high-cost Capex for spectrum acquisitions and upgrades with lower-cost Opex for running the network and maximizing subscriber profitability, will set themselves up for success (see one of my earlier posts around the same phenomenon in banking).
Not only did they run every single brand on a separate CRM and billing application (including all the various operational and analytical packages), they also ran nearly every customer-facing-service (CFS) within a brand the same dysfunctional way. In the end, they had over 60 CRM and the same number of billing applications across all copper, fiber, IPTV, SIM-only, mobile residential and business brands. Granted, this may be a quite excessive example; but nevertheless, it is relevant for many other legacy operators.
As a consequence, their projections indicate they incur over €600,000 annually in maintaining duplicate customer records (ignoring duplicate base product/offer records for now) due to excessive hardware, software and IT operations. Moreover, they have to stomach about the same amount for ongoing data quality efforts in IT and the business areas across their broadband and multi-play service segments.
Here are some more consequences they projected:
- €18.3 million in call center productivity improvement
- €790,000 improvement in profit due to reduced churn
- €2.3 million reduction in customer acquisition cost
- And if you include the fixing of duplicate and conflicting product information, add another €7.3 million in profit via billing error and discount reduction (which is inline with our findings from a prior telco engagement)
Despite major business areas not having contributed to the investigation and improvements being often on the conservative side, they projected a 14:1 return ratio between overall benefit amount and total project cost.
Coming back to the “imagine if” aspect now, one would ask how this behemoth of an organization can be fixed. Well, it will take years but without management (in this case new managers busting through the door), this organization has the chance to become the next Rocky Mountain mining ghost town.
The good news is that this operator is seeing some management changes now. The new folks have a clear understanding that business-as-usual won’t do going forward and that centralization of customer insight (which includes some data elements) has its distinct advantages. They will tackle new customer analytics, order management, operational data integration (network) and next-best-action use cases incrementally. They know they are in the data, not just the communication business. They realize they have to show a rapid succession of quick wins rather than make the organization wait a year or more for first results. They have fairly humble initial requirements to get going as a result.
You can equate this to the new Sheriff not going after the whole organization of the three, corrupt cattle barons, but just the foreman of one of them for starters. With little cost involved, the Sheriff acquires some first-hand knowledge plus he sends a message, which will likely persuade others to be more cooperative going forward.
What do you think? Is new management the only way to implement drastic changes around customer experience, profitability or at least understanding?
Maybe the problem lies in the widespread confusion about omni- vs. multi-channel initiatives. An omni-channel system takes a connected approach to multiple channels, seamlessly integrating customer activities into a single conversation, even when the customer decides, for whatever reason, to switch channel. In omni-channel retailing, the customer can select and change channels in any way that suits them – and the retailer can respond instantly to deliver the experience that the customer needs. Each time the customer interacts with the brand, they generate data that the retailer can use to better anticipate and serve the customer during the next conversation.
So, if omni-channel initiatives are so powerful, why are retailers not taking the next step?
In a multi-channel system, a retailer grows from a single channel to multiple channels with each channel essentially operating as a separate business unit. Each has its own pricing, promotions, inventories, and back office systems. The omni-channel system integrates all of these channels and their accumulated data into one cohesive view of the business and customer. But many retailers wrongly believe that their organizational structure and systems don’t lend themselves to the new environment.
Many feel that a fundamental redesign of the corporate retail organization – from a single P&L regardless of channel, to “rip and replace” of IT systems – would need to occur at the most basic levels. And many organizations are unsure if the extra time, money and risk to reorganize is worth the advantages promised by an omni-channel strategy. In short, many retailers have adopted a wait-and-see stance before they invest.
However, these retailers can take comfort and guidance from the conclusions of the IDC FutureScape: Worldwide Retail 2015 Predictions conference. Based on a survey of top retailers, the conference predicts that “In 2015, CIOs will invest in omni-channel integration technologies as a top priority to support growth in the omni-channel shopper sales premium of 30%.“
The Future is Now
When retailers invest in omni-channel integration, they essentially design an entirely new supply chain of unified capabilities that can simultaneously handle the demands of their “brick and mortar” stores, their ecommerce sites, and any other channel that they have in place. The retailers that have already done so are already seeing the benefits:
- Corporations that have invested in omni-channel services are already witnessing an average of 30% increase in sales.
- The IT departments of these corporations are spending far less time performing the redundant or duplicate tasks required by a multi-channel system.
- Both structured and unstructured data are more successfully and easily integrated across the company than with a multichannel operation.
