Author: Michael Pastore

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Software Deployment Strategy: How to Get It Right the First Time

Big or Small, Enterprise Architecture Is a Key Part of a Successful Software Deployment Strategy

A good software deployment strategy could be the difference between multiple and costly false starts and a smooth implementation. Considering the rate at which emerging technologies are introduced, it’s becoming more important than ever for organizations to have a software deployment strategy in place.

But what does it involve?

Not all software deployments and investments are equal. Large-scale, big-money investments like ERP require a lot of resources and planning. Small-scale investments, like website technology, on the other hand, can be purchased, expensed and deployed with few people knowing. And of course, there are thousands of software decisions made that fall somewhere in between.

Software purchase decisions and deployments represent an opportunity to leverage the experience and knowledge of your enterprise architecture (EA) team so you can make smarter, better investments. The key here is the EA team’s complete view of your IT landscape, which can help eliminate redundant purchases, identify issues of integration and more.

 

Software Deployment Strategy: How to Get It Right the First Time

Small Projects Can Create Big Headaches

Here’s an example of how a small-scale software investment can wreak havoc on an organization.

There is an intense focus today on customer experience (CX). Ensuring that your website visitors have access to the information they want, and they can find it quickly and easily, is just part of your overall CX. This makes your customer-facing technologies – the ones that power your website or mobile app – critical investments, even though they may not carry the price tag of an ERP system.

Even the smallest investments need to be vetted to make sure they work with existing infrastructure and processes. One small piece of website tech that ends up degrading your online CX can cost your organization millions in a very short amount of time. There’s simply too many choices just a click away today if something isn’t working properly. Differentiating technologies are also more likely to be customized than an application like ERP, which can often use a number of out-of-the-box processes.

These are areas where a software deployment strategy involving your EA team can help guide the software purchase and deployment process. But even in a world where software deployments increasingly mean logging into a cloud-based SaaS application, a software deployment strategy is still beneficial.

Don’t Be Resigned to Failure

Many SaaS vendors like to talk about how easy it is to get up and running with their products, especially when the infrastructure elements are in the cloud. But the reality is that the network that connects to the SaaS application, the security, the integrations with existing (often on-premise) applications, the SLAs and licensing, can all benefit from a review by the EA team.

Failed software deployments are, in fact, a significant problem for many organizations. Such failures can often be attributed to a lack of planning and foresight.

Considering the costs associated with some software – including its purchase, implementation and consultancy fees/training required to get started – a good software deployment strategy could save millions … literally.

A Gartner study found that nearly half (46 percent) of respondents said their most expensive, time-intensive software deployments were not delivering. When Gartner broke the software purchases in question into deal sizes of over and under $1 million, the firm got similar results.

When your EA team has the visibility to see across your IT landscape and understand the business processes built on your technology, it can help provide a better idea of the real costs behind your software deployments and you can better estimate your time to value. When it comes to software investments, you don’t be resigned to failure.

erwin EA gives organizations a full-featured, versatile platform for enterprise architecture in its broadest sense to ensure the success of projects – regardless of their size or scope.

Start your free trial of erwin EA now.

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The Design Thinking Process: Five Stages to Solving Business Problems

The design thinking process is a method of encouraging and improving creative problem-solving.

The design thinking process is by no means new.

John Edward Arnold, a professor of mechanical engineering and business administration, was one of the first to discuss the concept in as early as the 1950s.

But the wave of digital and data-driven business has created new opportunities for the design thinking process to be applied.

For example, your business is likely collecting, storing and analyzing more information than ever before.

And while the intense focus on analytics in recent years has been good for many businesses, it’s important to remember the human element of making decisions and solving problems.

So with that in mind, the design thinking process can be used to bridge the gap between the data and the people.

But what is the design thinking process, exactly? And how does it work?

Design Thinking Definition: The Five Stages of the Design Thinking Process

There are lots of ways to harness ideas and solve problems. Design thinking is one means to foster and refine creative problem-solving.

While it doesn’t suggest ignoring your data, design thinking is, at its core, human-centered. It encourages organizations to focus on the people they’re creating for in hopes of producing better products, services and internal processes.

5 Stages in the Design Thinking Process

There are five stages in the design thinking process:

1. Empathize – The first stage of the design thinking process is gaining a better understanding of what problems need solving. It puts the end user you are trying to help first and encourages you to work backwards. By consulting and subsequently empathizing with the end user, you ensure your eventual solution is goal-oriented, increasing the likelihood of its effectiveness.

