From Supply Chains to Digital Supply Network and Digital Collaboration Networks

Digital has a massive impact on the supply. Adding digital technology to enhance is not enough. Companies must re-invent their supply chains making their underlying DNA digital.

The Supply “chain” has evolved from linearly thought process to a circular concept (Circular Economy) to a now system of networks (Digital Supply Network).

This new Digital Supply Network allows to add/ drop partners and contributors fast and fill any disruptions with immediate alternatives.  It maximizes access to information, knowledge, innovation, resources, materials, infrastructure, services, products, etc.  It enables to respond to market opportunities at lighting speed and scale large without requiring upfront large investments. Cloud and XaaS services offering often almost immediately pay per use solutions.

Digital Supply Networks require a new vision and way of thinking. Traditional, text book supply chain methodology breaks down.

Disruptive technologies such mobile, social media, cloud, big data & analytics enable unprecedented opportunities to gain a holistic and detailed understanding of the real-time situation and take the best decision for the particular moment. Like smart IT networks automatically reconfigure themselves when one node breaks, so digital supply networks will equally and easily adjust. Mass production and mass customization are now fully possible fast and very efficiently.

Digital Supply Networks will then finally evolve into Digital Collaboration Networks, where there will not be one major driving company that procures from “outside” to produce/ deliver their products and services, but rather where a collection of individuals and organizations collaboratively add and receive inputs and support to create a collection of outputs, products and services.

What companies can/ should do?

 -       Follow a systematic approach

-       Re-visit your business strategy and align to the vast changing market, customer and competitive environment

-       Identify core strengths and capabilities across the key value chains.

-       Develop suitable Operating Model, architect a blueprint for the future.

-       Drop none-value adding work. In-source and outsource accordingly.

-       Streamline your processes, people and metrics accordingly.

-       Drive value transformation and optimization across the entire organization

-       Extend to your effort to your partners and tier 1 suppliers

-       Use data & fact based approaches (Lean Six Sigma, etc.), digital technologies (Big Data & Analytics, AI, Visualization etc.) to analyze complex cause-and-effect interrelationships and to gain an “end-to-end”/ holistic understanding for executive planning & decision making.

-       Think and optimize in concentric overlapping life cycles of products, services, innovation,

-       Focus on execution excellence, but in an agile, experimental way of continuous improvement

Specific examples of how digital impacts key functions within the organization

Procurement

Companies need to blueprint the future procurement operating model, optimize spend demand management through zero-based budgeting, sourcing for direct/core categories, relationship management and risk strategies. They need to improve total value of ownership by reducing overhead expenses and COGS; develop new cash flow streams through supplier innovation; reduce environmental and community development costs; decrease working capital.

The procurement operating model blueprint maps how a client’s procurement organization will operate across their organization, process, talent, and technology (and digital) landscape in order to implement their strategy and achieve the targeted operational and financial improvements.

Companies need to better plan and optimize their supply chains. At British Telecom we drove the reduction of the large supplier base with the objective to selectively focus on less suppliers, but developing more partners that would help BT achieve its strategic objectives and to achieve more collaboration, value contribution, innovation, speed, delivery capability and operational excellence.

Product lifecycle management (PLM)

Traditional product value chains used to be linear. Now they are fast-moving product development value networks, encompassing an extended ecosystem of partners, suppliers, manufacturers and customers—all influencing the product lifecycle.

Digital enablers and new technology paradigms have become part of the product development and lifecycle management process, utilizing big product data and digital infrastructures

Digital technologies can now reduce marginal cost of supply to near zero. Companies like YouTube, Kickstarter, Airbnb and Uber show you don’t need to own assets to provide trusted access. The cost for each of these companies to add a new room, video or car is near zero.

Digital allows the industry’s value chain to be completely unbundled. There are thousands of start-ups attacking existing markets of incumbents.

