Almost 20 years ago, Capital One recognized the need for one person to oversee their data security, quality, and privacy, and the role of the Chief Data Officer was born. Now reports show that 68% of organizations have a CDO (Harvard Business Review, 2020). And while the role has become more common and has significantly evolved, many data executives are still struggling to get a seat at the table or bring data to the forefront of their organization. In fact, in a recent survey, only 28% of respondents agreed that the role was successful and established. Company leaders agree that there needs to be a single point of accountability to manage the various dimensions of data inside and outside of the enterprise, including the quality and availability of that data. But now we are at a crossroads — what is the best way to align the work that the CDO does with the strategy of the business as a whole? The reality is that CDOs often struggle to find the internal and external support and resources needed to educate others to align with the organization’s goals. Implementing enterprise data governance, data architecture, data asset development, data science, and advanced analytics capabilities — such as machine learning and video analytics — at scale, is not an easy task. To be successful, data executives need support, resources, and communities focused on the elevation of data. We are proud to continue to help these communities come to life for the benefit of our colleagues and clients, establishing local resources here in the Midwest with global scale, reach, and impact. Read on as Mark Johnson, our Executive Leader for Data Management and Analytics, provides insight on the current state of data and the CDO, and provides details on multiple opportunities for data leaders of different levels to get more involved in the data community. Q: How has the role of data changed/evolved for organizations? The reality is that information is everything. This global pandemic proved that to many organizations. For some, it showed that their digital network was ready, and they were aptly prepared to take on COVID. For others, it has forced them to recognize their own immaturity with data and analytics. On its own, managing data is not exciting — the information just sort of exists. To give data value, you have to put it to use. And so, I think we are going to see the Chief Data Officer and/or Chief Data Analytics Officer really find their own in the coming years. It’s time for their seat at the table. The C-suite is now asking questions that can only be answered with data, and now they truly understand both the value and consequences of the data game. Q: What do you think are the biggest challenges facing CDOs/data leaders today? I think that the biggest challenge for data executives today is the acquisition of talent that is seasoned and experienced where you need them to be for your organization. Higher education hasn’t necessarily kept up with the data world, and often times it takes additional training to reach the right levels. The reality is that right now the talent is manufactured in the real world. Data executives have to be connected and equipped to mentor, train, and keep the right people. Q: You’ve mentioned that data leaders need to connect with each other. What value can people expect from these data communities? I think there is tremendous value. As we are seeing the power of data evolve in organizations, and the role of data leaders evolve as well, I think coming together to collaborate and share elevates the leader, the organization, and the view of data as a whole. In these communities, it gives people a safe space to talk about how they are doing, what they are doing, what their biggest challenges are, and what solutions are working for them. These communities have truly become both a learning laboratory and an accelerator for data. Q: As a big proponent of connecting data leaders, you have been involved in creating different opportunities for people to get together. What groups/events would you recommend, and how can people get involved? I personally have been involved with the MIT Chief Data Officer and Information Quality Symposium (MIT CDOIQ), which is such a great opportunity to start with for connection. It has developed into additional opportunities for data leaders at all levels to get involved and create the kind of community we need to truly elevate the value of data. Organizations like the CDO Magazine, the creation of CDO roundtables across the nation, and the International Society of Chief Data Officers (isCDO) all evolved from connecting data leaders and identifying common challenges. MIT CDOIQ: The International MIT Chief Data Officer and Information Quality Symposium (MIT CDOIQ) is one of the key events for sharing and exchanging cutting-edge ideas and creating a space for discussion between data executives across industries. While resolving data issues at the Department of Defense, the symposium founder, Dr. Wang, recognized the need to bring data people together. Now in its 15th year, MIT CDOIQ is a premier event designed to advance knowledge, accelerate the adoption of the role of the