2. Define the problem – Once you have a better understanding of potential issues, it’s time to get specific. At this point, it’s good practice to translate the problem into a “problem statement” – a concise description of the issue that identifies the current state you wish to address and the desired future state you intend to reach.

3. Ideate solutions – This is the time to get creative. Once you have a solid understanding of the problem you can brainstorm ideas to bridge the gap between the current and the desired future state to eliminate it.

4. Prototype – At stage four, it’s time to implement the ideas from stage three in the real world. Typically, the prototype will be a scaled-down example of the solution – or ideally, possible solutions. It goes without saying, but things are rarely perfect in their first iteration, as you’ll likely discover in the next stage.

5. Test – At this point, it’s time to test whether the proposed solution works. In the case of multiple potential solutions, this stage can identify which is most effective and/or efficient. It’s also an opportunity to assess what – if any – new problems the solution might cause.

With this in mind, it’s important to remember that progression through the five stages of the design thinking process isn’t necessarily linear.

Unsuccessful tests could lead your team back to the ideation stage. In some cases, you may want to circle back to stage one to test your new solution with end users. Then you’ll be able to better emphasize and understand how your solution might work in practice.

It’s also important to understand that the design thinking process is not, strictly speaking, the same as innovation. It’s an approach to problem-solving that may ultimately involve innovation or emerging technologies, but innovation is not inherently required.

Design thinking is an iterative process, and the best solutions that come out of it in many organizations will become part of their enterprise architectures.

Incorporating Design Thinking into Your Organization with Enterprise Architecture

The best way to put design thinking into use in your organization is by creating a strategic planning approach that takes ideas from assessment to analysis to delivery.

By employing an iterative approach with a thorough assessment and a feedback loop, everyone in your organization will feel more empowered and engaged.

The reality of business today is that nearly every business problem is going to have a technological solution.

It will fall to the IT organization to take the ideas that come out of your design thinking and figure out how to deliver them as solutions at scale and speed.

This is where enterprise architecture comes into play.

Evaluating, planning and deploying a business solution will require visibility. How will these solutions impact users? Can they be supported by the existing IT infrastructure? How do they fit into the business ecosystem?

When it comes to these important questions, the best place to get answers is from your enterprise architecture team. Be sure to make them a central part of your design thinking process.

In addition to enterprise architecture software, erwin also provides enterprise architecture consulting. You can learn more about those services here.

You also can try all the current features of erwin EA for free via our secure, cloud-based trial environment.

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Managing Ideation and Innovation with Enterprise Architecture

Organizations largely recognize the need for enterprise architecture tools, yet some still struggle to communicate their value and prioritize such initiatives.

As data-driven business thrives, organizations will have to overcome these challenges because managing IT trends and emerging technologies makes enterprise architecture (EA) increasingly relevant.

“By 2021, 40 percent of organizations will use enterprise architects to help ideate new business innovations made possible by emerging technologies,” says Marcus Blosch, Vice President Analyst, Gartner.

With technology now vital to every aspect of the business, enterprise architecture tools and EA as a function help generate and evaluate ideas that move the business forward.

Every business has its own (often ad hoc) way of gathering ideas and evaluating them to see how they can be implemented and what it would take to deploy them.

But organizations can use enterprise architecture tools to bridge the gap between ideation and implementation, making more informed choices in the process.

By combining enterprise architecture tools with the EA team’s knowledge in a process for managing ideas and innovation, organizations can be more strategic in their planning.

Emerging technologies is one of the key areas in which such a process benefits an organization. The timely identification of emerging technologies can make or break a business. The more thought that goes into the planning of when and how to use emerging technologies, the better the implementation, which leads to better outcomes and greater ROI.

Gartner emphasize the value of enterprise architecture tools

Enterprise Architecture Tools: The Fabric of Your Organization

At its 2019 Gartner Enterprise Architecture & Technology Innovation Summit, Gartner identified 10 emerging and strategic technology trends that will shape IT in the coming years.

They included trends that utilize intelligence, such as autonomous things and augmented analytics; digital trends like empowered edge and immersive experiences; mesh trends like Blockchain and smart spaces; as well as broad concepts like digital ethics and privacy and quantum computing.

As these trends develop into applications or become part of your organization’s fabric, you need to think about how they can help grow your business in the near and long term. How will your business investigate their use? How will you identify the people who understand how they can be used to drive your business?

