Business Focused Digital Transformation (BFDX)

By: Joe Roushar

August 2018

What is BFDX or Business Focused Digital Transformation?  To thoroughly understand it, we need to start at the beginning.  Digital Transformation (DX) means different things depending on your context. Many people equate DX to e-Commerce: moving the sales from bricks and mortar to “Clicks”. Others may think of it as moving to the cloud, or IoT (the internet of things), or incorporating big data or AI. Any of these can be transformative, but they may or may not help you succeed or compete more effectively. Successful technology implementation does not equate to business success, and there is a lot of Cobol code running on big iron that may not be so easy to profitably replace. A recent Forbes Tech Council article began with this ominous warning: “With a few exceptions, the majority of executives I speak with recognize the digital disruption that is upon us and are willing to invest in the transformation necessary to compete in the digital age, yet few have seen tangible value as a result of digital initiatives (Logan 2018). A huge differentiator between transformations that succeed and those that don’t is the business focus (BF). Without this focus on the business value outcomes and commitment from the business stakeholders, the DX won’t be worth the money thrown at it.

Being in IT for the past few decades, I’ve witnessed a lot of progress. Whether you like it or not, information technology seems to change significantly every few nanoseconds. On the other hand, technologies that were expected to die long ago are still alive and delivering business value. This implies that each industry is unique, but technologically in motion, and that while the speed of change may be accelerating, some businesses change faster than others. Social media is an enormous industry that didn’t appear or at least get named until halfway through my career. The buggy whip industry effectively died with the automobile, and you’d be hard-pressed to find a blacksmith shop on Main Street, even though the sound of hammer on metal was a staple of earlier generations. Your insight into your industry, and its evolution, is much more valuable than any number of articles and books about digital transformation. Your forward-looking business vision is the most important factor in setting a focal point that will result in a successful DX.

” Motivations Models” show industry and technology drivers underlying business vision and mission, and alignment between strategies and goals (see my diagram below). A major trend in business re-engineering is increasing customer focus to improve sales and retention. If this is important, the first question to ask about your DX initiative is: What will this do to delight customers and bring them closer to our brand and products? If the focus is more internal, such as reducing duplicate capabilities and data or streamlining operations, the questions need to be laser-focused on the outcomes, and success metrics, the way you both justify upfront and later judge the expenditure, should directly address present pain points. In DX initiatives, the entire organization is your patient, and hooking up the right monitors to gauge heart rate, breathing, and brain activity with a clear understanding of what improvements are targeted could be the difference between clear success and unnecessary expense.