Chief Data Officer, and change how data is leveraged in organizations across industries and geographies. Fusion has been a sponsor of this symposium for seven years now, and we are so excited to see how the event has grown. Designed for the CDO or top data executive in your organization, this is a space to really connect with other top industry leaders. CDO Roundtables Fusion has always been focused on building community and connecting people. And when one of our clients, a Fortune 500 retailer, mentioned wanting to talk with other data leaders from similar corporations, we realized that there was a big gap here — there was no space that existed where data leaders could informally come together, without sales pitches and vendor influence, and simply talk. That’s how the CDO roundtables were born — a place that allows data leaders to get to know each other, collaborate, accelerate knowledge growth, and problem solve. We just started two years ago in Cincinnati, but now, now we’ve expanded to multiple markets including Indianapolis, Columbus, Cleveland, Chicago, and Miami. These groups are designed for your CDO/CDAO and truly create an environment for unfiltered peer-to-peer discussion that helps solves data leadership challenges across industries. If you’re interested in joining one of these roundtables or starting one in your market, email me or message me on LinkedIn. I’m here and ready to get these roundtables started with executives in as many communities as I can. The more communities we have, the more data leaders and organizations we can serve. International Society of Chief Data Officers (isCDO) Launched out of the MIT CDOIQ symposium, the isCDO is a vendor-neutral organization designed to promote data leadership. I am excited to be a founding member of this organization, along with our Vice President of Strategy, David Levine. Our ultimate goal is to create a space that serves as a peer-advisory resource and enables enterprises to truly realize the value of data-driven decision making. With multiple membership options available, isCDO is the perfect opportunity for data leaders looking to connect with their peers and gain a competitive advantage by focusing on high-quality data and analytics. CDO Magazine I am really proud to be a founder of the CDO magazine, as it really is a resource for all business leaders, not just the CDO. We designed the magazine to be a resource for C-suite leaders — to educate and inform on the value proposition, strategies, and best practices that optimize long-term business value from investments in enterprise data management and analytics capabilities. Check out the publication here. And if you’re interested in contributing content or being interviewed, let me know at email@example.com. Closing: The role of the CDO is integral to organizations, but it’s still evolving. Now more than ever, it is important that data leaders come together to collaborate and problem-solve. Fusion is excited to be a part of each of these initiatives, and we are committed to being an agent of change in the communities we serve and beyond. By connecting global thought leaders we believe that organizations will realize the value of data to power their digital transformation. If you’re interested in joining any of these data communities or just have questions, feel free to reach out to Mark via email or on LinkedIn.
Articles about Page: Strategic data mangement
Return on investment (ROI) is top of mind for everyone. With so many competing priorities, how you spend your time and money, and what you get for it, matters more than ever. The focus used to completely be on the level of your investment. But the paradigm is shifting because of the data capabilities that now exist. In this article, we’ll explore how the definition of ROI has changed because of modern technology and approaches, where your data ROI comes from, and how to accelerate it. Setting goals for your data analytics efforts Data without analytics is ultimately an investment without return. Most organizations sit on troves of data, but can’t do anything with it. But analytics is a progression. Each of the levels on the data analytics maturity model represent questions you can begin to answer. To go from nothing to cognitive takes a lot — your investment increases substantially. Descriptive: What happened? Diagnostic: Why did it happen? Predictive: What will happen? Prescriptive: How can it happen? Cognitive: What can be suggested? With each step up the model, you add more information and complexity. For example, the descriptive level of maturity can be answered with a look at history. As you progress, you will need more information and stronger data relationships to better understand the “why.” Your data quality and integrity are also important. When you get to the cognitive step, you’re expanding outside your universe of data, and the contextual element of what you’re doing gets broader. For this step, consider Microsoft’s Cortana or IBM’s Watson. But in the modern data world, there doesn’t have to be a huge upfront investment. Shifting your focus from a return on investment to a return on insights can drastically impact how you