Information Management: Strategies for Gaining a Competitive Advantage with Data (2014)

Chapter 1. You're in the Business of Information

An introductory chapter stressing the importance of information to any business and how good decisions are made based on data.

Keywords

business intelligence; data warehousing; information management; big data; information architecture; performance management; leadership

The most successful organizations are the ones with the most useful and actionable information.

The book is about managing bet-your-business data about customers, products, finances, suppliers, employees, vendors, etc. and all manner of transactions. The possibilities for exploiting this data have increased exponentially in the past decade. It used to be we would try to put everything in a data warehouse (discussed in the next chapter.) While those data warehouses still need attention, they’re not the only game in town for data.

Technologists of all stripes in organizations are hard hit by demands for data – all data. They are also struck by the many possibilities for what to do with it.

So if this data is growing enormously, what’s big and what isn’t? The whole notion of what is “big” and what isn’t is dealt with in Chapter 10. I believe the notion of big versus not big will go away soon. It’s all data, begging to be turned into information. This book is the blueprint for corporate information.

Information is data taken under management that can be utilized.

An Architecture for Information Success

The recipe for success begins with a good, well-rounded and complete architectural approach. Architecture is immensely important to information success. You can architect the environment in a way that encourages data use by making it well-performing, putting up the architecture/data quickly and having minimal impact on users and budgets for ongoing maintenance (because it was built well initially).

I have seen any or all of these factors very quickly send companies retreating to the safety of status quo information usage, instead of progressive uses of information. In the small windows most users have to engage with the data, they will reach a certain level of depth with the data. If the data is architected well, that analysis will be deep, potentially much deeper, insightful and profitable. That is the power of architecture.

This book will have case studies of architecture, but I predominately will talk about the possibilities drawing from development at dozens of companies. Every company is on the journey to information nirvana. Every step of the way in the right direction is worth it. There is no letting up.

Information Technology Disintermediation

There has been a vast disintermediation of Information Technology (IT) functions. No longer is a single IT organization in charge of everything technical. How can they be? Technology supporting information drives all aspects of the business. This makes virtually everyone part of it (lowercase IT). That’s why this book is not just for those working in a formal IT organization, it’s for everyone in the company pursuing their goals through technology.

Users of information are increasingly getting involved in information architecture. They are contributing to weighing the tradeoffs, assessing their workloads in deep ways, selecting methods of data movement and levels of redundancy, determining what constitutes data quality and selecting tools.

If IT is supporting an initiative – as clearly it will do for many – this book provides guideposts for that interaction. This book will provide clear guidance to formal IT as well. My point is it’s information everyone in an organization needs to know. It has to do with the crown jewels, the modern-day gold of the organization – information. It’s how your organization will compete.

At the same time, it also is the responsibility of those who are aware of the possibilities (through the C-suite of executives) for information in the organization to coach the organization in those possibilities and how to USE the information wisely. To whom much is given, much is required. Your capabilities grow with your wisdom about information use and management. Share the information and grow the use of information in your organization.

The Data Scientist

Are you a vaunted “data scientist” if you bring appropriate platforms under consideration or if you know how to use vast amounts of information quickly for high business gain? Yes and yes – and increasingly the answer is becoming both.

If you’re waiting for the current state of affairs to get more settled, know that is unlikely to happen. Someone will champion big data. Someone will champion data virtualization (Chapter 9), data stream processing (Chapter 8) and most of the other components in this book in an organization of any size. Learn how to do it appropriately and let it be you.

Turning Information into Business Success

Today, you need to analyze your business constantly and from multiple perspectives or dimensions. There are the perspectives of the customer, the products, services, locations and many other major dimensions of the business. The high value comes from analyzing them ALL at once. You cannot simply set up a storefront, declare you are open and begin to let the business run on auto-pilot from there. You must analyze the business. Information Architecture is the key to organizing information.

The Glue is Architecture

Information must come together in a meaningful fashion or there will be unneeded redundancy, waste and opportunities missed. Every measure of optimizing the information asset goes directly to the organization’s bottom line.

In reality, information management is nothing more than the continuous activity of architecture.

