Category Archives: Enterprise Data Management
Like me, you probably just returned from an inspiring Sales Kick Off 2015 event. You’ve invested in talented people. You’ve trained them with the skills and knowledge they need to identify, qualify, validate, negotiate and close deals. You’ve invested in world-class applications, like Salesforce Sales Cloud, to empower your sales team to sell more effectively. But does your sales team have what they need to succeed in 2015?
Gartner predicts that as early as next year, companies will compete primarily on the customer experiences they deliver. So, every customer interaction counts. Knowing your customers is key to delivering great sales experiences.
But, inaccurate, inconsistent and disconnected customer information may be holding your sales team back from delivering great sales experiences. If you’re not fueling Salesforce Sales Cloud (or another Sales Force Automation (SFA) application) with clean, consistent and connected customer information, your sales team may be at a disadvantage against the competition.
To successfully compete and deliver great sales experiences more efficiently, your sales team needs a complete picture of their customers. They don’t want to pull information from multiple applications and then reconcile it in spreadsheets. They want direct access to the Total Customer Relationship across channels, touch points and products within their Salesforce Sales Cloud.
Watch this short video comparing a day-in-the-life of two sales reps competing for the same business. One has access to the Total Customer Relationship in Salesforce Sales Cloud, the other does not. Watch now: Salesforce.com with Clean, Consistent and Connected Customer Information
Is your sales team spending time creating spreadsheets by pulling together customer information from multiple applications and then reconciling it to understand the Total Customer Relationship across channels, touch points and products? If so, how much is it costing your business? Or is your sales team engaging with customers without understanding the Total Customer Relationship? How much is that costing your business?
Many innovative sales leaders are gaining a competitive edge by better leveraging their customer data to empower their sales teams to deliver great sales experiences. They are fueling business and analytical applications, like Salesforce Sales Cloud, with clean, consistent and connected customer information. They are arming their sales teams with direct access to richer customer profiles, which includes the Total Customer Relationship across channels, touch points and products.
What measurable results have these sales leaders acheived? Merrill Lynch boosted sales productivity by 15%, resulting in $50M in annual impact. A $60B manufacturing company improved cross-sell and up-sell success by 5%. Logitech increased across channels: online, in their retail partner’s stores and through distribution partners.
This year, I believe more sales leaders will focus on leveraging their customer information for competitive advantage. This will help them shift from sales automation to sales optimization. What do you think?
The article provided the following recommendations when talking to teenagers:
1. Talk with them and not at them.
2. Ask questions that go beyond “yes” or “no” answers to prompt more developed conversation.
3. Take advantage of time during car trips to talk with your teen.
4. Make time for sporting and school events, playing games, and talking about current events.
Let’s see how these recommendations could be applied:
1. Talk to them and not at them
Ask your teenager the following question – Have you ever heard about Enterprise Architecture?
“It is a way to help a company understand its customers and how its products are made and sold. It helps managers improve the way the company works and how technology is used to help people do a better job”.
2. Ask questions that go beyond “yes” or “no” answers to prompt more developed conversation.
Ask your teenager the following question: What do you want to do when you grow up? – Depending on the answer you may need to customize the text below.
“Enterprise Architecture helps you understand the needs of (the industry selected by your teenager). It will then tell you the typical activities that employees do and the systems and technologies that are used to simplify those activities”.
3. Take advantage of time during car trips to talk with your teen.
Imagine the following scenario with your teenager – we can do the following exercise. Let’s assume your teenager wants be part of an advertising agency for the entertainment industry.
“We should count the number of billboards on the side of the road and note how many are movie advertisements. I am interested in your opinion of which advertising style sparks your interest in a specific movie”.
“If we do that we can then discuss the different activities that are required in making that advertising material and how to make the images speak to you. Enterprise Architecture also does that. It helps you understand the activities required in any business, step by step, allowing you to create templates or graphics that represent any industry”.