- IT departments can retire older technologies that are no longer performing at their previous levels of efficiency.
- Consumer impacts on individual channels can now be identified almost immediately and the channels adjusted accordingly.
While many businesses may be cautious about taking the next step, the shopping characteristics of today’s consumer are rapidly changing. Customers are moving into an omni-channel world, whether the retailer is ready or not. This means that the business might be forced to play catch-up to their customers, and perhaps sooner than they might like. Omni-channel initiatives simply reflect, improve and realize the value of this customer behavior. Omni-channel initiatives are about making the individual consumer the main focal point of the business model.
It is troublesome to me to repeatedly get into conversations with IT managers who want to fix data “for the sake of fixing it”. While this is presumably increasingly rare, due to my department’s role, we probably see a higher occurrence than the normal software vendor employee. Given that, please excuse the inflammatory title of this post.
Nevertheless, once the deal is done, we find increasingly fewer of these instances, yet still enough, as the average implementation consultant or developer cares about this aspect even less. A few months ago a petrochemical firm’s G&G IT team lead told me that he does not believe that data quality improvements can or should be measured. He also said, “if we need another application, we buy it. End of story.” Good for software vendors, I thought, but in most organizations $1M here or there do not lay around leisurely plus decision makers want to see the – dare I say it – ROI.
However, IT and business leaders should take note that a misalignment due to lack OR disregard of communication is a critical success factor. If the business does not get what it needs and wants AND it differs what Corporate IT is envisioning and working on – and this is what I am talking about here – it makes any IT investment a risky proposition.
Let me illustrate this with 4 recent examples I ran into:
1. Potential for flawed prioritization
A retail customer’s IT department apparently knew that fixing and enriching a customer loyalty record across the enterprise is a good and financially rewarding idea. They only wanted to understand what the less-risky functional implementation choices where. They indicated that if they wanted to learn what the factual financial impact of “fixing” certain records or attributes, they would just have to look into their enterprise data warehouse. This is where the logic falls apart as the warehouse would be just as unreliable as the “compromised” applications (POS, mktg, ERP) feeding it.
Even if they massaged the data before it hit the next EDW load, there is nothing inherently real-time about this as all OLTP are running processes of incorrect (no bidirectional linkage) and stale data (since the last load).
I would question if the business is now completely aligned with what IT is continuously correcting. After all, IT may go for the “easy or obvious” fixes via a weekly or monthly recurring data scrub exercise without truly knowing, which the “biggest bang for the buck” is or what the other affected business use cases are, they may not even be aware of yet. Imagine the productivity impact of all the roundtripping and delay in reporting this creates. This example also reminds me of a telco client, I encountered during my tenure at another tech firm, which fed their customer master from their EDW and now just found out that this pattern is doomed to fail due to data staleness and performance.
2. Fix IT issues and business benefits will trickle down
Client number two is a large North American construction Company. An architect built a business case for fixing a variety of data buckets in the organization (CRM, Brand Management, Partner Onboarding, Mobility Services, Quotation & Requisitions, BI & EPM).
Grand vision documents existed and linked to the case, which stated how data would get better (like a sick patient) but there was no mention of hard facts of how each of the use cases would deliver on this. After I gave him some major counseling what to look out and how to flesh it out – radio silence. Someone got scared of the math, I guess.
3. Now that we bought it, where do we start
The third culprit was a large petrochemical firm, which apparently sat on some excess funds and thought (rightfully so) it was a good idea to fix their well attributes. More power to them. However, the IT team is now in a dreadful position having to justify to their boss and ultimately the E&P division head why they prioritized this effort so highly and spent the money. Well, they had their heart in the right place but are a tad late. Still, I consider this better late than never.
4. A senior moment
The last example comes from a South American communications provider. They seemingly did everything right given the results they achieved to date. This gets to show that misalignment of IT and business does not necessarily wreak havoc – at least initially.
However, they are now in phase 3 of their roll out and reality caught up with them. A senior moment or lapse in judgment maybe? Whatever it was; once they fixed their CRM, network and billing application data, they had to start talking to the business and financial analysts as complaints and questions started to trickle in. Once again, better late than never.
So what is the take-away from these stories. Why wait until phase 3, why have to be forced to cram some justification after the purchase? You pick, which one works best for you to fix this age-old issue. But please heed Sohaib’s words of wisdom recently broadcast on CNN Money “IT is a mature sector post bubble…..now it needs to deliver the goods”. And here is an action item for you – check out the new way for the business user to prepare their own data (30 minutes into the video!). Agreed?
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?