Customers use digital to change the way they interact with products, companies are looking for ways to use digital to develop them. “Words like ‘gym’ or ‘shops’ are nouns that describe a business but no longer define it. Digital is making the nouns a lot less relevant than the verbs.

Companies must take a holistic, transformational perspective on Innovation, Product Development and PLM. They strengthen outcome-driven business discipline that harmonizes people, process, data and systems. Everything should be driven by a measurable, outcome-driven business case.

R&D and Advanced R&D

When working with Huawei on developing and enhancing its Advanced R&D capabilities years ago, we looked at industry best practices to drive transformation. Today Huawei is an industry leader in new annual patents. Huawei eagerly learnt from the best and become a star.

Digital calls companies to rework their global operating model in R&D; planning and procurement; manufacturing locations; talent acquisition, retention and growth. The focus must be to develop and launch the right product, at the right time for the right cost.

 Product portfolio management

Companies need to adjust and optimize their product portfolio. It requires reducing complexity (using insight driven customer demand) and cost-to-serve to improve margins and minimize product costs.

Frugal Innovation, a term coined in developing countries, is a great concept that applies also to the developed markets. Basically, it focuses on just the features that a potential customer is just willing to pay and dropping other cost drivers that are just waste.

XaaS is more than just a new way to deliver technical capabilities, it is a major shift in the fundamental business model of the industry. XaaS allows companies to sell differently, to an expanded set of buyers, with a different value proposition – all of which much be backed up by a transformed set of commercial capabilities.

It also allows to reorganize engineering capabilities in order to increase developmental agility while maintaining quality and predictability.

In a time when consumers increasingly want to rent or pay for use, rather than own, companies need to adjust their business models. It may require organizations to diversify their business and play with numerous business models.

Ensure strategic alignment between the application landscape and business imperatives

• Reduce application redundancies and drive standardization

• Assess and address technology risks

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Big Data & Analytics - the full view (upon request)