Many organizations lack a structured approach for gathering and investigating employee ideas, especially those around emerging technologies. This creates two issues:

1. When employee ideas fall into a black hole where they don’t get feedback, the employees become less engaged.

2. The emerging technology and its implementation are disconnected, which leads to silos or wasted resources.

How Enterprise Architecture Tools Help Communicate the Value of Emerging Technologies

When your enterprise architecture is aligned with your business outcomes it provides a way to help your business ideate and investigate the viability of ideas on both the technical and business level. When aligned correctly, emerging technologies can be evaluated based on how they meet business needs and what the IT organization must do to support them.

But the only way you can accurately make those determinations is by having visibility into your IT services and the application portfolio. And that’s how enterprise architecture can help communicate the value of emerging technologies in your organization.

erwin EA provides a way to quickly and efficiently understand opportunities offered by new technologies, process improvements and portfolio rationalization and translate them into an actionable strategy for the entire organization.

Take erwin EA for a free spin thanks to our secure, cloud-based trial.

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Managing Emerging Technology Disruption with Enterprise Architecture

Emerging technology has always played an important role in business transformation. In the race to collect and analyze data, provide superior customer experiences, and manage resources, new technologies always interest IT and business leaders.

KPMG’s The Changing Landscape of Disruptive Technologies found that today’s businesses are showing the most interest in emerging technology like the Internet of Things (IoT), artificial intelligence (AI) and robotics. Other emerging technologies that are making headlines include natural language processing (NLP) and blockchain.

In many cases, emerging technologies such as these are not fully embedded into business environments. Before they enter production, organizations need to test and pilot their projects to help answer some important questions:

  • How do these technologies disrupt?
  • How do they provide value?

Enterprise Architecture’s Role in Managing Emerging Technology

Pilot projects that take a small number of incremental steps, with small funding increases along the way, help provide answers to these questions. If the pilot proves successful, it’s then up to the enterprise architecture team to explore what it takes to integrate these technologies into the IT environment.

This is the point where new technologies go from “emerging technologies” to becoming another solution in the stack the organization relies on to create the business outcomes it’s seeking.

One of the easiest, quickest ways to try to pilot and put new technologies into production is to use cloud-based services. All of the major public cloud platform providers have AI and machine learning capabilities.

Integrating new technologies based in the cloud will change the way the enterprise architecture team models the IT environment, but that’s actually a good thing.

Modeling can help organizations understand the complex integrations that bring cloud services into the organization, and help them better understand the service level agreements (SLAs), security requirements and contracts with cloud partners.

When done right, enterprise architecture modeling also will help the organization better understand the value of emerging technology and even cloud migrations that increasingly accompany them. Once again, modeling helps answer important questions, such as:

  • Does the model demonstrate the benefits that the business expects from the cloud?
  • Do the benefits remain even if some legacy apps and infrastructure need to remain on premise?
  • What type of savings do you see if you can’t consolidate enough close an entire data center?
  • How does the risk change?

Many of the emerging technologies garnering attention today are on their way to becoming a standard part of the technology stack. But just as the web came before mobility, and mobility came before AI,  other technologies will soon follow in their footsteps.

To most efficiently evaluate these technologies and decide if they are right for the business, organizations need to provide visibility to both their enterprise architecture and business process teams so everyone understands how their environment and outcomes will change.

When the enterprise architecture and business process teams use a common platform and model the same data, their results will be more accurate and their collaboration seamless. This will cut significant time off the process of piloting, deploying and seeing results.

Outcomes like more profitable products and better customer experiences are the ultimate business goals. Getting there first is important, but only if everything runs smoothly on the customer side. The disruption of new technologies should take place behind the scenes, after all.

And that’s where investing in pilot programs and enterprise architecture modeling demonstrate value as you put emerging technology to work.

Emerging technology - Data-driven business transformation

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Enterprise Architect: A Role That Keeps Evolving

Enterprise architect is a common job title within IT organizations at large companies, but the term lacks any standard definition. Ask someone on the business side what their organization’s enterprise architects do, and you’ll likely get a response like, “They work with IT,” which is true, but also pretty vague.

What the enterprise architects at your organization do depends in large part on how the IT department is organized. At some organizations, enterprise architects work closely with the software applications in a role that some might refer to as a solution architect.

In other organizations, the role of enterprise architect might carry more traditional IT responsibilities around systems management. Other enterprise architects, especially at large organizations, might specialize in exploring how emerging technologies can be tested and later integrated into the business.