4. Make time for sports and school events, play games, and talk about current events.
Another sample conversation to support this recommendation could be:
“Let’s go to the movies this week. Once you select one you would like to see, see if you can identify why you choose this particular movie over the other ones. If you think of the billboards that we saw, can you remember what motivated or influenced you?. We can understand together what the designers of those images were creating in the visual experience. Perhaps you have new ideas or suggestions on how they could have done it better? With the help of Enterprise Architecture companies identify more efficient activities to generate more business”.
After researching the topic I realized that we could apply these recommendations to share Enterprise Architecture with our business partners. Perhaps the readers of this blog can help by using these recommendations with their teenagers at home to explain the basic concepts of Enterprise Architecture and collectively create a simpler way to talk about Enterprise Architecture.
I have to admit I am a huge and longtime Mixed Martial Arts (MMA) fan. Even before MMA became main stream, I have followed and studied traditional martial arts from Tae Kwon Do, Judo, Boxing, Wrestling, and Jujitsu since I was a young lad. Given I hate pain, I am glad I call myself a fan and only a spectator. Modern MMA fighters are extremely talented athletes however their success to win the cage is dependent on having a strong base across different disciplines. They must be good on their feet with effective punches and kicks, have world class level wrestling, jujitsu, and judo on the ground, strong defense techniques all around, and a strong will not to quit.
My other passion of which is a less painful one is helping organizations understand and harness technology and best practices to leverage great data for business success. Believe it or not, there are close similarities between being an effective MMA fighter and a successful information architect. Information architects in today’s modern Big Data/Internet of Things world has to have a mix of knowledge and skills to recommend, design, and implement the right information management solutions for their businesses. This involves having a strong background in database development, data engineering, computer programming, web, security, networking, system administration, development, and other technology competencies to formulate and categorize information into a coherent structure, preferably one that the intended audience can understand quickly, if not inherently, and then easily retrieve the information for which they are searching.
Like successful MMA fighters, Information Architects require training and development of basic building blocks regardless of their “intellectual” and “technical” prowess. Having a strong base allows architects to recommend the right solutions, avoiding ineffective and inefficient methods such as hand coding critical data integration, data governance, and data quality processes that often result in bad data, higher costs, and increased risk of not meeting what the business needs. An MMA fighter with a strong base would leverage those skills to avoid techniques or moves that places themselves at harm or risk of getting knocked out, choked out, or getting an arm broken by their opponent. Instead, like an MMA fighter, well developed architects leverage that base and knowledge to adopt proven technologies for their information architecture and management needs.
The technologies to manage data in the enterprise vary both in performance, functionality, and value. Like MMA fighters competing for a living, it’s important they learn from skilled masters vs. the local martial arts school at your neighborhood strip mall or free YouTube videos recorded by jokers claiming to be a master and hoping that knowledge will help them survive in combat. Similarly, architects must make careful investments and decisions when designing systems to deliver great data. Short cuts and “good enough” tools won’t cut it in today’s data driven world. Great Data only comes by Great Design powered by an intelligent and capable data platform. “Are you Ready to Get it On!”
- Home Hubs from Google, Samsung, and Apple (who did not attend the show but still had a significant impact).
- Home Hub Ecosystems providing interoperability with cars, door locks, and household appliances.
- Autonomous cars, and intelligent cars
- Wearable devices such as smart watches and jewelry.
- Drones that take pictures and intelligently avoid obstacles. …Including people trying to block them. There is a bit of a creepy factor here!
- The next generation of 3D printers.
- And the intelligent baby pacifier. The idea is that it takes the baby’s temperature, but I think the sleeper hit feature on this product is the ability to locate it using GPS and a smart phone. How much money would you pay to get your kid to go to sleep when it is time to do so?
Digital Strategies Are Gaining Momentum
There is no escaping the fact that the vast majority of companies out there have active digital strategies, and not just in the consumer space. The question is: Are you going to be the disruptor or the disruptee? Gartner offered an interesting prediction here:
“By 2017, 60% of global enterprise organizations will execute on at least one revolutionary and currently unimaginable business transformation effort.”
It is clear from looking at CES, that a lot of these products are “experiments” that will ultimately fail. But focusing too much on that fact is to risk overlooking the profound changes taking place that will shake out industries and allow competitors to jump previously impassible barriers to entry.
