Transforming to a Digital Organization
Building a holistic consumer centric value chain with a single success criterion across the value chain, A CXO perspective
by Shafeer Badharudeen, Chief Technology Officer
Digital is the talk of the town as consumers that every business is targeting have changed from a state of scarcity to state of abundance. Hence providers of products and services need to be precise in all 360-degree directions to deliver to the context of the consumer. Everyone talks digital through their own interpretations wherein each diverse interpretation is reflecting only the one-sided focus that organizations end up calling as digital. But often such approaches will not be truly reflecting the true business outcomes expected to happen from a true digital transformation. That being the fact and reality, it would be interesting to look at the outcome expectation from applying digital everywhere. The fundamental transformation digital should be bringing to the organization is the transformation to a real-time organization that can self-adapt based on the ecosystem turbulences. Let us look at how that transformation can be approached in a structured manner considering the as-is state.
A practical approach to digital transformation would be to take into account the as-is state of the digital maturity level of each of the portfolios by calculating the distance they have to traverse to correlate and match to the context of the holistic digital adaptation the company would be intending to transform. A decision on the desired digital outcomes at the company level first would be required before backtracking the same at the portfolio levels by taking stock of the reflection of the respective practices, data coverage and integrity, actors, workflows, systems and channels with touch points attributing to the business outcomes.
Let us first look at the digital outcome expectations of a company. Predictability and Precision are the broader buckets under which business outcome indicators can fall in for any company irrespective of their nature of business. Predictability and precision of topline and bottom-line should be the common payload across the organization for defining the transformation journey from the respective portfolio angles. Here, portfolio reference is for the ones that are relevant to the business ecosystem context. Predictability and precision buckets would include predictability and precision of the topline and the operational cost line items that falls in between top line and bottom line. Topline when drilled down further should include predictability of the dependent factors influencing the topline such as growth model, customer base, market share, margin etc. In similar way, operational cost includes the cost of workforce across portfolios, the cost of supply chain, inventory cost, raw material cost and the dependency relationships between them.
Prior to defining the correlation mapping between the company level digital goals and objectives with respective portfolio level goals and objectives, one of the preliminary hygiene to ensure as part of the digital transformation is the integrity and trust of the data to be taken into consideration for workflow definition and decision making. Integrity, trust and real time nature of data from the root data source have to be achieved by exploring the adoption of Internet of Things (#IoT) wherever it makes sense. With sensors available for almost all kinds of real time data collection requirements, be it environmental sensing, people tracking, health data sensing of humans and machines, soil data sensing, visual and aerial sensing etc., the same has to be leveraged to the fullest extent to avoid the human dependency on the data collection.
Business ecosystem includes a network of organizations performing various roles. In the consumer centric business ecosystem where each and every performance indicator gets tracked from the context of the consumer, it is critical to ensure the integrity of the data by deep linking it to the root source in the business ecosystem. As transparency and trust of the data from the consumer context has to be kept intact throughout the supply chain from the root source till the customer delivery, organizations transforming to digital should be looking at establishing or being part of a #Blockchain network that ensures the data integrity and trust before they transform their workflows and systems to digital. In similar ways, if the company as part of its operations and maintenance lifecycle management is leveraging an extended business partner value chain, the core payload driving the respective value chain should be brought under a Blockchain network that can ensure single source of truth across the value chain. For example, if the asset life cycle management involves usage of assets by servicing partners on one end and the regular maintenance and calibration of the asset by respective OEMs at the other end, it is suggested to bring the asset lifecycle payload on #Blockchain as well.
Once the data integrity is ensured with single source of truth reflecting everywhere in the value chain, the next step would be to ensure an integrated data pipeline within the organizations’ value chain to ensure that, a solid data foundation is set for systems within the respective portfolios and actors performing the right actions and decisions by taking into account the right kind of context and correlation mapping of the data. Integrated data pipeline will set the foundation for addressing the challenge of information silos that exist in the as-is IT system landscape. Having mentioned that, it is for the portfolio anchors to request the IT to break those silos as part of mapping their portfolio objectives with organizational objectives of bringing precision on the outcomes. As part of becoming a lean organization that follows the lean SLAs across, it’s very important that information and insights flows across the portfolios seamlessly. For example, the shop floor in a manufacturing enterprise should be having complete visibility on the sales order pipeline, the inventory pipeline and the warehouse and supply chain pipeline to ensure that they remain lean between demand and supply. In the consumer centric business ecosystem where real time responsiveness across the nodes within the value chain becomes important, organizations as part of their digital transformation should be creating an integrated data pipeline much earlier in the transformation journey. This is where the adaptation of #BigData technologies should be explored for setting up the integrated data pipeline.