Technology research and advisory firm Gartner predicts that enterprise architects will increasingly move into an internal consultancy function within large organizations. While this use of the role is not currently widespread, it’s easy to see how it could make sense for some businesses.

If, for example, a business sets a goal to increase its website sales by 20 percent in one year’s time, meeting that goal will require that different IT and business functions work together.

The business side might tackle changes to the marketing plan and collect data about website visitors and shoppers, but ultimately they will need to collaborate with someone on the technology side to discuss how IT can help reach that goal. And that’s where an enterprise architect in the role of an internal consultant comes into play.

Each business is going to organize its enterprise architects in a way that best serves the organization and helps achieve its goals.

That’s one of the reasons the enterprise architect role has no standard definition. Most teams consist of members with broad IT experience, but each member will often have some role-specific knowledge. One team member might specialize in security, for example, and another in applications.

Like the tech industry in general, the only constant in enterprise architecture is change. Roles and titles will continue to evolve, and as the business and IT sides of the organization continue to come together in the face of digital transformation, how these teams are organized, where they report, and the types of projects they focus on are sure to change over time.

Enterprise integration architect is one role in enterprise architecture that’s on the rise. These architects specialize in integrating the various cloud and on-premise systems that are now common in the hybrid/multi-cloud infrastructures powering the modern enterprise.

Enterprise Architect: A Role That Keeps Evolving

For the Enterprise Architect, Business Experience Becomes a Valuable Commodity

Regardless of the specific title, enterprise architects need the ability to work with both their business and IT colleagues to help improve business outcomes. As enterprise architecture roles move closer to the business, those with business knowledge are becoming valuable assets. This is especially true for industry-specific business knowledge.

As industry and government compliance regulations, for example, become part of the business fabric in industries like financial services, healthcare and pharmaceuticals, many enterprise architects are developing specializations in these industries that demonstrate their understanding of the business and IT sides of these regulations.

This is important because compliance permeates every area of many of these organizations, from the enterprise architecture to the business processes, and today it’s all enabled by software. Compliance is another area where Gartner’s internal consultancy model for enterprise architects could benefit a number of organizations. The stakes are simply too high to do anything but guarantee all of your processes are compliant.

Enterprise architect is just one role in the modern organization that increasingly stands with one foot on the business side and the other in IT. As your organization navigates its digital transformation, it’s important to use tools that can do the same.

erwin, Inc.’s industry-leading tools for enterprise architecture and business process modeling use a common repository and role-based views, so business users, IT users and those who straddle the line have the visibility they need. When everyone uses the same tools and the same data, they can speak the same language, collaborate more effectively, and produce better business outcomes. That’s something the whole team can support, regardless of job title.

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Enterprise Architecture and Business Process: Common Goals Require Common Tools

For decades now, the professional world has put a great deal of energy into discussing the gulf that exists between business and IT teams within organizations.

They speak different languages, it’s been said, and work toward different goals. Technology plans don’t seem to account for the reality of the business, and business plans don’t account for the capabilities of the technology.

Data governance is one area where business and IT never seemed to establish ownership. Early attempts at data governance treated the idea as a game of volleyball, passing ownership back and forth, with one team responsible for storing data and running applications, and one responsible for using the data for business outcomes.

Today, we see ample evidence this gap is closing at many organizations. Consider:

  • Many technology platforms and software applications now are designed for business users. Business intelligence is a prime example; it’s rare today to see IT pros have to run reports for business users thanks to self-service.
  • Many workers, especially those that came of age surrounded by technology, have a better understanding of both the business and technology that runs their organizations. Education programs also have evolved to help students develop a background in both business and technology.
  • There’s more portability in roles, with technology minds moving to business leadership positions and vice versa.

“The business domain has always existed in enterprise architecture,” says Manuel Ponchaux, director of product management at erwin, Inc. “However, enterprise architecture has traditionally been an IT function with a prime focus on IT. We are now seeing a shift with a greater focus on business outcomes.”

You can see evidence of this blended focus in some of the titles, like “business architect,” being bestowed upon what was traditionally at IT function. These titles demonstrate an understanding that technology cannot exist in the modern organization for the sake of technology alone – technology needs to support the business and its customers. This concept is also a major focus of the digital transformation wave that’s washing over the business world, and thus we see it reflected in job titles that simply didn’t exist a decade ago.

Job titles aside, enterprise architecture (EA) and business process (BP) teams still have different goals, though at many organizations they now work more closely together than they did in the past. Today, both EA and BP teams recognize that their common goal is better business outcomes. Along the way to that goal, each team conducts a number of similar tasks.

