Integrated information for policy-managed decisions

MM: It seems that as your solution evolves to include WiFi Max networks and 3G phones—such as the iPhone—these mobile Internet connected devices become points of control of an entire industry, almost like the channel changer for a TV; it’s becoming the control system for these very sophisticated applications.

MB: I think of the world of mobile devices as a great way to give freedom to people who otherwise have to be slaves to the careful tending of systems and so forth. In that sense, they’re very freeing.

If you take the kinds of monitoring and management application that people want as a business intelligence solution and simply display it to them on a mobile device, you’re not going to be doing them any favors. You’re just changing the location at which they have to do a piece of work, where they look at a screen, make a business decision and so forth. It might give them some location freedom, but there’s a lot more potential out there for the activity you have to do, from the mobile perspective—to be a higher level of monitoring. You automate the decision-making at the lower level.

Today, let’s say you’re looking at a sales margin inventory kind of report. You say, “Gee. Here’s a product that I have very low inventory of, and I happen to be selling a lot of it. Gee. It’s selling at high margins. I guess I should reorder that.”

Of course, the system should just reorder that for you.

Today, people struggle just to get all that information on one line. So they can see that the problem is actually there. The next generation of systems will be ones directed at business rules that will help people automate the solutions. It’s what we call “operational business intelligence,” where triggers and tripwires and things of that sort can notice characteristics of the data in the enterprise, and can take actions.

Then from their favorite mobile device, people can make sure that the decision-making that’s happening for them is not going off the rails for some unforeseen reason. Instead of having to switch every switch on the train, you just have to see that the trains are all moving in a reasonable way.

I think the future will lead to integrated information properly displayed for human decision-making, to support of that human decision-making.

MM: And eventually, I guess, we get into policy-managed processes that basically report back to you that, “Hey. I did this. Is that okay?”

MB: Once you have integrated information, the sky is the limit with what you can do with it. Integrating the information and presenting it in a reasonable model for people has been the bottleneck and remains the bottleneck today.

MM: Well, that sounds like a great place to conclude. Thanks very much.

Problem of transportation logistics

MM: Not just trucks, but what’s on the pallet and how many pallets get organized by what truck.

MB: That’s right. And how many stops it takes and so forth.

This brings me back to what we mean by a “Diagonal,” BI application.

To build an application that really helps address the problem of transportation logistics, or the truck shipping of goods, you have to embed a lot of industry understanding and knowledge of trucking into the application. So it requires information specific to the business problem of shipping goods by truck, but it’s not specific to any particular industry.

You don’t really care whether you’re shipping machinery or consumer packaged goods or clothing. These applications cut across industries, but not all industries. Obviously, financial services people aren’t shipping goods around by truck, and for the most part, shipping is just not a part of their primary value proposition. Similarly, higher education is not a truck-oriented industry. But any manufacturing company, whether in the food segment, the clothing segment, the toy segment, the industrial products segment, etc., all have a similar trucking problem to solve.

Another example is any company that makes or sells something that typically has sales margin and profitability issues. The companies really want to understand what products are selling at good profit margins. They want to be assured that the inventory they carry, relative to sales rate, is in balance.

Sales margins and profitability issues cut across industries that have goods to buy and sell—but obviously these aren’t applicable to government or higher education. It’s not like a database system because it doesn’t apply across all industries.

These diagonal types of applications are important because they add high value for their customers. They typically save companies thousands and thousands of dollars all the time, or even millions, for large companies. So they are applications that can command high price points, because they really deliver great savings and a very attractive return.

But also, they’re applications that—because they can be sold across many industries—have a pretty large base of prospective customers—larger than vertical-market applications that are targeting a very narrow perspective. They are very attractive from a business standpoint.

Diagonal applications also work very synergistically with SaaS deployments. That was one of the things that I emphasized in the talk I gave at SaaScon. The reason there are companies like Oco and obviously other new market entrants in this space is because of this synergy.

When you build a system for a particular business problem, transportation logistics, let’s say, then the structure of the database of information that’s needed to support it is not specific to that particular customer. It’s a database that’s designed to support transportation logistics.

As a result, you can get great economy of scale in the deployment of that system by creating a SaaS multi-tenant deployment of that database. All the customers sharing that infrastructure are trying to solve the same kind of transportation and logistics problem against a database of similar structure.

This works a lot better than the ASP models of a decade ago. Back then, custom data warehouses would be designed for each business. If you tried to aggregate those together, you’d get a whole bunch of totally different databases. In some sense, they were too customized. You’re not going to get common behavior by putting them together.

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PvT: Okay. Talk a little bit about digital asset management and whether or not that’s a feasible way for global organizations to manage their corporate brand identities, photos, and videos—their brand assets?

MM: Sure. Well, just for a little bit of a history on that. My firm invented the term “media asset management” in 1994 in our work with Aldus and MediaStation.

Later in 1996 or so, we expanded the term when we wrote the white paper for Apple Computer as part of their Masters of Media Program—a brilliant industry-wide marketing framework that included Adobe, Agfa, Kodak, Quark, and Xerox conceived and executed by Jeff Martin, then the Director of Marketing for their Advertising, Design, New Media, and Publishing division.

Apple commissioned an executive white paper to make the business case for their line of Apple servers. IBM picked up from there and commissioned another white paper and international roadshow—also to make the case for the IBM Content Manager.

In 1998, my partners and I wrote the first full market report on DAM and continued with the reports until 2002.

In 2001, we began our long-standing partnership with Henry Stewart Events and their DAM Symposium.

In 2003, as the Editor in Chief, I started the Journal of Digital Asset Management—with which I continue today.

