Digital Transformation - 5 Disciplines of the Agile Enterprise
Digital Transformation is definitely developing buzzword allure. But leaving the hype aside, under the surface, the challenge is real and all about change management. This article gives a hollistic view on the topic breaking it down in a number of concrete disciplines that together form a recepy of a succesfull transformation programme.
Embracing Change does not come naturally, enterprises are at their core organic structures of people intrinsically resisting change. Nobody wakes up in the morning and decides to move out of their comfort zone. In a digital age, accellerating changes in the external fabric of the enterprise pose a managerial problem. In order to face this external challenge, adapting to change needs to become less painful, less uncomfortable and part of the DNA of an Enterprise.
Ultimately it is the internal fabric of the enterprise that needs to become more flexible: there is a need to build/ transform into an Agile Enterprise. This Agile Enterprise is the engine for all digital transformation projects and when failing to make this crucial transformation, enterprises run a real risk becoming extinct.
Transforming the internal fabric of the enterprise, allowing it to adapt rapidly to changes in the external fabric without giving up the rigidity and focus needed for a successful strategy execution, is the centrepiece of any digital transformation programme. It touches culture, business processes as well as the ability to transform business models and accelerate innovations in a digital world.In designing a digital transformation program, all these aspects should be considered to avoid creating high friction losses when e.g. internalising digital pilot projects.
There is no quick fix for Digital Transformation, it is a larger change management program that needs to be planned and executed with care and requires profound insight in what delivers competitive advantage at the customer front.
Digital Transformation has a different taste in each individual Enterprise. This article tries to give a overview on all aspects/disciplines of Digital Transformation, ranging from IT Transformation to Customer Centric Innovation. Whereas each aspect can be treated with different priority, what connects them all is the Digital Strategy that gives orientation to the design of the digital transformation programme.
This article gives a high-level concept for transforming the internal fabric of an enterprise, an implementation blueprint at the basis for initiating a transformation project.
- Relative Sense of Urgency
- Transformation Blueprint
- Discipline 1: Developing a Data Strategy & Establishing an Enterprise Data Architecture
- Discipline 2: Business Processes Management in a Digital world
- Discipline 3: Data driven Decision Culture – change catalysts
- Discipline 4: Value Propositions – business model transformation
- Discipline 5: Innovation in a digital age
1. Relative Sense of Urgency
In most B2B markets, there is no need for panic, decades of resistance to change have resulted in significant barriers. Established industry structures, purchasing best practices, partner and service ecosystems are the mangrove forest that can absorb large part of the energy that a digital tsunami brings. Sense of urgency can therefore be relative to the industry you work in and potentially less existential in the short term.
The best practices, regulations and institutionalised lock-in strategies of supplier ecosystems that govern e.g. the real estate / construction industry raise a high barrier for innovations to take place and in response to margin erosion, consolidation is the most forthcoming scenario. In these environments, digital transformation has more mid-term relevance instead of being the immediate response to changes in the external fabric of the enterprise. That does not mean that transformation programme should be postponed as there is a significant productivity gain for grabs or simply enjoying the benefits of being able to attract and retain good talent. The perceived sense of urgency is a different one..
B2C Markets are more at risk. The case of Nokia phones tumbling down from being the world leader in Mobile Phones to saving the company in an overpriced and well-orchestrated fire sale to Microsoft, offers an early example of failed digital transformation. If Nokia hadn’t been blind-eyed by a decision culture that was not data driven instead focussed on internal consensus and maintaining the status quo, it could have seen the writing on the wall and adapted more quickly to the looming smartphone revolution and become a software driven company. The difference with the B2B Market is the switching cost / lock-in mechanisms that are almost almost negligable in a B2C market compared to the barriers built up in B2B markets.
The proposed implementation guidelinecreates a generic framework for creating an agile enterprise and applies to all circumstances.
2. Transformation Blueprint
The proposed approach for transforming into an Agile Enterprise and leveraging innovation power at the customer front is built around the Blueprint shown below.
At the centrepiece of the blueprint is an Enterprise Data Architecture offering a catalyst for establishing a data culture in the enterprise. This data culture drives decision making and is an engine for Agile Business Process Management. With these 2 building blocks in place the core engine of a enabling the enterprise to deal with external change is established. This in its turn lowers the barriers for business model transformation as well as executing digital innovation at the customer front. The Sections below are a deep-dive in these disciplines
3. Developing a Digital Strategy & establishing an Enterprise Data Architecture
Research by McKinsey (Ref 1) has shown that using data effectively translates in a 1% margin improvement and specifically for the retail sector, data driven companies have doubled their EBIT Margin compared to their more traditional peers.