1. Business priorities are the number one driver: no transformation should begin until the key business outcomes are clearly defined. Esther Shein in CIO says “improving digital presence will be a top driver for IT investment over the next two years. Other broad goals respondents have for their organizations include reducing operational costs, improving the customer experience, and aligning IT with business strategy” (Shein, 2018). “The challenge for executives is understanding how to leverage them not only to change but also to transform their businesses” (Logan 2018). How do you know if your business priorities are correct and transformative? When key business stakeholders can align on a single vision and are excited about allocating their resources to make it happen, you know you are on to something. DX will not succeed without commitments from business stakeholders. When IT understands the shared vision before the first system or platform change is discussed, visionary IT leaders and architects can then collaborate with the business to identify the technology and information impacts and strategies. The combination of alignment across business functions and alignment between business and IT will go a long way toward overcoming resistance to change: the excessive drag that keeps the project from taking flight. Residual resistance can be reduced using people change management.
2. Don’t think of the business case for DX with a project-centered mindset. Elevate your view to the vision and mission of the organization, make sure they are good for the next few years, then justify the work with vision and mission level expectations. “ROI and deadlines are things that projects are made of. Digital transformation is not a project; it is a complete sea change” (Logan 2018). Of course, it is easy to cross the line into the realm of Bullshit Bingo, in which almost every word is a meaningless platitude. The best way to avoid this is to create a focused elevator pitch style explanation of what is to be achieved and get each stakeholder to articulate conceptual level outcomes that will achieve the focused objectives. Next, match each conceptual level outcome with a set of meaningful detailed process level changes. Notice I’m still talking about processes and not systems. The system impacts will come, but should not drive the discussion. Finally, for each outcome, measure progress. With a dashboard that may resemble a bedside array in a hospital, track the sales, retention, throughput, WIP or whatever you’re working to improve with as fine a granularity as makes sense for your organization.
3. Business information should receive forethought – never afterthought: Systems are less important than business outcomes, and cannot succeed unless the entire data ecosystem is factored into the transformation. The entire information lifecycle, from improving your ability to acquire more meaningful information, to improving your ability to analyze and exploit it will be affected if your initiative is to be truly transformative. “At the heart of the digitization revolution is the ability to accurately and quickly automate the capture of information from any source” (Orcutt 2017).  Avoid unnecessary duplication of data, and think carefully about why you are building a data warehouse or data lake. If the outcomes you seek need to span the great divide between structured (databases) and unstructured (documents and rich media) information, you may need semantic metadata management to bind them together, and you may need some AI to discover, catalog, and classify your information assets. Orcutt goes on to suggest “using natural language and deep semantic processing …to extract value and understand meaning and relationships between entities … provides unprecedented insights to make smarter business decisions quicker” (ibid). “Information is not just a key part of digital transformation as such. It also comes into the picture at each step along the road towards achieving both specific and enterprise-wide digital transformation goals” (De Clerk 2017).
4. Don’t think of swapping platforms as DX. Platform first strategies may not deliver any business value (see 1, 2, and 3 above). The reason big iron is still alive and well is that the value proposition for mainframes still works in some cases. If you are not certain how to determine if a new platform is in order, bring in an agnostic enterprise architect with experience in the specific platform change contemplated. This is not an “any consultant will do” recommendation. Choose wisely and the results will speak for themselves. Don’t bring in a person who has spent their entire career deep in the code, nor a person with generic credentials. There are tools and organizations available to help you find the person with industry and platform experience that will be able to help you make difficult decisions, and be pleased with the outcomes.
5. Intercommunication between systems, services, micro-services, and data stores can make or break the project: define each information exchange carefully in the context of the required outcome. If you find the number of data interchange routines seems to be proliferating, be careful. In moves to Micro-services, the number of data interchanges may grow if each routine handles fewer categories or actual objects of information. But in the end, you want to increase your control of, and visibility into data movement and too much growth in the number of separate processes impairs your ability to manage the complexity.

Outcomes can be defined at multiple levels of granularity, and if you do the top-down (conceptual to logical) and bottom-up (detail process and data design) work in tandem, ensuring that they meet nicely in the middle, your outcomes will be surprisingly well-aligned. Many IT groups have little experience thinking of data independent of systems, but for successful BFDX, especially in a world where new information sources arrive with increasing velocity, information strategy supporting a BFDX should be:

1. a core component of the transformation strategy
2. independent of vendor systems
3. governed by knowledgeable stewards and subject experts
4. a core component of any AI and/or machine learning initiative
5. secure from the outset

Today, the best common wisdom I have encountered uses centralized policies and API-based information exchanges as core technical components of an information strategy to support BFDX. Organizations that choose to move toward microservices are well-served by centralized policies and metadata, and consistent smart APIs. For on-premise and cloud-based deployment models, strategic Information is equally valuable. But it is not free. “In the absence of an information management strategy, most organizations arrive at what passes for a strategy simply by aggregating their past sins. Organizations typically have a variety of technologies and tools in place, often the result of decisions made years ago and often made within individual departments. Simply ripping out this accumulated infrastructure is usually not an option. However, there are some hard questions that organizations should ask in terms of integrating and leveraging what they have and driving future decisions against a strategy” (Mancini 2017).

Just as Digital Transformation should not be attempted without deep commitment, defining an information management strategy is an example of investment for the future for which you “pay now” to avoid higher costs later. This should include an advanced information model and supporting metadata in a data catalog that can be used to support all key processes, and especially, all needed insights. But the competitive advantages can be very significant. Furthermore, BFDX initiatives, especially those including AI or machine learning, without a clearly defined information strategy are less likely to deliver the full business value anticipated.

References

Rethinking Digital Transformation, Joe Logan, Forbes Technology Council, May, 2018

6 hot digital transformation trends — and 4 going cold, Esther Shein, CIO by IDG, April, 2018

Information Management Fuels Your Digital Transformation Efforts, Bruce Orcutt, CMS Wire, March, 2017

Digital transformation and information management, JP De Clerk, i-SCOOP 2017
8 Factors to Consider in Creating an Information Strategy, John Mancini, AIIM eBook, 2015