Murphy’s First Law of Bad Data – If You Make A Small Change Without Involving Your Client – You Will Waste Heaps Of Money
I have not used my personal encounter with bad data management for over a year but a couple of weeks ago I was compelled to revive it. Why you ask? Well, a complete stranger started to receive one of my friend’s text messages – including mine – and it took days for him to detect it and a week later nobody at this North American wireless operator had been able to fix it. This coincided with a meeting I had with a European telco’s enterprise architecture team. There was no better way to illustrate to them how a customer reacts and the risk to their operations, when communication breaks down due to just one tiny thing changing – say, his address (or in the SMS case, some random SIM mapping – another type of address).
In my case, I moved about 250 miles within the United States a couple of years ago and this seemingly common experience triggered a plethora of communication screw ups across every merchant a residential household engages with frequently, e.g. your bank, your insurer, your wireless carrier, your average retail clothing store, etc.
For more than two full years after my move to a new state, the following things continued to pop up on a monthly basis due to my incorrect customer data:
- In case of my old satellite TV provider they got to me (correct person) but with a misspelled last name at my correct, new address.
- My bank put me in a bit of a pickle as they sent “important tax documentation”, which I did not want to open as my new tenants’ names (in the house I just vacated) was on the letter but with my new home’s address.
- My mortgage lender sends me a refinancing offer to my new address (right person & right address) but with my wife’s as well as my name completely butchered.
- My wife’s airline, where she enjoys the highest level of frequent flyer status, continually mails her offers duplicating her last name as her first name.
- A high-end furniture retailer sends two 100-page glossy catalogs probably costing $80 each to our address – one for me, one for her.
- A national health insurer sends “sensitive health information” (disclosed on envelope) to my new residence’s address but for the prior owner.
- My legacy operator turns on the wrong premium channels on half my set-top boxes.
- The same operator sends me a SMS the next day thanking me for switching to electronic billing as part of my move, which I did not sign up for, followed by payment notices (as I did not get my invoice in the mail). When I called this error out for the next three months by calling their contact center and indicating how much revenue I generate for them across all services, they counter with “sorry, we don’t have access to the wireless account data”, “you will see it change on the next bill cycle” and “you show as paper billing in our system today”.
Ignoring the potential for data privacy law suits, you start wondering how long you have to be a customer and how much money you need to spend with a merchant (and they need to waste) for them to take changes to your data more seriously. And this are not even merchants to whom I am brand new – these guys have known me and taken my money for years!
One thing I nearly forgot…these mailings all happened at least once a month on average, sometimes twice over 2 years. If I do some pigeon math here, I would have estimated the postage and production cost alone to run in the hundreds of dollars.
However, the most egregious trespass though belonged to my home owner’s insurance carrier (HOI), who was also my mortgage broker. They had a double whammy in store for me. First, I received a cancellation notice from the HOI for my old residence indicating they had cancelled my policy as the last payment was not received and that any claims will be denied as a consequence. Then, my new residence’s HOI advised they added my old home’s HOI to my account.
After wondering what I could have possibly done to trigger this, I called all four parties (not three as the mortgage firm did not share data with the insurance broker side – surprise, surprise) to find out what had happened.
It turns out that I had to explain and prove to all of them how one party’s data change during my move erroneously exposed me to liability. It felt like the old days, when seedy telco sales people needed only your name and phone number and associate it with some sort of promotion (back of a raffle card to win a new car), you never took part in, to switch your long distance carrier and present you with a $400 bill the coming month. Yes, that also happened to me…many years ago. Here again, the consumer had to do all the legwork when someone (not an automatic process!) switched some entry without any oversight or review triggering hours of wasted effort on their and my side.
We can argue all day long if these screw ups are due to bad processes or bad data, but in all reality, even processes are triggered from some sort of underlying event, which is something as mundane as a database field’s flag being updated when your last purchase puts you in a new marketing segment.
Now imagine you get married and you wife changes her name. With all these company internal (CRM, Billing, ERP), free public (property tax), commercial (credit bureaus, mailing lists) and social media data sources out there, you would think such everyday changes could get picked up quicker and automatically. If not automatically, then should there not be some sort of trigger to kick off a “governance” process; something along the lines of “email/call the customer if attribute X has changed” or “please log into your account and update your information – we heard you moved”. If American Express was able to detect ten years ago that someone purchased $500 worth of product with your credit card at a gas station or some lingerie website, known for fraudulent activity, why not your bank or insurer, who know even more about you? And yes, that happened to me as well.
Tell me about one of your “data-driven” horror scenarios?