Upon request, I have put together the five parts of the previous published Big Data series and combined into one documents. This offers you to read everything in one place. Please share your thoughts and best practices with me. You always may email me directly to alexwsteinberg@gmail.com
Big Data Series - Part 1   Technical challenges
Big Data requires to learn much about data as an asset and analytics. Data is the most precious asset in an organization, the currency of the enterprise.
Companies’ data ecosystems have become complex and littered with silos. A large majority of companies is still not able to make full use of Big Data advantages.
There are many challenges with Big Data: Lack of knowledge, varying definitions & expectations, different views about data sources and use cases, ignorance about valuable data sources, technologies, etc.
Companies must understand data across the entire data supply chain and their individual stages: Identifying & leveraging data sources, importing, enhancement of data value, combination with other data, generation of insight, and taking of specific actions.
This means: companies must mobilize data across the enterprise; deeply understand, analyze and determine value of respective data; understand business use case and data patterns to determine appropriate actions.
It requires companies to commit to continuous discovery, experimentation, testing, learning, adapting and innovation.
There are many approaches, solutions and technologies presently offered in the Big Data domain and quickly evolving. Companies need to be aware of the different options and their pros & cons to combine those to an overall solution.
Continue part 2 out of 5  
Big Data Series – Part 2 - Traditional data approaches not enough anymore
Given the varying types, sources and sheer size of data today the traditional approach of collecting data in a staging area, transforming into desired format, loading in mainframe/ data ware house and then delivering requested data to users on a point by point query does not work well any more.
Companies must perform calculations, run simulations models, compare statistics at fast speed to generate insights. Real-time analytical tools able to pre-process streaming data and correlate data from internal and external sources, offer interesting opportunities, but also complex challenges.
Data acceleration enables massive amounts of data to be ingested, processed, stored, queried and accessed much faster. It ensures multiple ways for data to come into the company’s data infrastructure and be referenced fast.
Data acceleration leverages hardware and software power through clustering and helps correlate different data sources, including localization. It improves interactivity by enabling users and applications to connect to the data infrastructure in universally accepted ways and ensuring that user queries are delivered as quickly as required.
Continue part 3 out of 5
Big Data Series – Part 3 Six technology components for Data Acceleration
There are at least six key technology components to build a supporting architecture: Big Data platforms, Ingestion solutions, Complex event processing, In-memory databases, Cache clusters and Appliances. Each component helps with data movement (from source to where needed), processing and interactivity (the usability of the data infrastructure).
Big Data platform (BDP)
BDP is a distributed file system and compute engine. It contains a big data core, a computer cluster with distributed data storage and computing power. Replication and sharding partitions very large databases into smaller, more easily to manage parts in order to accelerate data storage.
Newer additions enable more powerful use of core memory as a high-speed data store. These improvements allow for in-memory computing. Streaming technologies added to the core can enable real-time complex event processing. In-memory analytics support better data interactivity.
Further enhancements to the big data core create fast and familiar interfaces with data on the cluster. The core stores structured and unstructured data, but requires map/reduce functionality to read. Query engine software enables the creation of structured data tables in the core and common query functionality (SQL etc.)
Ingestion
Collecting, capturing and moving data from its sources to underlying repositories used to be done traditionally through the extract, transform and load ETL method. Today the priority is not the structure of the data as it enters the system, but assuring that all data is gathered covering different increasing data types & sources and quickly transported to areas where it can be processed by users. Ingestion solutions cover both static and real-time data. The data the gathered by the publisher and then send to a buffer/ queue, where the user can request the data.
Complex Event Processing (CEP)
After data ingestion the CEP is responsible for preprocessing and aggregation (& triggering events). It tracks, analyzes and processes data of events and derives conclusions. CEP derives data from multiple sources and combines historic as well as fresh data in order to infer patterns and to understand complex circumstances. Its engines pre-process fresh data streams from its sources, expedite processing of future data batches, match data against pre-determined patterns and trigger events based on detected patterns.
CEP offers immediate insight and enables fast action taking. In-memory computation allows to run Data movement and processing in parallel, increasing speed. CEP solutions add computing power by processing the data before it is submitted to the data stores or file systems.
In-memory databases (IMDB)
IMDBs are faster than traditional databases, because they use simpler, internal algorithms and executive fewer central processing unit instructions. The database is preloaded from disk to memory. Accessing data in memory eliminates the seek-time involved in querying data on disk storage. The applications communicate through SQL, which receives records in the RAM and triggers the query optimizer.
IMDBs constrain the entire database to a single address space. Any data can be accessed within microseconds. The steadily falling RAM prices favor this solution.
Cache Clusters
They are clusters of servers in which memory is managed by a central software designed to transfer the load from upstream data sources (databases) to applications and users. They are typically maintained in-memory and can offer fast access to frequently accessed data. They sit between the data source and the user. Traditionally they accommodate simple operations such as reading and writing values. They are populated when a query is sent from a data user to the source. Prepopulating data into a cache cluster of frequently accessed data improves response time. Data grids can take caching a step forward by supporting more complex queries and using massive parallel processing (MPP) computations.
Appliance
Massive parallel processing sits between data access and data storage. Appliance here is a pre-configured set of hardware and software including servers, memory, storage, input/output channels, operating systems, DBMS, admin software and support services.
It may have a common database for online transactions and analytical processing, which improves the interactivity and speed. Appliances can perform complex processing on massive amounts of data.
Implementing and maintaining high performance data bases on clusters is challenging and few companies have the necessary expertise to do so themselves.
Custom-silicon circuit boards enable to develop their specific solutions. It enables development on devices for specific use cases and allows for network optimization (integrating embedded logic, memory, networking and process cores). This plug and play functionality offers interesting possibilities.
Continue part 4 out of 5
Big Data Series – Part 4 Creating a suitable Technology Stack/ Solution
All of these components bring their individual technology features. Companies must wisely put together an overall solution from among those components, leveraging their complementary advantages and customizing those to their particular needs.
There are four fundamental technology stacks (with their variations) offer possible solutions:

1. Big data core only or with enhancements (with complex event processing, with in-memory database, with query engine or with complex event processing and query engine)
   • This technology is the de-facto standard for exceptional data movement, processing and interactivity.
   • Data usually enters the cluster through batch or streaming.
   • Events are not processed immediately, but in intervals. Enables parallel processing on large data sets, and thus advanced analytics.
   • Applications and services may access the core directly and deliver improved performance of large, unstructured data sets.
   • Adding CEP enhances big data core processing capabilities, real-time detection of patterns in data and trigger events. Enables real-time animated dashboards. Could add machine learning program to the CEP.
   • IMDB can further increase computing power through placing key data in RAM.
   • Query engines can further open interfaces for applications to access big data even faster.
2. In-memory data base (IMDB) cluster only or with enhancements (with Big Data Platform, with complex event processing)
   • External data is streamed in or transferred as bulk to the IMDB
   • Users and applications can directly query the IMDB, usually through SQL like structures.
   • The incoming data is first pre-processed through the BDP before it goes to the IMDB
   • In case of CEP, the CEP first ingests the data; the processing is then done in the IMDB and then returned to the application for faster interactivity.
3. Distributed Cache only or with enhancement (with Application and Big Data platform)
   • A simple caching stack sitting atop of the data source repository. The application retrieves the data. The most relevant data subset is placed in the cache.
   • Processing of the data falls to the application (may result in slower processing speeds)
   • If BDP, the BDP ingests the data from the source and does the bulk of the processing, then puts data subset in cache.
4. Appliance only or with enhancement (with Big Data platform)
   • Data streams directly into the appliances; the application talks directly to the appliance
   • If BDP, the BDP ingests and processes data. The application can directly talk to the appliance for queries.

Continue part 5 out of 5

Big Data Series – Part 5 – 12 Immediate suggestions to build a data supply chain

• Consider data as perhaps the most important asset in your organization. Become data driven. Some people call it “data religious”.
• Research about Big data & Analytics best practices. It requires continuous learning. Refer to the different approaches offered in previous blogs (Data Acceleration Part 1 and 2).
• Do an inventory of existing data. Focus on most frequently accessed and time-relevant data.
• Identify, simplify and optimize inefficient data processes. Eliminate manual, time-consuming data curation processes (such as tagging and cleaning).
• Identify currently unmet business needs and develop solutions.
• Identify and overcome data silos.
• Simplify and standardize data access through a robust data platform
• Build an effective technology stack using one of the four suggested options while leveraging some of the described six components (Data Acceleration Part 1 and 2).
• Further explore API management, traditional middleware, PaaS and other possibilities
• Analyze current internal data sources and look for still hidden sources. Explore external sources to increase quantity and quality of available data.
• Identify and improve individual data supply chain streams
• Develop a systematic roadmap for building an effective overall data supply chain

Special thanks to Accenture Technology Labs and Analytics Group, whose thought leadership, best practices and white papers have served as inspiration and knowledge source for this Big Data series.

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How Telcos can develop into Integrated Digital Service Providers

The majority of telcos have digital agendas to build multi-channel or omni-channel capabilities. However, their digital transformation is often only in the early stages.

Telcos to become Integrated Digital Service Providers

The objective for telcos should be to develop into Integrated Digital Service Providers, bringing together digital infrastructure, digital business operations & capabilities and digital offerings.

Telcos could become key players in the digital value chain by assuming new roles and offering new services such as: M2M enabler, Cloud Service provider, one stop IT service provider, smart city enabler or offer vertical solutions (digital home and home health care integrator, transport tolling partner, etc.).

Telcos need to take necessary actions

In order to do so, telcos must rethink their current customer operations and inherent BSS/ OSS landscapes. Core capabilities should be extended to campaign management, order entry, fulfillment, charging & billing, self-service user interface and other.