The glue that brings the components together is called architecture. Architecture is a high-level plan for the data stores, the applications that use the data and everything in-between. The “everything in-between” can be quite extensive as it relates to data transport, middleware and transformation. Architecture dictates the level of data redundancy, summarization and aggregation since data can be consolidated or distributed across numerous data stores optimized for parochial needs, broad-ranging needs and innumerable variations in between.

There must be a ‘true north’ for this enterprise information architecture and that is provided in this book. I do not provide a “one size fits all” reference architecture. Each company is going to be different. There are different starting points and different target interim ending points for architecture (it never really ends). Each company is at a different level of maturity and will wish to advance at a different pace. Many companies are not going to be able to move at the speed desired without new skills in place.

There needs to be a process in every organization to vet practices and ideas that accumulate in the industry and the enterprise and assess their applicability to the architecture. I highly advocate some company resources be allocated to “looking out and ahead” at unfulfilled, and often unspoken, information management requirements and, as importantly, at what the vendor marketplace is offering. This is a job without boundaries of budget and deadlines, yet still grounded in the reality that ultimately these factors will be in place. It’s a very important job for caretaking the information management asset of an organization. For titles, I’ll use Chief Information Architect.

Workload Success

Even organization leaders can take a tactical approach to the execution of the requirements. However, it does not necessarily take longer to satisfy information requirements in an architected fashion. If architecture principles and technology possibilities are not considered beforehand, the means to satisfy the current requirement may be inappropriately defaulted to the means to satisfy the last requirement. And so on.

The Chief Information Architect

The information architecture in place at any point in time is going to be a combination of a bottoms-up, needs- and workload-based approach and a top-down, longer-term thought out approach. Bottoms-up solves crises and advances tactical needs. Top-down – the job of the aforementioned Chief Information Architect among others – looks ahead. It still solves tactical issues, but does so with the strategic needs of the organization in mind. While no organization is run by either approach exclusively, can we please dial up some more top-down to avoid problems caused, essentially, by the lack of a true architecture?

The proposed approach of this book is to:

1. Have a ‘true north’ in mind for a 5-year information architecture, understanding that it is subject to change¹

2. Have a Chief Information Architect managing the 5-year plan and contributing to workload architecture

3. Organize new information requirements into workloads, which comprise functionality that is necessary to achieve with data, as well as the management of the data itself

4. Allocate those workloads to the most appropriate architectural construct for its success (defined below)

5. Perform all work with an eye towards delivering return on investment (ROI) to the business at the lowest total cost of ownership (TCO)

Ultimately, we are trying to deliver return on investment to the business. It’s a principle well worth following as you make decisions. ROI is [return/(return – investment)] and is always specified with a time period (i.e., 145% in 3 years). It requires the discipline of breaking down the workload into its projected cash flow. Whether you embrace the math or not, embrace the idea of delivering value to the business that could, ultimately deliver ROI. This can happen through short-term financial bottom-line impact or through information-borne innovation that yields ROI later. That is what information management should be all about – not speculation, fun exploration or a book standard. It’s about business.

By reducing fraud, a financial services provider showed a 74% 3-year ROI against the existing fraud loss trend and an insurer showed a 213% 3-year ROI through routing claims to the best provider for the service.

Once we have established, as a business, that a workload has high, positive ROI (relative to other possibilities for the investment), we establish the architecture for it that meets the performance, agile and scalability requirements with the lowest TCO. As such, most of this book is focused on conveying the capabilities of each platform to help you allocate workloads appropriately – with the lowest TCO! It is not designed to make you a “one percenter” in knowledge of any of the individual platforms in isolation.

Information Workloads

Allocation of workload to an architecture component is both an art and a science. There are user communities with a list of requirements upon a set of data. There are other user communities with their own list of requirements on the same data. Is this one workload? If ultimately it is best to store the data in one location and utilize the same tool(s) to satisfy the requirements, the practical answer is yes.

What Determines Workload Success

It is primarily the performance of the data access that constitutes the success of a workload². Performance can be engineered (and it always must be to some degree), but primarily we give performance a huge step forward with correct workload-platform allocation.

Secondly, we need to get the workload up and running quickly. Getting to that fast performance quickly is the second measure of the success of an information workload. I talk about agile methods in Chapter 16.