Revisiting of the process workflows and relevance of actors within the respective process workflows should be evaluated next from the re-engineered context of integrated data pipeline and data integrity assurance ensured through Blockchain. In the consumer centric business value chain, workflow processes should be following the lean SLA models across the value chain. In order to achieve lean SLAs, workflows should be real-time in nature and actors within the workflow should be equipped with real-time resource availabilities, real-time decision support enablement and real-time decision making. Actor efficiencies should be ensured through the infusion of Artificial Intelligence (#AI) and predictive decision models covering 360-degree dependency insights presented to human actors for ensuring data driven decision making. Connecting other dependency dots which if not connected and correlated will result in leakage of operational cost and process completion delays also have to be looked at. Robotic Process Automation (#RPA) can be adopted in the workflow areas where high volume, repeated tasks which humans were performing earlier.
Identifying the coverage and depth of the input signals and the authenticity in terms of the precision reflection of the business parameter they convey to the nodes dealing with the respective topline influencing factors is one of the crucial first step in designing the portfolio that can be transformed with digital. Whether the data originates from the root source or it gets abstracted at several levels as part of business model boundaries matters a lot while considering the authenticity of the input signals fed for decision making. For example, Walmart as a consumer centric organization that wants to deliver the best grocery to their clients, need to track the supply chain of the grocery to the level of farm if they want to truly reflect the objectives, they are outlining at the management level. In the digital world, where every business re-defines their business models keeping the consumer at the center, their respective portfolios also should reflect the same considering the 360-degree perspective of the consumers and the variety of ever changing options spectrum available for him/ her for what he/ she wants to fulfil.
At the portfolio levels, dependency relationships between the company’s topline/ bottom-line measurement factors and portfolio level factors influencing them are crucial.
If we take procurement portfolio as an example of how its digital journey should be, mapping the top objective back to procurement should result in procurement leveraging digital technologies like #Blockchain for payload supply chain that include external and internal actors, #AI for quality assurance and insisting #IoT on the farms. Relevance of the workflows dealing with those input signals, identification of the roles and the intelligence index the actors should possess and the digital outputs to be achieved and fed into different other nodes within the value chain that ultimately delivers the topline also have to be relooked from the context of the perspective transformation required to map the respective portfolio outcomes with topline. In this process of identifying dependency relationships, one of the key checkpoints related to maturity towards digital is to explore whether single version of the outcome influencing parameters are being shared across all other dependent portfolio nodes or not.
Let us look at the manufacturing workflow as an example to highlight how digital has to transform the value chain. Industry is talking about Fourth Industrial Revolution (4IR) and the journey towards “Factory of the Future”. At the portfolio levels, the concept will translate to SMART and integrated sales lifecycle management, SMART procurement, SMART asset management, SMART and lean inventory, SMART shop floor, SMART warehouse, SMART supply chain, SMART product lifecycle management (PLM), SMART SCADA, SMART surveillance and security. What is the definition of ‘SMART’ across manufacturing portfolios from a digitization context? Are all these “SMART” transformations converging to a common objective of elevating the topline? If not, though we can call them “SMART” from the context of operational process automations we would have achieved in the respective portfolio levels, they wouldn’t be ultimately delivering the end results expected at the company level.
Let us specifically look at the sales portfolio transformation from the context of as-is state to a portfolio that handles sales lifecycle in an integrated and SMART manner. As-Is state include several discrete process models for campaigns, leads, opportunities, sales and accounts with very limited interactivity between them. Also, the outcome flow from the sales node to subsequent value chain nodes are more or less confined to updating of order quantity to warehouse and to shop floor depending on the nature of the order. Sales portfolio has a major role to play in creating a consumer centric digital value chain while ensuring that “lean, sleek and optimal” model is practiced across the value chain nodes. As part of that, sales portfolio should be feeding in the order and conversion trend to inventory management system for maintaining a lean and perpetual inventory while also ensuring a lean warehouse. When we build the digitally transformed integrated sales life cycle management portfolio, it should also be taking into account the reflection of the performance of various internal portfolios like customer support, after sales service, quality etc. to reflect customer sentiments, market sentiments etc.
Distributed intelligence and real-time adaptability to the ever-changing environment should be the hallmark of an organization that has embraced digital in its broader sense. As part of reflecting the real time objective of the organization, it is also important to look at the adaptability of the digital tech stack across the organization for the right context that reflect the direct correlation mapping of portfolio I/O signals with the digital outcome defines for the organization. Digitally transformed organization should be having sensors, actuators, real time #AI powered intelligence, robotic processes, real time predictive intelligence extraction at respective places in the value chain from veracity of data feeds and the integrated data pipeline that ensures 360-degree coverage for decision support. But unless and until the digital technology stack gets applied for the right context within the top-line and bottom-line payloads management business supply chain, right transformational outcomes will remain as a far-fetched dream.