Operators should increase their strategic capabilities in the service market including omni-channel experience management, single order product catalog and entry function for all sales channels, integrated policy management & control. Partner enablement across the value chain must include M2M and over the top providers, Content, resellers, roaming, wholesale and other players.

The use of APIs and techniques next based action, Unified Marketing, social sentiment analysis, real time charging, can help.

Data need to be integrated with decision support and campaign management systems as well as the analytics engine to trigger context aware events in real time. Customer platforms need to enable marketing campaigns down to the micro and nano level of segmentation and customization. They must support a seamless omni-channel experience, including crowdsourcing. A key word is mass differentiation.

A Web and mobile Portal needs to effectively enable ecommerce, Mobile & Web care, Collaboration Community and order entry. Cloud based sales & services need to guarantee Social listening & Ads, Lead & Opportunity, management, forecasting, etc.

Such system needs to bring together all key parts such as Customers, Prospects, Partners, Social networks, Call Centers, Shops, Connected devices, etc.

How to bring things together for an overall solution

One approach is to split the production systems (Billing & collection, accounts receivables & payables, CRM) from the distribution systems (omni-channel, customer experience management, product catalog, order entry) and integrate those through a Hub.

This Hub could serve as a layer above the network and BSS/OSS layers and then enable digital marketing, online sales, eRetail, smart care and other functions.

Other initiatives could complement:

1)      Drive agile and design thinking across the organization.

2)      Simplify, minimize and standardize. For example, examine and address the overlapping boundaries and inefficiencies among business relationship, development & transformation, IT governance and maintenance.

3)      Leverage SaaS technologies or build virtualized software-based operational stacks.

4)      Move to cloud or outsource tasks such as commissioning, trouble ticketing, fraud & churn analysis, work force management, roaming settlements and partner management.

Work the architecture at two speeds

The backend and transactional core systems of records must be designed and operated for stability, resilience, scalability, reliability and high quality data management. All telcos, different to digital native companies, will need to build on their existing legacy systems. Release cycles will be longer here.

The customer facing front part of the architecture requires fast and highly agile software development and servicing. New micro services must be deployed within hours. Developers should be able to use a wide range of programming languages without being locked in by a stringent development frame work. Business users should be able to make immediate changes to automated processes. Time consuming integration work must be minimized. Decouple products from the processes. Enable work load balancing across private, public and other clouds.

Build a new organization and governance model in parallel with the technology.

The Enterprise Architect’s opportunity to play key role

The Enterprise architect plays a key role to help the CIO drive the digital transformation. The skill set of enterprise architects of the future will include business strategy formulation & execution, business innovation, stakeholder management and agile management. The EA needs to support both hunting and harvesting.

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Applications for competitive advantage - recommended actions

Applications have become a key driver of strategy, innovation and competitive differentiation. Applications are a crucial gateway to seamless customer experience, new services, and revenue streams. Application and business strategies need to align and merge over time.

Companies need to become software driven businesses. They require a new mind set and way of working, an overall organizational approach to business, IT and applications.

Many opportunities and much to be done

A new IT/ OT operating model needed

IT and Operational Technology must increasingly integrate in the age of IoT. Companies require a new IT operating model and a way of how they design, build, use and manage software. Enabling software in itself is becoming a revenue generating product.

The cloud can help mesh together the formerly inaccessible enterprise and machine generated data. It will help bring different business functions even closer together.

New software development thinking

Traditional coding of applications with complex, lengthy implementation cycles does not meet the business requirements any longer. Companies require modular architectures. They need to use next generation integration techniques, driven by a mobile-first, cloud-first mind set.

Applications need to be quickly assembled out of existing, small, reusable components leveraging modular architectures.

Leverage available technologies

Massive amounts of available data, processing power, natural language learning, cognitive computing and machine learning, rule-based algorithms and other advances in data science call for embedding Software Intelligence directly in the applications or processes.   

Intelligent automation helps achieve major productivity increases, minimize errors and throughput time. It also can effectively support and enhance humans in higher quality work. Integrated Analytics enables Applications to analyze, comprehend and take appropriate actions independently.