Thirdly, if the good performance goes away quickly because the application is not scaling, all would be for naught. The third measure of workload success is scale. The solution should be scalable in both performance capacity and incremental data volume growth. The solution should scale in a near-linear fashion and allow for growth in data size, the number of concurrent users, and the complexity of queries. Understanding hardware and software requirements for such growth is paramount.

Note that this does not mean the initial architecture will last forever untouched. All good things come to and end and information management is no different. This does not stop us from pursuing making information as good as it can be, given what is known today.

These are the three factors I primarily consider as I give workload recommendations for the various information management platforms in this book. It does not mean there are not other factors. There are, but they tend to be “dragged along” when the focus is on these three factors. Architecture component selection is more important than ever because it must scale with exponentially increasing data volumes and user requirements.

Information in Action

Consider what the right architecture for an ROI-producing workload can generate for the companies below and you can see the importance of investing in wise platform selection and the need to go well beyond hanging up that storefront.

Big Box Retailer

Same store sales are dropping and the company is losing market share though web activity remains strong. It needs a way to improve its sales through understanding the dynamics of in-store and online purchasing. Through information analysis, it determines that customers who buy in-store buy much more and much more profitable items. This is partly due to impulse purchasing in the store. To boost this activity, they try to encourage online shoppers to come in to the store.

They need to make the right offer. At checkout, they encourage a store visit. For those near a store - determined using geospatial analysis - when all the products are available in the store - determined using inventory data - they extend a customized discount – approximately the cost of gas - if the buyer will come in to the store.

Also by analyzing patterns that lead to purchases and why a lot of demand is dropped shortly after a purchase pattern begins, it is determined that the main thing that causes abandonment is if the product they are interested in is not in stock. And it’s not just any product in the basket – the first product into the basket counts the most, by far. By improving the information available to the shopper, the company sees more baskets go through to the sale. It also is able to better stock the most interesting items, including those in abandoned carts. If, by chance, a basket is abandoned due to an out of stock condition, they can email the shopper when the product(s) are in stock and try to recover the sale.

Telecommunications Provider

Dropped calls in a region are causing major customer defections. The company needs to know the detail about the drops - what’s driving defectors and what kinds of defectors are dropping off. By creating a call graph showing who is calling who, the company gains access to the customer’s value and influence circle. High value customers and influencers move immediately to a watch list.

By cross-referencing the location of dropped calls, tower coverage holes emerge. By looking at factors in the dropped calls like devices used, cell site handoffs and signal strength, causative factors might be determined.

This company can now add towers quickly to cover the high value and influential customers. They can also begin a campaign for the other high value and influential customers who will not benefit from the towers. They can issue apologies, credits, free upgrades, and possibly free cell boosters. The cell boosters cost $250 each so must be distributed judiciously. However, with the information under management, it can weigh the cost against the customer’s value and likelihood to churn and can make ROI-based actions.

Judgment Still Necessary

I am keenly aware that, as technology expands its ever-growing footprint into all aspects of our lives, personal disruption can occur. Nowhere is technology making more strides than information management and nowhere else must personnel adapt as much as in their use of information. It is changing the nature of the company job.

Information by itself cannot think. True artificial thought - the kind that replaces human thought and judgment - should not be thought of as the next logical step in the journey. Good information management will not take the place of the skills and experience of the business analyst or data scientist. The essence of human thought is the aptitude to resolutely manipulate the meaning of the inputs encountered to create perceptibly favorable situations and arrive at a basic cognitive orientation.

It is impossible to capture all the data in empirical form that analysts utilize to make the most effective decisions. The liaison responsibilities of the analyst - between business owners, end users, IT staff and IT management - is also a necessary component of successful data analysis and operational function.

At a minimum, and where many programs are today, information management simply provides access to corporate data more efficiently and occasionally does some automated cleaning of that data. While an analyst’s role in manually accumulating disparate corporate data can be diminished, the higher value-added role of thinking cannot be.

Thus, the great judgment found in the great business analysts will always be required for our success in information management. We cannot hope, nor should we strive for, any diminishment of that role with our work as information managers. It should grow, more empowered than ever before, into the new realms we’ll now start to explore.