IDC predicted that the Internet of Things market would be over $7 Trillion by the year 2020. We can all argue about the exact number, but something major is clearly happening here. …And it’s big.
Is Your Organization Ready?
A study by Gartner found that 52% of CEOs and executives say they have a digital strategy. The problem is that 80% of them say that they will “need adaptation and learning to be effective in the new world.” Supporting a new “Internet of Things” or connected device product may require new business models, new business processes, new business partners, new software applications, and require the collection and management of entirely new types of data. Simply standing up a new ERP system or moving to a cloud application will not help your organization to deal with the new business models and data complexity.
Architect’s Call to Action
Now is the time (good New Year’s resolution!) to get proactive on your digital strategy. Your CIO is most likely deeply engaged with her business counterparts to define a digital strategy for the organization. Now is the time to be proactive in terms of recommending the IT architecture that will enable them to deliver on that strategy – and a roadmap to get to the future state architecture.
Key Requirements for a Digital-ready Architecture
Digital strategy and products are all about data, so I am going to be very data-focused here. Here are some of the key requirements:
- First, it must be designed for speed. How fast? Your architecture has to enable IT to move at the speed of business, whatever that requires. Consider the speed at which companies like Google, Amazon and Facebook are making IT changes.
- It has to explicitly directly link the business strategy to the underlying business models, processes, systems and technology.
- Data from any new source, inside or outside your organization, has to be on-boarded quickly and in a way that it is immediately discoverable and available to all IT and business users.
- Ongoing data quality management and Data Governance must be built into the architecture. Point product solutions cannot solve these problems. It has to be pervasive.
- Data security also has to be pervasive for the same reasons.
- It must include business self-service. That is the only way that IT is going to be able to meet the needs of business users and scale to the demands of the changes required by digital strategy.
For a webinar on connecting business strategy to the architecture of business transformation see; Next-Gen Architecture: A “Business First” Approach for Agile Architecture. With John Schmidt of Informatica and Art Caston, founder of Proact.
For next-generation thinking on enterprise data architectures see; Think “Data First” to Drive Business Value
For more on business self-service for data preparation and a free software download.
As more and more businesses become fully digitized, the instantiation of their business processes and business capabilities becomes based in software. And when businesses implement software, there are choices to be made that can impact whether these processes and capabilities become locked in time or establish themselves as a continuing basis for business differentiation.
Make sure you focus upon the business goals
I want to suggest that whether the software instantiations of business process and business capabilities deliver business differentiation depends upon whether business goals and analytics are successfully embedded in a software implementation from the start. I learned this first hand several years ago. I was involved in helping a significant insurance company with their implementation of analytics software. Everyone in the management team was in favor of the analytics software purchase. However, the project lead wanted the analytics completed after an upgrade had occurred to their transactional processing software. Fortunately, the firm’s CIO had a very different perspective. This CIO understood that decisions regarding the transaction processing software implementation could determine whether critical metrics and KPIs could be measured. So instead of doing analytics as an afterthought, this CIO had the analytics done as a fore thought. In other words, he slowed down the transactional software implementation. He got his team to think first about the goals for the software implementation and the business goals for the enterprise. With these in hand, his team determined what metrics and KPIs were needed to measure success and improvement. They then required the transaction software development team to ensure that the software implemented the fields needed to measure the metrics and KPIs. In some cases, this was as simple as turning on a field or training users to enter a field as the transaction software went live.
Make the analytics part of everyday business decisions and business processes
The question is how common is this perspective because it really matters. Tom Davenport says that “if you really want to put analytics to work in an enterprise, you need to make them an integral part of everyday business decisions and business processes—the methods by which work gets done” (Analytics at Work, Thomas Davenport, Harvard Business Review Press, page 121). For many, this means turning their application development on its head like our insurance CIO. This means in particular that IT implementation teams should no longer be about just slamming in applications. They need to be more deliberate. They need to start by identifying the business problems that they want to get solved through the software instantiation of a business process. They need as well to start with how they want to improve process by the software rather than thinking about getting the analytics and data in as an afterthought.