Digital Agents, enabled by self-governance, are already serving customers. The artificial intelligence company IPsoft has already deployed an effective digital help desk application that can understand human language in 10 languages, search knowledge and databases and respond to specific customer questions within seconds.

Develop better software

The technological advancement enables also of how software can be developed. Test automation tools can use cognitive computing and robotics to generate test artifacts (scenarios, conditions and results) based on plain text functional requirements.

Post deployment tools for service operations can continuously accelerate problem resolution by curating specialized application knowledge and leveraging descriptive analytics and natural language processing.

Applications can and should now automate routine tasks, improve business processes through integrated analytics und ultimately govern themselves.

Leverage Agile, DevOps and other agile engineering techniques!

The importance of APIs

New Application Programming Interfaces (APIs) must enable flexible, efficient exchange of internal and external software components and services. The Internet of Things will bring together all current IT devices with technology equipment, sensors and other devices.  Products will increasingly turn into product-service hybrids.

Support Big Data & Analytics correctly

Extracting the biggest value from Big data & Analytics, requires the right structures, processes and components across the value chain. Big data architectures need to be embedded within the business processes and applications, not at alongside.

Re-work IT systems

One of the barriers is the often monolithic nature of IT systems. Astonishingly, 70 percent of all business transaction still happen in COBOL. Enterprise architecture must support platform integration capabilities, security, API lifecycle management and monitoring. Virtualization, abstraction, simplification, separation of technical and business logic, modularization, componentization and containerization are effective techniques.  

As part of an ecosystem, the individual player need to work together to mitigate the risks of connected applications. Obsolete and legacy applications carry limited or now security built in and must be tightly managed.

Unfortunately, while key technologies are advancing at massive speed, business processes and applications lag behind.

Use IT across the organization

On a larger scale the formerly stand-alone IT function need to be integrated in and fully used by the individual business functions across the organization and value chain.

Integration, Orchestration and Business Process Management services will help configure applications customized to business needs at an ongoing basis.

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Keys to building your digital commerce platform right

Building effective commerce platforms are important to meet the sophisticated needs in the digital age. The undertaking is very complex as it requires work on the strategic, tactical and operational level. Looking only at technology is a frequent shortcut to failure.
Every larger company should consider working with a service provider that can ideally address all aspects of this complex undertaking.
Based on previous projects, I provide you with a check list of key areas and recommendations.

Vision, strategy and business model
Your service provider (SP) should be able to help you develop/ refine your digital vision, strategy and business model. Your SP should be able to help you build a roadmap for transforming your organization.

Management, business and technology consulting
Your SP should not only speak tech-language, but truly understand your business needs from top to bottom. Throwing technology at problems, before clarifying/ solving the business side, often only creates more problems.
The SP should provide true vertical domain knowledge, including customer behavior & 360 degree view, Omni-channel objectives, partner models, inventory, pricing and sales.

Operations
Many areas are obvious candidates for outsourcing. Your SP should be able to take you through various options such as hosted, managed services, performance based pricing models, staff outsourcing, etc.
As requested, the SP should be able to provide commerce infrastructure and operations services (advanced automated site testing, performance management, security testing on cloud platforms)

Systems
Often upgrades to ERP and order management systems are necessary. The SP needs to be able to integrate disparate internal client systems (legacy, home grown ecommerce systems, etc.) and advise on design and architecture.

Technology
Ability to implement the technology flawlessly has become a basic requirement. The SP need to implement a solid commerce technology infrastructure able to meet the expected demands in the future. It involves upgrading and optimizing existing sites and integrating diverse technology programs to enable a comprehensive digital experience. As needed ecommerce, call-center, in-store and other areas need to be fully brought together; applications, mobility wisely integrated.
Big Data & Analytics increasingly drive the marketing of the digital age. XaaS and Cloud enable faster, better and more efficient business and operations. The SP needs to understand these areas and incorporate those effectively into the overall solution.
The SP should offer accelerators and own of the shelf software and solutions to minimize time/ cost to market and maximize value of the new commerce applications. Further the SP must be able to provide solid post-implementation support.