The amount of available data however is overwhelming, it doubles every 2 years, worldwide. Converting data into information and deriving intelligence out of it is an exercise that is resource intensive and can quickly become an important operations cost. That is why sufficient time needs to be spent on defining a data strategy and a holistic enterprise data architecture, not as an island within the Digital Transformation Team, but instead fully aligned with the business strategy and fully integrated with the legacy systems the enterprise operates on.
The central paradigm in designing an Enterprise Data Architecture (EDA) is the alignment with the Business Strategy (Digital/non-Digital), more importantly, business requirements drive technology choice.
In designing the EDA, some additional design principles need to apply:
Single Source of truth: the EDA needs to offer a framework for all the data for building the cockpit for monitoring and strengthening of core activities (no silos’s)
Flexibility by design: Layered Approach with clear boundaries as to allow aligning technology with evolving business requirement as well as to remain at the technological state of the art without having to redesign the EDA.
Definition: The Enterprise Data Architecture (EDA) refers to a collection of master blueprints designed to align IT programs and information assets with business strategy. EDA is used to guide integration, quality enhancement and successful data delivery. EDA is part of the overall enterprise architecture, which has several integrated aspects, including hardware, applications, business processes, technology choices, networks and data.
The Graph shows a high-level view of what an EDA for digital transformation might look like integrating the legacy world of data warehousing with the new real time decision support world of the agile enterprise.
Start with Strategy: business requirements drive technology
Business Strategy defines the information need and ultimately the underlying data architecture. Defining this data architecture is an important exercise that needs to be planned carefully. Enterprises that fail to see this run an acute risk of building incompatible data islands and inflating the cost of generating the necessary information. Backpaddling on an enterprise data architecture that is not aligned with business strategy sets back the complete transformation effort.
Return on data initiatives is an important consideration to make in any Digital Transformation Programme. The Digital Business Case, taking all the upside of the digital transformation program and weighing it against the implementation and operational cost creates a framework for discussing assumptions, impact, allocating resources as well as evaluating implementation scenario’s.
Common pitfall: Strategy vs Operational Effectiveness – Formulating (Digital) Business Strategy is not a trivial exercise and should not be confused with leveraging data to obtain operational efficiency. Strategy is about the cluster of activities that in the market the company operates in, delivers (even limited) competitive advantage.
Integrating Legacy Systems – two speeds
Legacy data systems do not become obsolete in the new Enterprise Data Architecture. They need to be integrated with a digital data architecture that is designed for real time decision support and data processing. Individualised marketing, pricing as well feeding new business models needs a different data infrastructure and processing capability. The traditional data warehouse, through which the organisation gains stability and financial transparency needs to be scaled down and integrated with the high speed transactional architecture that supports new products and services.
Governance and Security: Data Democracy
Getting Data in front of people is the only way to create excitement and initiate change. Data Culture should become part of the value system of an enterprise, creating a cross-cutting data set across the organisation is a key success factor. In parallel, the necessary governance systems and security mechanisms should be put in place. Data Protection and Privacy laws need to be complied with at all times to avoid Data Culture to backfire.
EDA as Competitive Asset
If Data culture becomes an engine for Competitive advantage, the data which is the fuel that flows through that engine should be treated as a competitive asset. This is important in the innovation process where make/buy/partner decisions are taken and in partnerships, that data is often shared with partners. Caution needs to be taken in doing so, considering what will happen to the data once you share it as well as looking at the fine print of the contractual framework related to data ownership.
4. Business Process Management in a Digital world
“Start with Business Strategy” is the universal paradigm for the design of a digital transformation program. A well-designed business strategy clearly focusses on what activities / business processes give the enterprise a competitive edge in the marketplace. The digital business strategy is a subset of the overall strategy sharing and fully integrated with the enterprise operational strategy as elaborated in an earlier Article: Digital-Transformation-Strategy-Compass-Concept-Note-The Mobile Project (2017) (Ref 2).
In a digital World, the challenge is to keep strategy, business processes/activities in-tune with an environment featuring accelerated change: market structures, competitive landscape, consumer behavior are evolving at a fast pace. With competitive advantage at stake, it is worth developing a new approach to Business Process Management (BPM) to keep up with external change. Whereas the traditional way of doing BPM in the enterprise in most cases is still being executed according to the waterfall principle, a more agile, Scrum-like approach needs to be taken to BPM.
The proposed Methodology for making business processes more agile can be found in the publication Corporate development with agile business process modelling as a key success factor (Ref 3).