Why does this matter so much? Davenport suggests that “embedding analytics into processes improves the ability of the organization to implement new insights. It eliminates gaps between insights, decisions, and actions” (Analytics at Work, Thomas Davenport, Harvard Business Review Press, page 121). Tom gives the example of a car rental company that embedded analytics into its reservation system and was able with the data provided to expunge long held shared beliefs. This change, however, resulted in a 2% increased fleet utilization and returned $19m to the company from just one location.
Look beyond the immediate decision to the business capability
Davenport also suggests as well that enterprises need look beyond their immediate task or decision and appreciate the whole business process or what happens upstream or downstream. This argues that analytics be focused on the enterprise capability system. Clearly, maximizing performance of the enterprise capability system requires an enterprise perspective upon analytics. As well, it should be noted that a systems perspective allows business leadership to appreciate how different parts of the business work together as a whole. Analytics, therefore, allow the business to determine how to drive better business outcomes for the entire enterprise.
At the same time, focusing upon the enterprise capabilities system in many cases will overtime lead a reengineering of overarching business processes and a revamping of their supporting information systems. This allows in turn the business to capitalize on the potential of business capability and analytics improvement. From my experience, most organizations need some time to see what a change in analytics performance means. This is why it can make sense to start by measuring baseline process performance before determining enhancements to the business process. Once completed, however, refinement to the enhanced process can be determined by continuously measuring processes performance data.
Analytics Stories: A Banking Case Study
Analytics Stories: A Financial Services Case Study
Analytics Stories: A Healthcare Case Study
Who Owns Enterprise Analytics and Data?
Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR
Thomas Davenport Book “Competing On Analytics”
Solution Brief: The Intelligent Data Platform
Author Twitter: @MylesSuer
The last few months have allowed me to see MDM, data quality and data governance from a completely different perspective. I sat with other leaders here at Informatica, analysts who focus on information quality and spent time talking to our partners who work closely with customers on data management initiatives. As we collectively attempted to peer into the crystal ball and forecast what will be hot – and what will not – in this year and beyond for MDM and data quality, here are few top predictions that stood out.
1. MDM will become a single platform for all master entities
“The classical notion of boundaries that existed where we would say, this is MDM versus this is not MDM is going to get blurred,” says Dennis Moore – SVP, Information Quality Solutions (IQS), Informatica. “Today, we master a fairly small number of attributes in MDM. Rather than only mastering core attributes, we need to master business level entities, like customer, product, location, assets, things, etc., and combine all relevant attributes into a single platform which can be used to develop new “data fueled” applications. This platform will allow mastering of data, aggregate data from other sources, and also syndicate that data out into other systems.”
Traditionally MDM was an invisible hub that was connected to all the spokes. Instead, Dennis says – “MDM will become more visible and will act as an application development platform.”
2. PIM is becoming more integrated environment that covers all information about products and related data in single place
More and more customers want to have single interface which will allow them to manage all product information. Along with managing a product’s length, width, height, color, cost etc., they probably want to see data about the history, credit rating, previous quality rating, sustainability scorecard, returns, credits and so on. Dennis says – “All the product information in one place helps make better decisions with embedded analytics, giving answers to questions such as:
- What were my sales last week?
- Which promotions are performing well and poorly?
- Which suppliers are not delivering on their SLAs?
- Which stores aren’t selling according to plan?
- How are the products performing in specific markets?”
Essentially, PIM will become a sovereign supplier of product data that goes in your catalog and ecommerce system that will be used by merchandisers, buyers, and product and category managers. It will become the buyer’s guide and a desktop for the person whose job is to figure out how to effectively promote products to meet sales targets.
3. MDM will become an integral part of big data analytics projects
“Big data analytics suffers from the same challenges as traditional data warehouses – bad data quality produces sub-optimal intelligence. MDM has traditionally enabled better analysis and reporting with high quality master data. Big data analytics will also immensely benefit from MDM’s most trustworthy information.” – Said Ravi Shankar – VP of Product Marketing, MDM, Informatica
Naveen Sharma who heads Enterprise Data Management practice at Cognizant reemphasized what I heard from Dennis. He says – “With big data and information quality coming together, some of the boundaries between a pure MDM system and a pure analytical system will start to soften”. Naveen explains – “MDM is now seen as an integral part of big data analytics projects and it’s a huge change from a couple of years ago. Two of large retailers we work with are going down the path of trying to bring not only the customer dimension but the associated transactional data to derive meaning into an extended MDM platform. I see this trend continuing in 2015 and beyond with other verticals as well.”