Organizational alignment and Program Management
Markets, Customers and Competition are rapidly evolving. Realignment of the organizational structures, roles, processes, policies, procedures and metrics is unavoidable. The SP should provide guidance in organizational design, transformation & change management. Solid Program management and project execution should support all efforts.

Innovation and agility
The SP should be able to drive innovation and offer best practices from across the industry; leverage insight and solutions from its own innovation labs.
The SP should practice agile methodology and should drive agility throughout the organization.

Price/ Costs
Be aware that the price quoted is not the total cost! Some service providers may be considerable cheaper, but also come with substantial burden on the client organization in terms of increased management time and other overhead. The biggest – often unaccounted - expense – is that of missed revenue and business opportunity.

Engagement
Last but not least the SP should really support a collaborative arrangement and offer various pricing and operating models in line with the client’s needs and performance metrics.

Finding the right Service Provider
Not all Service providers (SP) obviously have breadth and depth of experience to provide the mentioned necessary service. Nevertheless, a good number of companies, also called Global Commerce Service Providers, are able to address most of those needs and provide full client solutions.

Accenture Digital, Sapient Nitro, Deloitte Digital, Razorfish Global, Cognizant and IBM GBS are among the leaders of GCS Providers. Strong contenders are Tata Consulting Services, Infosys, HCL, Wipro and others.

Finding and selecting the right Service Provider for your company is both a science and an art. This guide has given you some key pointers. For questions and thoughts, please let me know.
+++
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CIO actions to build/ improve IT operations

Companies are facing very challenging times. Here, a list of key actions that CIO and Heads of IT should consider. Many of these actions could be financed by vendors/ partners through managed services, cost and risk sharing models:

Build Operations

-          Enable ecosystems of things to respond to action, rather than static, predefine work flows and procedures. Guide end-to-end experience through user personae and journey maps. Monitor/ detect signals and predict impact in the market.

-          Decide on architecture based on use case and business outcomes: Embed intelligence on edge/ each device, in network, cloud broker or back on enterprise hub. Channels and Customer touch points are multiplying the complexity to bring things together

-          Manage all physical and functional attributes of sensors and devices; enable to remotely manage devices. Keep overview of spectrum of network technologies and protocols. Manage properly.

-          Integrate information flow from varying type of devices with proprietary protocols

-          Secure the entire system of devices, connectivity and information exchange. Manage security at the seams (devices, sensor, communication chips, analytics, event analytics, rules engine, etc.)

-          Virtualize and automate operating environment (server, storage, network, security)

-          Implement software defined networking (SDN). Systems must allow real-time integration across multiple services, servers, clouds, data stores enabling mobile devices to initiate requests from everywhere.

-          Build/ support digital platforms to handle all channel, campaign, context and content related activities. Effectively work with CMO to provide richer, target driven, targeted campaigns, promotions and properties. Understand that Marketing is becoming increasingly technology driven and enabled. Connectivity, data and technology have become part of the new marketing mix (with engagement as the forth).

Improve operations

-          Streamline, optimize and automate operations

-          Switch to out-of-the box solutions, minimize customizations and work on technical debt

-          Improve current technical systems through a persona based, user-centric focus.

-          Move applications to the cloud

-          Implement DevOps improving  requirements management, Continuous build, configuration and release management across the organization

-          Upgrade core applications on the existing platform, implement new solutions or overhaul / rebuild platform

-          Drive down operations, people and infrastructure costs. Lead progress in Software defined storage and Software defined data centers as far as feasible (applications strongly dependable on legacy hardware)

-          Drive other sustainable, green initiatives (including energy efficiency programs)


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To share your own thoughts or other best practices about this topic, please email me directly to alexwsteinberg (@) gmail.com.