Enterprise Architecture and Business Process: Better Together

One prominent example is modeling. Both enterprise architecture and business process teams do modeling, but they do it in different ways at different levels, and they often use different data and tools. This lack of coordination and communication makes it difficult to develop a true sense of a process from the IT and business sides of the equation. It can also lead to duplication of efforts, which is inefficient and likely to add further confusion when trying to understand outcomes.

Building better business outcomes is like following a plan at a construction site. If different teams are making their own decisions about the materials they’re going to use and following their own blueprints, you’re unlikely to see the building you expect to see at the end of the job.

And that’s essentially what is missing at many organizations: A common repository with role-based views, interfaces and dashboard so that enterprise architecture and business process can truly work together using the same blueprint. When enterprise architecture and business process can use common tools that both aid collaboration and help them understand the elements most important to their roles, the result is greater accuracy, increased efficiency and improved outcomes.

erwin’s enterprise architecture and business process tools provide the common repository and role-based views that help these teams work collaboratively toward their common goals. Finally, enterprise architecture and business process can be on the same page.

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Digital Transformation in Municipal Government: The Hidden Force Powering Smart Cities

Smart cities are changing the world.

When you think of real-time, data-driven experiences and modern applications to accomplish tasks faster and easier, your local town or city government probably doesn’t come to mind. But municipal government is starting to embrace digital transformation and therefore data governance.

Municipal government has never been an area in which to look for tech innovation. Perpetually strapped for resources and budget, often relying on legacy applications and infrastructure, and perfectly happy being available during regular business hours (save for emergency responders), most municipal governments lacked the ability and motivation to (as they say in the private sector) digitally transform. Then an odd thing happened – the rest of the world started transforming.

If you shop at a retailer that doesn’t deliver a modern, personalized experience, thousands more retailers are just a click away. But people rarely pick up and move to a new city because the new city offers a better website or mobile app. The motivation for municipal governments to transform simply isn’t there in the same way it is for the private sector.

But there are some things many city residents care about deeply: public safety, quality of life, how their tax dollars are spent, and the ability to do business with their local government when they want, not when it’s convenient for the municipality. And much like the private sector, better decisions around all of these concerns can be made when accurate, timely data is available to help inform them.

Digital transformation in municipal government is taking place in two main areas today: constituent services and the “smart cities” movement.

Digital Transformation in Municipal Government: Being “Smart” About It

The ability to serve constituents easily and efficiently is of increasing importance and a key objective of digital transformation in municipal government. It’s a direct result of the data-driven customer experiences that are increasingly the norm in the private sector.

Residents want the ability to pay their taxes online, report a pothole from their phone, and generally make it easier to interact with their local officials and services. This can be accomplished with dashboards and constituent portals.

The smart cities movement refers to the broad effort of municipal governments to incorporate sensors, data collection and analysis to improve responses to everything from rush-hour traffic to air quality to crime prevention. When the McKinsey Global Institute examined smart technologies that could be deployed by cities, it found that the public sector would be the natural owner of 70 percent of the applications it reviewed.

“Cities are getting in on the data game,” says Danny Sandwell, product marketing director at erwin, Inc. And with information serving as the lifeblood of many of these projects, the effectiveness of the services offered, the return on the investments in hardware and software, and the happiness of the users all depend on timely, accurate and effective data.

These initiatives present a pretty radical departure from the way cities have traditionally been managed.

A constituent portal, for example, requires that users can be identified, authenticated and then have access to information that resides in various departments, such as the tax collector to view and pay taxes, the building department to view a building permit, and the parking authority to manage public parking permits.

For many municipalities, this is uncharted territory.

Smart Cities

Data Governance: The Force Powering Smart Cities

The efficiencies offered by smart city technologies only exist if the data leads to a proper allocation of resources.

If you can identify an increase in crime in a certain neighborhood, for example, you can increase police patrols in response. But if the data is inaccurate, those patrols are wasted while other neighborhoods experience a rise in crime.

Now that they’re in the data game, it’s time for municipal governments to understand data governance – the driving force behind any successful data-driven operation. When you have the ability to understand all of the information related to a piece of data, you have more confidence in how it is analyzed, used and protected.

Data governance doesn’t take place at a single application or in the data warehouse. It needs to be woven into the enterprise architecture and processes of the municipality to ensure data is accurate, timely and accessible to those who need it (and inaccessible to everyone else).