4. Business requirements are leading to the creation of solutions
There are several business problems being solved by MDM, such as improving supplier spend management and collaboration with better supplier data. Supply chain, sourcing and procurement teams gain significant cost savings and a boost in productivity by mastering supplier, raw materials and product information and fueling their business and analytical applications with that clean, consistent and connected information. Jakki Geiger, Senior Director of IQS Solutions Marketing at Informatica says, “Business users want more than just the underlying infrastructure to manage business-critical data about suppliers, raw materials, and products. They want to access this information directly through a business-friendly user interface. They want a business process-driven workflow to manage the full supplier lifecycle, including: supplier registration, qualification, verification, onboarding and off-boarding. Instead of IT building these business-user focused solutions on top of an MDM foundation, vendors are starting to build ready-to-use MDM solutions like the Total Supplier Relationship solution.” Read more about Valspar’s raw materials spend management use case.
5. Increased adoption of matching and linking capabilities on Hadoop
“Many of our customers have significantly increased the amount of data they want to master,” says Dennis Moore. Days when tens of millions of master records were a lot are long gone and having hundreds of millions of master records and billions of source records is becoming almost common. An increasing number of master data sources –internal and external to organization – are contributing significantly to the rise in data volumes. To accommodate these increasing volumes, Dennis predicts that large enterprises will look at running complex matching and linking capabilities on Hadoop – a cost effective and flexible way to analyze large amount of data.
6. Master insight management is going to be next big step
“MDM will evolve into master insight management as organizations try to relate trusted data they created in MDM with transactional and social interaction data,” said Rob Karel – VP of Product Strategy and Product Marketing, IQS, Informatica. “The innovations in machine and deep learning techniques will help organizations such as healthcare prescribe next best treatment based on history of patients, retailers suggest best offers based on customer interest and behavior, public sector companies will see big steps in social services, etc.”
Rob sees MDM at the heart of this innovation bringing together relevant information about multiple master entities and acting as a core system for insight management innovations.
7. MDM and Data Governance
Aaron Zornes – Chief research officer at the MDM Institute predicts that in 2014-15, vendor MDM solutions will move from “passive-aggressive” mode to “proactive” data governance mode. Data governance for MDM will move beyond simple stewardship to convergence of task management, workflow, policy management and enforcement according to Aaron.
8. The market will solidify for cloud based MDM adoption
Aaron says – “Cloud-innate services for DQ and DG will be more prevalent; however, enterprise MDM will remain on premise with increasing integration to cloud applications in 2015.
Naveen sees lot of synergy around cloud based MDM offerings and says – “The market is solidifying for MDM on cloud but the flood gates are yet to open”. Naveen does not see any reason why MDM market will not go to cloud and gives the example of CRM which was at similar junction before Saleforce came into play. Naveen sees similar shift for MDM and says – “The fears companies have about their data security on cloud is eventually going to fade. If you look closely at any of the recent breaches, these all involved hacks into company networks and not into cloud provider networks. The fact that cloud service providers spend more dollars on data security than any one company can spend on their on-premise security layer will be a major factor affecting the transition”. Naveen sees that big players in MDM will include cloud offerings as part of their toolkit in coming years.
Ravi also predicts an increase in cloud adoption for MDM in future as the concern for placing master data in the cloud becomes less with maximum security provided by cloud vendors.
So, what do you predict? I would love to hear your opinions and comments.
The first architect grew through the ranks starting as a Database Administrator, a black belt in SQL and COBOL programming. Hand coding was their DNA for many years and thought of as the best approach given how customized their business and systems were vs. other organizations. As such, Architect #1 and their team went down the path of building their data management capabilities through custom hand coded scripts, manual data extractions and transformations, and dealing with data quality issues through the business organizations after the data is delivered. Though their approach and decisions delivered on their short term needs, the firm realized the overhead required to make changes and respond to new requests driven by new industry regulations and changing market conditions.