invest in your data and your results. Calculating the ROI of data and analytics projects Ultimately, ROI is realized from leveraging effective data management to enable access to: more and better data maximizing visualizations advanced analytics actionable insights for outcomes For data management, that means: Improved quality and completeness Confidence and trust Accountability through governance Improved stewardship Advancing culture change to help stakeholders understand the importance and value proposition By improving your data management, the insights from your data become better and more actionable, including: Access to more data and the inclusion of new sources Faster and easier access to data Greater integration of disparate data Easier standup and use of analytics technology In years past, insights from data analytics might have been limited to data scientists or experts in the field. But now, with analytics tools and technologies, data insights are useful to — and actionable for — people across the entire organization. The larger the investment in time and money, the more emphasis on ROI, how quickly it can be realized, and the amount of trailing value. Data leaders have to work with their organizations to understand what the best strategy is – whether that be a smaller investment with a slower return or a big investment that allows you to realize your ROI sooner. It is critical to evaluate your organization’s needs, expectations, and goals before making decisions on strategic data management. Understanding the classic data ecosystem In a classic data ecosystem, the setup might look something like this. In a classic data ecosystem, it requires deep analysis to understand sources and the definition of data, and a considerable amount of time and effort to reach the gold standard you need for your data to be utilized for BI and analytics. Investments are required on all layers. There is no real way to invest in one aspect of your data and analytics and still find value. There is also significant effort required to ensure that as you introduce new systems, you don’t break legacy systems and processes already in place. Quite often, work must be done upfront to ensure that changes (even upgrades) will not cause disruption. In addition, significant “time-to-market” factors need to be considered with classic data ecosystems. Often, the slow delivery of data and features forces businesses to make incremental changes without undertaking any kind of larger project. Doing so might be helpful at first, but can cause issues later. With a slow delivery of data, many organizations using a classic data ecosystem find that they are unable to keep up with the pace of business today. Classic data ecosystems are often built to meet reporting needs, not analytical needs and the analytics piece is a one-off project. The deployment and incorporation of analytical models into production in a classic setup requires a considerable amount of time and customization. Building a modern data ecosystem In this more modern data ecosystem, there is a more layered approach. Now it is much easier to gather, ingest, and integrate the data, and bridge gaps between systems, along with including new concepts like data lakes that can include data layers at the bronze, silver, and gold levels. You don’t have to invest fully in all of the layers, you can invest where you need to. You still have BI & analytics capabilities, but you have more of an application integration framework that serves additional needs. And then there is the trust of the data. This setup allows for more flexibility and customization for all parts of the organization. Read more: How to build your data analytics capabilities The value of incremental change Your investment doesn’t have to be an all-or-nothing proposition. You can incrementally build out components and capabilities and can make data available for exploration without deep upfront analysis that often slows everything down. Additionally, you can control the degree of your investment in a significant way. Without having to push data through all the layers to make it useful and the use of flexible architecture, you don’t have to make a significant investment and change to make it worth it. You can also leverage external tools in the interim. Service and subscription-based features allow for fast initiation, and exploratory efforts can be stood up and torn down easily and quickly. New technologies and design/development paradigms enable faster adoption overall. And now, more user groups are able to access data and analytics, create more use cases, and make business decisions on the insights. Ultimately, it is time to shift your thinking on ROI and leverage modern data technology and tools and focus on the return on insights, intelligence, and innovation. For more information on data, analytics, and assigning ROI, Fusion’s Vice President of Data, Saj Patel, recently spoke at the CDO Summit. His presentation details how to accelerate ROI and gain buy-in across your organization. Watch the recording here and connect with us if you have any specific questions Learn more about Strategic Data Management here.