When this all comes together – good data, solid analytics and improved services for residents – the results can be quite striking. New efficiencies will make municipal governments better stewards of tax dollars. An improved quality of life can lift tax revenue by making the city more appealing to citizens and developers.

There’s a lot for cities to gain if they get in the data game. And truly smart cities will make sure they play the game right with effective data governance.

Benefits of Data Governance

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Digital Transformation In Retail: The Retail Apocalypse

Much like the hospitality industry, digital transformation in retail has been a huge driver of change.

One important fact is getting lost among all of the talk of “the retail apocalypse” and myriad stories about increasingly empty shopping malls: there’s a lot of money to be made in retail. In fact, the retail market was expected to grow by more than 3 percent in 2018, unemployment is low, and wages are at least stable.

In short, there’s money to be spent. Now, where are shoppers spending it?

Coming into 2019, consumers are in control when it comes to retail. Choices are abundant. According to Deloitte’s 2018 Retail, Wholesale and Distribution Industry Trends Outlook, “consumers have been conditioned to expect fast, convenient and effortless consumption.”

This is arguably the result of the degree of digital transformation in retail that we’ve seen in recent years.

If you want to survive in retail today, you need to make it easy on your customers. That means meeting their needs across channels, fulfilling orders quickly and accurately, offering competitive prices, and not sacrificing quality in the process.

Even in a world where Amazon has changed the retail game, Walmart just announced that it had its best holiday season in years. According to a recent Fortune article, “Walmart’s e-commerce sales rose 43 percent during the quarter, belying another myth: e-commerce and store sales are in competition with each other.”

Retail has always been a very fickle industry, with the right product mix and the right appeal to the right customers being crucial to success. But digital transformation in retail has seen the map change. You’re no longer competing with the store across the street; you’re competing with the store across the globe.

Digital Transformation In Retail

Retailers are putting every aspect of their businesses under scrutiny to help them remain relevant. Four areas in particular are getting a great deal of attention:

Customer experience: In today’s need-it-fast, need-it-now, need-it-right world, customers expect the ability to make purchases where they are, not where you are. That means via the Web, mobile devices or in a store. And all of the information about those orders needs to be tied together, so that if there is a problem, it can be resolved quickly via any channel.

Competitive differentiation: Appealing to retail customers used to mean appealing to all of your customers as one group or like-minded block. But customers are individuals, and today they can be targeted with personalized messaging and products that are likely to appeal to them, not to everyone.

Supply chain: Having the right products in the right place at the right time is part of the supply chain strategy. But moving them efficiently and cost effectively from any number of suppliers to warehouses and stores can make or break margins.

Partnerships: Among the smaller players in the retail space, partnerships with industry giants like Amazon can help reach a global audience that simply isn’t otherwise available and also reduce complexity. Larger players also recognize that partnerships can be mutually beneficial in the retail space.

Enabling each of these strategies is data – and lots of it. Data is the key to recognizing customers, personalizing experiences, making helpful recommendations, ensuring items are in stock, tracking deliveries and more. At its core, this is what digital transformation in retail seeks to achieve.

Digital Transformation in Retail – What’s the Risk?

But if data is the great enabler in retail, it’s also a huge risk – risk that the data is wrong, that it is old, and that it ends up in the hands of some person or entity that isn’t supposed to have it.

Danny Sandwell, director of product marketing for erwin, Inc., says retailers need to achieve a level of what he calls “data intelligence.” A little like business intelligence, Sandwell uses the term to mean that when someone in retail uses data to make a decision or power an experience or send a recommendation, they have the ability to find out anything they need about that data, including its source, age, who can access it, which applications use it, and more.

Given all of the data that flows into the modern retailer, this level of data intelligence requires a holistic, mature and well-planned data governance strategy. Data governance doesn’t just sit in the data warehouse, it’s woven into business processes and enterprise architecture to provide data visibility for fast, accurate decision-making, help keep data secure, identify problems early, and alert users to things that are working.

How important is clean, accurate, timely data in retail? Apply it to the four areas discussed above:

Customer experience:  If your data shows a lot of abandoned carts from mobile app users, then that’s an area to investigate, and good data will identify it.

Competitive differentiation: Are personalized offers increasing sales and creating customer loyalty? This is an important data point for marketing strategy.

Supply chain: Can a problem with quality be related to items shipping from a certain warehouse? Data will zero in on the location of the problem.

Partnerships: Are your partnerships helping grow other parts of your business and creating new customers? Or are your existing customers using partners in place of visiting your store? Data can tell you.