The second architect is a “gadget guy” at heart who grew up using off the shelf tools vs. hand coding for managing data. He and his team decides not to hand code their data management processes, instead adopt and built their solution leveraging best of breed tools, some of which were open source, others from existing solutions the company had from previous projects for data integration, data quality, and metadata management. Though their tools helped automate much of the “heavy lifting” he and is IT team were still responsible for integrating these point solutions to work together which required ongoing support and change management.
The last architect is as technically competent as his peers however understood the value of building something once to use across the business. His approach was a little different than the first two. Understanding the risks and costs of hand coding or using one off tools to do the work, he decided to adopt an integrated platform designed to handle the complexities, sources, and volumes of data required by the business. The platform also incorporated shared metadata, reusable data transformation rules and mappings, a single source of required master and reference data, and provided agile development capabilities to reduce the cost of implementation and ongoing change management. Though this approach was more expensive to implement, the long term cost benefit and performance benefits made the decision a “no brainer’.
Lurking in the woods is Mr. Wolf. Mr. Wolf is not your typical antagonist however is a regulatory auditor whose responsibility is to ensure these banks can explain how risk is calculated as reported to the regulatory authorities. His job isn’t to shut these banks down, instead making sure the financial industry is able to measure risk across the enterprise, explain how risk is measured, and ensure these firms are adequately capitalized as mandated by new and existing industry regulations.
Mr. Wolf visits the first bank for an annual stress test audit. Looking at the result of their stress test, he asks the compliance teams to explain how their data was produced, transformed, calculated, to support the risk measurements they reported as part of the audit. Unfortunately, due to the first architect’s recommendations of hand coding their data management processes, IT failed to provide explanations and documentation on what they did, they found the developers that created their systems were no longer with the firm. As a result, the bank failed miserably, resulting in stiff penalties and higher audit costs.
Next, Architect #2’s bank was next. Having heard of what happened to their peer in the news, the architect and IT teams were confident that they were in good shape to pass their stress test audit. After digging into the risk reports, Mr. Wolf questioned the validity of the data used to calculate Value at Risk (VaR). Unfortunately, the tools that were adopted were never designed nor guaranteed by the vendors to work with each other resulting in invalid data mapping and data quality rules and gaps within their technical metadata documentation. As a result, bank #2 also failed their audit and found themselves with a ton of on one-off tools that helped automate their data management processes but lacked the integration and sharing of rules and metadata to satisfy the regulator’s demand for risk transparency.
Finally, Mr. Wolf investigated Architect #3’s firm. Having seen the result of the first two banks, Mr. Wolf was leery of their ability to pass their stress test audits. Similar demands were presented by Mr. Wolf however this time, Bank #3 provided detailed and comprehensive metadata documentation of their risk data measurements, descriptions of the data used in each report, an comprehensive report of each data quality rule used to cleanse their data, and detailed information on each counterparty and legal entity used to calculate VaR. Unable to find gaps in their audit, Mr. Wolf, expecting to “blow” the house down, delivered a passing grade for Bank 3 and their management team due to the right investments they made to support their enterprise risk data management needs.
The moral of this story, similar to the familiar one involving the three little pigs is about the importance of having a solid foundation to weather market and regulatory storms or the violent bellow of a big bad wolf. A foundation that includes the required data integration, data quality, master data management, and metadata management needs but also supports collaboration and visibility of how data is produced, used, and performing across the business. Ensuring current and future compliance in today’s financial services industry requires firms to have a solid data management platform, one that is intelligent, comprehensive, and allows Information Architects to help mitigate the risks and costs of hand coding or using point tools to get by only in the short term.
Are you prepared to meet Mr. Wolf?
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?
Established in Northwestern United States, North 40 Outfitters, a family owned and operated business, has been outfitting the hardworking and hard playing populace of the region. Understanding the diverse needs of its customers, hardworking people, North 40 Outfitters carries everything from fencing for cattle and livestock to tools and trailers. They have gear for camping and hunting—even fly fishing.