Strategic Capability

I say this all as preamble, do I consider digital asset management strategic capability? The short answer is, emphatically, yes. You can’t manage a global brand and a pan-regional marketing operations without some form of DAM. In fact, we have published a series of executive white papers on the subject.

Now DAM has a lot of misinterpretations, or misunderstandings in terms of what it constitutes.

DAM, first and foremost, constitutes business strategy for accelerating operational processes within media, entertainment, and publishing, and marketing content processes within global brands. So it’s reducing cycle time, reducing cost, and having a process that’s far more agile or flexible in adapting to change.

I contrast digital asset management with content management. I used to say somewhat tongue in cheek that content management is really ‘crap management’.

Content management deals with more or less self-descriptive files—documents or Web pages for which you do not need a lot metadata to describe its contents, meanings, semantics associations with other content and, more specifically, who owns the content or images—from where did the editorial or copywritten material come, when does it expire, all that.

Digital asset management, in contrast, deal with non-descriptive files, hence the emphasis on metadata and the systematic reuse and transformation of preexisting digital media files. This entails the creation and management of metadata associated with findability, reuse standards, and permissions or digital rights management.

Now a reusable digital file may represent an image, photograph, or publishing template. Digital assets may include text or product claims used in marketing communications, or video clips, MP3 podcasts, and type fonts, or Flash animation. Or elements that contribute to immersive virtual world experiences 3D and 2D models or primitives.

A digital asset might also include software code assets—scripts and programming—and things like IT service management policies and business rules or software libraries and software objects. Or learning objects or reusable pieces curricula that flow into books, instructional DVDs, or online courseware.

So, digital asset management is really about reuse and creating metadata that give you competitive advantage: Cost reduction, time to market, higher quality, greater process agility, and the ability to maintain transparency or governance across an entire marketing supply chain.

As a business strategy, digital asset management starts with a DAM repository—where you put all those bits—and begins to really payoff with an operational group—a DAM service group—that maintains the integrity of metadata, digital asset files, and user productivity.

This brings us to the current state of the art in DAM:  Managing a supply chain for continuous improvement and reduction of cost, cycle time, defects, and opacity of key business processes.

So, I do not consider digital asset management an option, nor a luxury. Just like you have an email system, you must have a DAM. It’s just not an option.

SOA Value Chains?

PvT: Who are the prime contributors to the development and support of an operational marketing and service innovation platform? And how did you start researching the technical ecosystem—what you and I now call engagement marketspace?

We started in 1995 with digital asset management and content management because no matter what else came along, you must have a media and content under management.

In 2000, we started investigating another class of vendors in the marketing automation, MRM, and marketing operations management space. Some of the vendors have make great progress.

With rare exception, they all still need to better understand DAM and, more the point, metadata management—a database and DBA for logging and tracking enterprise metadata as instantiated in all enterprise databases, including ERP and CRM, as a strategic asset.

Since 2004, we have tracked vendors that come from the CRM, business intelligence, and process analytics space.

For the last three or so years, we have tried to understand firms in marketing service provider and data enrichment vendors—lots to cover!

Of course there are whole sets of vendors in dynamic messaging and email management content space, and in the customer experience management space too/

As I stated before, there’s many different technology vectors in the marketing and innovation value chain, that ultimately support the idea of an innovation-services platform.

This calls attention to, however, the critical need for leadership within marketing to have a services integration framework and an underlying Service Oriented Architecture (SOA) enabling this integration framework. IBM does some great work there with its component business models—what I call CIO blueprints.

Services integration

However, the senior marketing executive, not the CIO, must commission and own the services integration framework—it basically specifies in one wall-mounted poster all of the services – marketing and innovation-related services – of the business eco-system from which the firm will build, buy, or rent technology or engagement services over the next five years.

Now, the CIO blueprint represent an living, evolving visual depiction of one thing: how firm intends provision services needed attracting, serving, and keeping profitable customers for life.

The CIO blueprint also makes explicit how the firm intends to marshal the resources of a global business eco-system: ‘Here’s what we bring to the customer experience. Here’s what our partners bring, and here’s how it all integrate to an end-to-end process of customer-making.

PvT: I guess that repositions marketing automation a bit player in a larger play?

MM: Well, I don’t think that the rubric of marketing automation delivers useful distinction anymore. I don’t like the term “marketing automation” because many of the research firms and vendors have abused the term, rendering it useless.

Rather, I would like to speak about marketing in terms of process maturities, and levels of process maturity for a marketing operation.

Again, the senior executive doesn’t really care about technology or marketing automation, per se, he or she is most concerned with operational capabilities and building or enhancing capabilities which will related directly to a process maturity model for marketing operation.

However, this all underscores a very strategic point: business rules and metadata enable orchestration of the technologies and processes of how firms attract, serve, and keep customers for life. Very, very few technology vendors deliver solutions for orchestrating the customer engagement life cycle. Typically, the missed or underplay the role of three SOA capabilities: digital asset management, metadata management, and marketing claims management.

Marketing claims management

This last one, marketing claims management, entails a end-to-end workflow for developing and publishing approved copywritten material—product or service claims—to a specialize XML database publishing system. I use the term broadly to include anything written, formatted, and published in printed collateral, business communications, web sites, interactive detailing or presentation systems, catalogs, microsites, newsletters, etc.

In my view of the world, marketing claims management represents a subsystem of DAM and metadata management—that in turn represent subsystems of master data management.

And all of which requires a IT governance scheme—systems, processes, and accountabilities for researching, acquiring or developing, deploying, provisioning, managing, and retiring the technologies used to attract, serve, and keep customers for life!

Key point: tomorrow’s CMOs are mid-level IT executives today getting their masters in Business Administration or Media Psychology.