Alternatively, you also may connect with me and become part of my professional network of Business, Digital, Technology & Sustainability experts at

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Tranforming supply chains with digital methodologies

The globalization and digitalization has massive impact on supply chains. Agile methodology can help in the transformation efforts and provide solid, practical guidance.

The ADAPT-model of the Scrum methodology offer five common activities:

• Awareness – that the current situation/ process is not delivering acceptable value
• Desire – to adopt/ change
• Ability – the necessary capabilities and skills to succeed
• Promotion – sharing experience and making sure that others see successes
• Transfer – managing the implications of using the new approach throughout the company

Awareness, Desire and Ability are overlapping, whereas Promotion and Transfer repeat and occur throughout the transition effort.

Mike Cohen, highly respected Agile Leader and bestselling author of “Succeeding with Agile” provides a very systematic and practical approach that can also be well leveraged for driving change and transformation programs in general. I have summarized from Mike and provided additional thoughts:

A transformation leader needs to engage in these activities on multiple levels:

• Organizational
  • A critical mass of people with similar awareness is required before the organization will collectively move forward
• Individuals
  • Organizations are made up of individuals. To change organizations, a transformation leader must change individuals.
  • Important is that individual are in different stages of awareness, desire, ability,  promoting change, transferring abilities/ learning to others. They progress differently and need different guidance & support
• As a team
  • Teams can be aids or hindrance to progress of individuals; enforce or undermine right attitudes & behavior
• Per practice
  • Functional units/ stages within the supply chain

Examining the ADAPT model in detail:

1. AWARENESS

Becoming aware that what worked in the past is no longer working can be extremely difficult. This is especially true for companies that are successful. There is almost always a lag between when the need to change first arise and when we become aware of it.

Impediments are:

• A lack of exposure to the big picture
• A refusal to see what’s right in front of us
• People confuse movement with progress
• People listen to their own propaganda

Good way to tools for developing awareness are:

• Communicate that there is a problem. Generate discomfort.
• Use metrics to reinforce core reasons to change.
• Provide exposure to new people and experiences. Encourage people to learn from others in the market, conferences, competitors, etc.
• Run a pilot to demonstrate success (and refine your approach)
• Focus on the most important reasons to change

DESIRE

Without desire there will not be any meaningful action.

Tools for increasing desire:

• Communicate that there is a better way
• Create a sense of urgency
• Build momentum
• Agree on a trial, get teams to test drive
• Align incentives/ remove disincentives
• Address fear
• Help people let go of the past and do not discredit it
• Engage people in the effort.

ABILITY

Becoming agile and equally transformation efforts require learning new personal and technical skills, thinking, working as a team and at different pace.

Tools for developing ability:

• Provide coaching and training (using various approaches & tools)
• Hold individual accountable (must understand that they are expected to apply new skills)
• Share information (collaborate across teams; learn from each other, use tools such as departmental intranet, Wikis, communities of practice and reading groups to disseminate information).
• Set reasonable targets, progress incrementally
• Just do it – Experiment, be patient and expect to make mistakes
• Fail often, fail fast, fail cheaply

PROMOTION

Promotion must lay the foundation for the next pass through the ADAPT cycle. Spread successes to raise awareness and desire for the transformation. Goal is to get the people to commit to the transition, not just merely comply with it.

A good idea is to not put a name on your transition, as it is harder to resist a nameless effort.

Seek shamelessly attention. The more often people here about the effort – even better see or experience it – the better. Use graphical displays, organize events, etc.

 

TRANSFER

A transformation effort requires the support from the other parts of the organization. Without their cooperation, most efforts are likely to fail, even when successful within their own group! The law of organizational gravity pools many innovative groups or good improvement efforts back to the beginning. Key functions to gain cooperation are HR, Marketing and Finance.

Agile methodology is proven. It is structured to embrace change and thus often provides better, faster results. Leading companies driving transformation efforts – across Organization, value & supply chains – will increasingly use agile methodologies to succeed.

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