Named after the Homestead Act of 1862, an event with strong significance in the region, North 40 Outfitters heritage is built on its community involvement and support of local small businesses. The company’s 700 employees could be regarded as family. At this year’s Thanksgiving, every employee was given a locally raised free range turkey to bring home. Furthermore, true to Black Friday’s shopping experience, North 40 Outfitters opened its door. Eschewing the regular practice of open as early as 3 AM, North 40 Outfitters opened at the reasonable 7 o’clock hour. They offered patrons donuts as well as coffee obtained from a local roaster.
North 40 Outfitters aims to be different. They achieve differentiation by being data driven. While the products they sell cannot be sourced exclusively from local sources, their experience aims to do exactly that.
Prior to operating under the name North 40 Outfitters, the company ran under the banner of “Big R”, which was shared with several other members of the same buying group. The decision to change the name to North 40 Outfitters was the result of a move into the digital realm— they needed a name to distinguish themselves. Now as North 40 Outfitters, they can focus on what matters rather than having to deal with the confusion of a shared name. They would now provide the “local store” experience, while investing in their digital strategy as a means to do business online and bring the unique North 40 Outfitters experience and value nationwide.
With those organizational changes taking place, lay an even greater challenge. With over 150,000 SKUs and no digital database for their product information, North 40 Outfitters had to find a solution and build everything from the ground up. Moreover, with customers demanding a means to buy products online, especially customers living in rural areas, it became clear that North 40 Outfitters would have to address its data concerns.
Along with the fresh rebrand and restructure, North 40 Outfitters needed to tame their product information situation, a critical step conducive to building their digital product database and launching their ecommerce store.
North 40 Outfitters was clear about the outcome of the recent rebranding and they knew that investments needed to be taken if they were to add value to their existing business. Building the capabilities to take their business to new channels, ecommerce in this case, meant finding the best solution to start on the right foot. Consequently, wishing to become master of their own data, for both online and in-store uses, North 40 Outfitters determined that they needed a PIM application that would act as a unique data information repository.
It’s important to note that North 40 Outfitters environment is not typical to that of traditional retailers. The difference can be found in the large variation of product type they sell. Some of their suppliers have local, boutique style production scales, while some are large multi-national distributors. Furthermore, a large portion of North 40 Outfitters customers live in rural regions, in some cases their stores are a day’s drive away. With the ability to leverage both a PIM and an ecommerce solution North 40 Outfitters is now a step closer to outfitting everyone in the Northwestern region.
It is still very early to talk about results, since North 40 Outfitters has only recently entered the implementation phase. What can be said is that they are very excited. Having reclaimed their territory, and equipped with a PIM solution and an ecommerce solution they have all the right tools to till and plow the playing field.
The meaning of North 40 Outfitters
To the uninitiated the name North 40 Outfitters might not mean much. However, there is a lot of local heritage and history standing behind this newly rebranded name. North 40 is derived from the Homestead Act of 1862. The Act refers to the “North forty”, to the Northern most block of the homesteader’s property. To this day, this still holds significance to the local community. The second half of the brand: “Outfitters” is about the company’s focus on the company ability to outfit its customers both for work and play. On the one hand, you can visit North 40 Outfitters to purchase goods aimed at running your ranch, such as fencing material, horse related goods or quality tools. At the same time, you can buy camping and backpacking goods—they even sell ice fishing huts.
North 40 Outfitters ensures their customers have what they need to work the land, get back from it and ultimately go out and play just as hard if not harder.
Happy Holidays, Happy HoliData
In case you have missed our #HappyHoliData series on Twitter and LinkedIn, I decided to provide a short summary of best practices which are unleashing information potential. Simply scroll and click on the case study which is relevant for you and your business. The series touches on different industries and use cases. But all have one thing in common: All consider information quality as key value to their business to deliver the right services or products to the right customer.
Thanks a lot to all my great teammates, who made this series happen.
Happy Holidays, Happy HoliData.