Try drawing these conclusions without data. You can’t. And even worse, try drawing them with inaccurate data and see what happens when a partnership that was creating customers is ended or mobile app purchases plummet after an ill-advised change to the experience.

If you want to focus on margins in retail, don’t forget this one: there is no margin for error.

Over the next few weeks, we’ll be looking closely at digital transformation examples in other sectors, including hospitality and government. Subscribe to to stay in the loop.

Data Management and Data Governance: Solving the Enterprise Data Dilemma

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Digital Transformation Examples: How Data Is Transforming the Hospitality Industry

The rate at which organizations have adopted data-driven strategies means there are a wealth of digital transformation examples for organizations to draw from.

By now, you probably recognize this recurring pattern in the discussions about digital transformation:

  • An industry set in its ways slowly moves toward using information technology to create efficiencies, automate processes or help identify new customer or product opportunities.
  • All is going fine until a new kid on the block, born in the age of IT and the internet, quickly starts to create buzz and redefine what customers expect from the industry.
  • To keep pace, the industry stalwarts rush into catch-up mode but make inevitably mistakes. ROI doesn’t meet expectations, the customer experience isn’t quite right, and data gets exposed or mishandled.

There’s one industry we’re all familiar with that welcomes billions of global customers every year; that’s in the midst of a strong economic run; is dealing with high-profile disruptors; and suffered a very public data breach to one of its storied brands in 2018 that raised eyebrows around the world.

Welcome to the hospitality industry.

The hotel and hospitality industry was expected to see 5 to 6 percent growth in 2018, part of an impressive run of performance fueled by steady demand, improved midmarket offerings, and a new supply of travelers from developing regions.

All this despite challenges from upstarts like AirB2B, HomeAway and Couchsurfing plus a data breach at Marriott/Starwood that exposed the data of 500 million customers.

Digital Transformation Examples: Data & the Hospitality Industry

Online start-ups such as Airbnb, HomeAway and Couchsurfing are some of the most clear cut digital transformation examples in the hospitality industry.

Digital Transformation Examples: Hospitality – Data, Data Everywhere

As with other industries, digital transformation examples in the hospitality industry are abundant – and in turn, those businesses are awash in data with sources that include:

  • Data generated by reservations and payments
  • The data hotels collect to drive their loyalty programs
  • Data used to enhance the customer experience
  • Data shared as part of the billions of handoffs between hotel chains and the various booking sites and agencies that travelers use to plan trips

But all of this data, which now permeates the industry, is relatively new.

“IT wasn’t always a massive priority for [the hospitality industry],” says Danny Sandwell, director of product marketing for erwin, Inc. “So now there’s a lot of data, but these organizations often have a weak backend.”

The combination of data and analytics carries a great deal of potential for companies in the hospitality industry. Today’s demanding customers want experiences, not just a bed to sleep in; they want to do business with brands that understand their likes and dislikes; and that send offers relevant to their interests and desired destinations.

All of this is possible when a business collects and analyzes data on the scale that many hotel brands do. However, all of this can fail loudly if there is a problem with that data.

Getting a return on their investments in analytics and marketing technology requires hospitality companies to thoroughly understand the source of their data, the quality of the data, and the relevance of the data. This is where data governance comes into play.

When hospitality businesses are confident in their data, they can use it a number of ways, including:

  • Customer Experience: Quality data can be used to power a best-in-class experience for hotels in a number of areas, including the Web experience, mobile experience, and the in-person guest experience. This is similar to the multi-channel strategy of retailers hoping to deliver memorable and helpful experiences based on what they know about customers, including the ability to make predictions and deliver cross-sell and up-sell opportunities. 
  • Mergers and Acquisitions: Hospitality industry disruptors have some industry players thinking about boosting their businesses via mergers and acquisitions. Good data can identify the best targets and help discover the regions or price points where M&A makes the most sense and will deliver the most value. Accurate data can also help pinpoint the true cost of M&A activity.
  • Security: Marriott’s data breach, which actually began as a breach at Starwood before Marriott acquired it, highlights the importance of data security in the hospitality industry. Strong data governance can help prevent breaches, as well as help control breaches so organizations more quickly identify the scope and action behind a breach, an important part of limiting damage.
  • Partnerships: The hospitality industry is increasingly connected, not just because of booking sites working with dozens of hotel brands but also because of tour operators turning a hotel stay into an experience and transportation companies arranging travel for guests. Providing a room is no longer enough.