Applied to the critical processes in the Enterprise, this method allows implementing a key building block of the Agile Enterprise. Some measures need to accompany the introduction of agile BPM:
Introduction and training of cross functional teams involving Strategy, Operations and IT that have the power to execute the Agile Business Process Management
Setting up a good process controlling/alarming not only for the critical processes but also for the supporting processes activities to allow quick feedback loops (pos/neg). => EDA Design Input
Also here the Return on Data Initiatives imperative applies: the measurable effect is improved efficiency / less overhead by (1) more agile processes and (2) better insight into process efficiency.
5. Data driven Decision Culture – change catalysts
Building an EDA and filling it with Data is just an initial hurdle to take. Making data part of the decision culture to make better decisions requires a cultural challenge. When decision processes are intrinsically slow and political, data initiatives will hardly manage to energize the enterprise and organisational agility will never be reached.
Deafness by design – setting up wider programme of cultural change
Some Enterprises are intrinsically deaf to changes in the external fabric. Symptoms of such a state are well described in an earlier article : Signs of a Corporate Immune System designed to Kill Innovation (The Mobile Project 2017) (Ref 4). Depending on the degree of “hearing impairment”, a wider programme needs to be started to fix this challenge. The proposed approach below describes the minimal approach to establishing a data culture.
Change Catalysts
Using catalysts to induce a cultural change is a very effective way of applying change management. The proposed method is simple, yet effective if given the right management support.
Identify key decision forums across the enterprise that are key in maintaining the enforce the strategy or the delivery of customer success. Identification of these forums should be done by the C-Suite, personally committing to establishing a data driven discussion in these forums.
Synchronise Data Requirements with EDA Design to guarantee accessibility and quality of data.
Design the “Experiment” well to allow measuring the impact on the quality of the decision making. This requires evaluating data requirements
Document, Spread the word, including evidence about bad decisions taken.
Repeat / Improve/Iterate
Risk Management
De-politicizing and accelerating decision-making cycles and real time feedback increases visibility of mistakes. In the assumption that the residual risks are inferior to the risk of not taking a decision, risks should be part of the decision culture and consequently openly discussed and monitored. With shortened decision cycles, decision quality should increase but also mistakes will increase. An open dialogue about mistakes (fail fast) should become part of the company culture. Ultimately, data transparency will reduce overall risk.
Skills
Organisations that are overwhelmed with digital transformation challenges are most likely also facing issues on skill profile of the employees. Pro-actively investing in widening the data skillset of the workforce to facilitate transformation effort and decrease resistance should not be postponed. In an enterprise that has adopted a true data culture, the use of analytics tools such as PowerBI and Tableau should slowly overtake the use of PowerPoint.
6. Value Propositions – business model transformation
The data tsunami which creates a constant information stream along the lifecycle of the products and solutions often allows establishing a new business model in the market. More importantly, it offers an opportunity for a new entrant to enter the market with a disruptive business model. This offers a compelling event for business model transformation. For product-based companies, it is about evolving towards product as a service, for software licence companies, it often means developing a SaaS model. With data as an enabler, the real challenge is transforming into an organisation that supports the new business models with the right processes, skills and governance structures. Being an Agile Enterprise is almost a precondition for making this possible
A well-designed business model transformation framework needs to take into account the following factors:
Strategy / Business Plan / Blue Print: It is reasonable to expect the new business model will yield different margins R&D spending levels and operating profits. Therefore, before engaging on the journey, it is important to obtain clear consensus on the strategic intent (Digital Strategy) and how it fits with the overall Strategy as well as the financial objectives of the enterprise. Then, the development of a business plan and blueprint for transformation and operational execution can begin. A well thought-thru blueprint needs to consider Governance, Organization, Process as well as business operations aspects.
Financial / Legal / Accounting: Business Model transformation requires setting up a new contractual framework as well as applying a different set of booking principles. Liabilities in relation to e.g. KPI’s, SLA’s fulfilment and new headcount need to be accurately allocated. In the end, all this affects the profitability of the new business significantly and therefore is a discipline that needs to be developed in the organization.
Skill Development and Alignment: a successful business model transformation is highly dependent on people that bring the right skills/ capabilities. Skill Development and alignment in the organization is a key success factor for building an effective operation with minimal friction and maximal synergy with the existing organization. Misaligned capabilities, solutions, positioning and skills negatively impact the potential for profitability.