Digital natives like Uber and Lyft have all but changed the face of the taxi industry and the customer experience. Many are huge fans of these companies, and it’s no wonder. You don’t have to flag anyone down or have an awkward street scuffle to get a ride. Uber has skipped the web and gone straight to the mobile device as its target platform for order management and fulfillment. Every customer transaction goes into Uber’s database: name, address, credit card info, cell number, pickup location, drop-off location, where you travel and when — the list goes on. But it’s not just the ride that is valuable to Uber. Their database is where the real value is. And guess what? Uber was recently valued at $49 billion. Every company has data. And every company needs a data strategy to take advantage of its value. Some steps to create a winning strategy are: 1. Make data management and analytics a priority Increasingly, business and personal transactions and interactions are going through digital channels. As they move to digital channels, they leave behind a lot of data that was not available to companies before. New sources of data exist everywhere — social media, geolocation data, etc. There’s just a lot more digital content available now to help a business understand its performance, relationships, and reputation. But you need to know what to do with it. For example, as Uber’s database grows, it becomes more valuable. They can look at their customers’ digital footprint through analytics and, over time, they can see distinct types of users emerge from their travel and interaction patterns. They can then use these analytics to expand and refine their service offering to better serve the needs of users and travelers with similar digital footprints. 2. Overcome IT challenges There are many new choices of data technologies. You need to figure out how to incorporate them into your company’s existing technology stack. But even before that, you need to understand how to manage data as an asset and consider: How data is governed Who owns the data How to manage data quality and security How to handle demand management as new data requests come in and new data sources are identified In addition, you need to understand how it will be integrated into the infrastructure and environment. That said, it’s hard to find the people right now who understand all of these technologies. There is a shortage of data scientists and Hadoop engineers, for example. Having access to the resources with the skills to implement and manage these new technologies can be one of your biggest constraints and barriers. Legacy systems vs. open source There are also challenges associated with the whole technology space. Legacy vendors, such as Oracle, Teradata, and Microsoft, want to maintain their hold. They’re all fighting to remain relevant in a technology market space where open source is creating more compelling and cost-effective solutions for businesses. Microsoft, which has a huge research component, has had difficulty embracing the open source movement in the past. Today they are in full support of open source projects in Azure and Visual Studio and release many of their own code bases, such as .NET. Open source is actually much more valuable because it’s run by people who are constantly working on issues of security or lack of performance. These folks will immediately address your issues for one overriding reason, they are passionate about code — Wikipedia all over again! 3. Prepare for organizational change We’re not just dealing with our own transactional data anymore. We’re dealing with data from our industry or sector, as well as external data, such as weather. Though weather might not seem like it has anything to do with your business, weather data can provide great insight that can enable you to positively impact business. Many other datasets are also available, some for a fee, which organizations have discovered they must pay attention to, in addition to their own operational data. The technologies of today’s data management agenda are new and emerging and are not technologies for which IT traditionally has the skills. There’s a big divide between IT capability and what the business demands for integrating and managing data. As a result, roles like data scientist and data analyst, with the kinds of necessary skills, are not yet common within organizations, making organizational and change management a requirement. 4. Embrace the role of a CDO Until recently, we’ve pretended as if the people who are responsible for the technology (the wires, pliers, software, and ERP systems) actually care about the data, but they don’t. A CIO is not the best person to manage the data. There’s a new paradigm out there, the chief data officer or CDO. Data is such a critical corporate asset that it needs to be managed strategically and at the executive level outside of IT. Technology is an enabler, but data is an asset. Currently many account for them in the exact opposite paradigm. Many organizations are now appointing a CDO, reporting to the COO or CEO, and their role is to oversee and manage quality, integrity, and use of the organization’s data assets, just like the CFO governs the organization’s financial data. Start implementing a winning data strategy today The elements covered here will get your business off to a strategic start toward more effective management of your data and analytics. If you want to be successful, remain open to new ideas, get help from outside, and embrace new paradigms for how your business should interact with data as it continues to evolve. It’s critical to understand that you should absolutely take advantage of anything that can accelerate driving insights from the data already just sitting in your systems out into the marketplace. Having a strategic partner who brings the required expertise and ability to implement proven methodologies will enable your company to create successful data capabilities, and you’ll be able to groom and train internal resources at the same time. That’s what’s going to enable you to beat your competition.
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