Data governance is not an application or a tool. It is a strategy. When it is done correctly and it is deployed in a holistic manner, data governance becomes woven into an organization’s business processes and enterprise architecture.

It then improves the organization’s ability to understand where its data is, where it came from, its value, its quality, and how the data is accessed and used by people and applications.

It’s this level of data maturity that provides comfort to employees – from IT staff to the front desk and everyone in between – that the data they are working with is accurate and helping them better perform their jobs and improve the way they serve customers.

Over the next few weeks, we’ll be looking closely at digital transformation examples in other sectors, including retail and government. Subscribe to to stay in the loop.

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For Pharmaceutical Companies Data Governance Shouldn’t Be a Hard Pill to Swallow

Using data governance in the pharmaceutical industry is a critical piece of the data management puzzle.

Pharmaceutical and life sciences companies face many of the same digital transformation pressures as other industries, such as financial services and healthcare that we have explored previously.

In response, they are turning to technologies like advanced analytics platforms and cloud-based resources to help better inform their decision-making and create new efficiencies and better processes.

Among the conditions that set digital transformation in pharmaceuticals and life sciences apart from other sectors are the regulatory environment and the high incidence of mergers and acquisitions (M&A).

Data Governance, GDPR and Your Business

Protecting sensitive data in these industries is a matter of survival, in terms of the potential penalties for failing to comply with any number of industry and government regulations and because of the near-priceless value of data around research and development (R&D).

The high costs and huge potential of R&D is one of the driving factors of M&A activity in the pharmaceutical and life sciences space. With roughly $156 billion in M&A deals in healthcare in the first quarter of 2018 alone – many involving drug companies – the market is the hottest it’s been in more than a decade. Much of the M&A activity is being driven by companies looking to buy competitors, acquire R&D, and offset losses from expiring drug patents.

 

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With M&A activity comes the challenge of integrating two formerly separate companies into one. That means integrating technology platforms, business processes, and, of course, the data each organization brings to the deal.

Data Integrity for Risk Management and More

As in virtual every other industry, data is quickly becoming one of the most valuable assets within pharmaceutical and life science companies. In its 2018 Global Life Sciences Outlook, Deloitte speaks to the importance of “data integrity,” which it defines as data that is complete, consistent and accurate throughout the data lifecycle.

Data integrity helps manage risk in pharmaceutical and life sciences by making it easier to comply with a complex web of regulations that touch many different parts of these organizations, from finance to the supply chain and beyond. Linking these cross-functional teams to data they can trust eases the burden of compliance by supplying team members with what many industries now refer to as “a single version of truth” – which is to say, data with integrity.

Data integrity also helps deliver insights for important initiatives in the pharmaceutical and life sciences industries like value-based pricing and market access.

Developing data integrity and taking advantage of it to reduce risk and identify opportunities in pharmaceuticals and life sciences isn’t possible without a holistic approach to data governance that permeates every part of these companies, including business processes and enterprise architecture.

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Data Governance in the Pharmaceutical Industry Maximizes Value

Data governance gives businesses the visibility they need to understand where their data is, where it came from, its value, its quality and how it can be used by people and software applications. This type of understanding of your data is, of course, essential to compliance. In fact, according to a 2017 survey by erwin, Inc. and UBM, 60 percent of organizations said compliance is driving their data governance initiatives.

Using data governance in the pharmaceutical industry helps organizations contemplating M&A, not only by helping them understand the data they are acquiring, but also by informing decisions around complex IT infrastructures and applications that need to be integrated. Decisions about application rationalization and business processes are easier to make when they are viewed through the lens of a pervasive data governance strategy.

Data governance in the pharmaceutical industry can be leveraged to hone data integrity and move toward what Deloitte refers to as end-to-end evidence management (E2E), which unifies the data in pharmaceuticals and life sciences from R&D to clinical trials and through commercialization.

Once implemented, Deloitte predicts E2E will help organizations maximize the value of their data by:

  • Providing a better understanding of emerging risks
  • Enabling collaboration with health systems, patient advocacy groups, and other constituents
  • Streamlining the development of new therapies
  • Driving down costs

If that list of benefits sounds familiar, it’s because it matches up nicely with the goals of digital transformation at many organizations – more efficient processes, better collaboration, improved visibility and better cost management. And it’s all built on a foundation of data and data governance.

To learn more, download our free whitepaper on the Regulatory Rationale for Integrating Data Management & Data Governance.

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