Process/ Guiding Principles/ Infrastructure: Business model transformation requires setting up a new process and ecosystems. The new Business processes need to be closely integrated with the existing process landscape the product organization is using to guarantee a friction-less business operation. Also, a set of guiding principles need to be developed that allow managers in the organization to make their decisions on a day to day basis. Topics like Partner Management as well as Account Development need to reflect the company’s strategy and not the initiative of a single business unit. Also, a different set of KPI’s need to be developed to manage the new business model (EDA Input).
Organizational: Often, organizational structure is defined to deliver the old business model effectively. A new organizational design might be required to develop a successful and sustainable new business in the market. The level of centralization as well as the allocation of the P&L responsibility are some of the essential questions that a company needs to answer when engaging in new business model.
Business Model Transformation is a different discipline that is more related to change management/ service led transformation. This discipline is not new and a well-established transformation practice.
7. Digital Innovation – a new discipline
As much as the Agile Enterprise needs to be quick in detecting changes in the external fabric, it is the speed of translating this into the internal fabric that will eventually determine success. With a blossoming start-up culture, the option to “buy and integrate” might become the more attractive choice in order not to miss the window of opportunity at the customer front. This is a critical competence for thriving in a digital world. If Siemens had not passed the opportunity to buy CISCO at an early stage, they might not have missed the IP market trend and still have a thriving telecom business.
A new Digital Innovation Discipline needs to be developed introducing new paradigms in the organisation around how Innovation is done.
Make/Buy/Partner Process in a digital age
The Make/Buy/Partner Decisions are the anchor points around which digital innovation crystalizes. This is in multiple locations in the enterprise: Make/Buy/Partner Decisions are taken at key milestones in the governance of the following activities
Agile Business Process Management (as defined in 4.)
Business Innovation
Following factors should play an important role in the make/buy/partner welded together in a decision matrix:
Strategy: strengthen/build a strategic activity/ business area?
What is the Window of Opportunity? Can it be influenced? Competitive Positioning?
Resources: availability and critical character?
What are the Partnering Options?
Opportunity Cost?
As much as these questions are stating the obvious, making the right make/buy/partner decisions is a crucial competence in the Agile Enterprise. Especially when partnerships are an option in which data is shared, caution needs to be taken in execution of the partnership, considering what will happen to the data once you share it as well as looking at the fine print of the contractual framework related to data ownership.
Also, more and more external data on competition and market needs to be an integral part of the decision process. This is a competence that needs to be built up in many enterprises, developing a strong scouting capability and bring that knowledge inside of the organisation in the key decision forums.
As errors are inevitable and timing is of increasing importance, decision cycles should become shorter and innovation should be more customer centric instead of technology centric. In this field, there is widespread potential for improvement across most industries.
Customer Centric Innovation
Methods for Customer Centric Innovation are slowly hitting mainstream level. Design Thinking Workshops are taking place across all industries united around the idea that innovation speed at the customer front is much higher than the internal innovation speed. This results in a pipeline of concepts and solutions that needs to be subjected to a critical evaluation before being turned into a Minimal Viable Product. Somewhere in the governance of this pipeline, make/buy/partner decisions will give direction and a landing ground for the innovations in the organisation. In order to facilitate a soft landing of this new business 2 disciplines need to be worked on:
Implementation: Facilitate Implementation with Ecosystem Partners - some Enterprises decide to establish a Digital Innovation Hub, a lab environment where together with Partners, new business approaches are being worked on. This is a viable approach as long as there is an underlying (digital) strategy driving the selection of the partners.
Integration: Accelerate Organisational Integration of new business by creating a sandbox type of environment where new business can grow without having the complete corporate overhead to deal with and nevertheless having full access to the organisation. Such a new business governance concept needs to be developed that can easily be communicated / introduced as well as being compliant with corporate reporting guidelines.
References:
1. Why you need a digital data architecture to build a sustainable digital business – McKinsey Quarterly 2018 - https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/why-you-need-a-digital-data-architecture
2. Digital-Transformation-Strategy-Compass-Concept-Note-The Mobile Project (2017) - https://www.themobileproject.net/single-post/2017/11/02/Digital-Transformation-Strategy-Compass-concept-note
3. Corporate development with agile business process modelling as a key success factor, Daniel Pashek, Elsevier 2016, https://ac.els-cdn.com/S1877050916324425/1-s2.0-S1877050916324425-main.pdf?_tid=63911c2b-1590-4496-8c3d-d35e49dbad85&acdnat=1537906908_1dc020f3e58675b3a9cc5526b79af884
4. Signs of a Corporate Immune System designed to Kill Innovation (The Mobile Project 2017) - https://www.themobileproject.net/single-post/2017/11/28/Signs-of-a-Corporate-Immune-System-designed-to-Kill-Innovation
