Digital transform is probably the fuzziest coinage in today’s business world. Putting incessant effort into capturing too many moving portions, the digital transformation solutions into the visual disturbance. Furthermore, we are struggling to explain that it is an umbrella term. The question is – what is the significance of digital transformation? Are digital transformation services about walking apace with newer gadgets and newer software? Or the implication is that consumers desire to interact with the brands using a totally different means? Or could be it gives our retooling the means through which we conduct business to utilize what this new world of technology brings before us? The question is – are any one of the choices the cause or is it a cumulative thing?
So, let us check these two tricky things regarding digital transformation:
Number 1 – It is the customers that drive change. When we are mentioning digital transformation, we understand that it is not a mere commodity. It is a process that gets triggered on the C-level. They signify tectonic shifts in the manner organizations or businesses build also use software, the ways in which businesses maneuver internal operations, also eventually the ways those in the organizations think and perceive. However, does this necessarily come from within the business?
Do you remember when you had used cash the last time? Or when was the last time you sent a handwritten note? Most things have gone digital and we have gone used to interacting digitally with the world outside. Within enterprises, this kind of change in mindset is driven by the changes with our end consumers and we need to respond.
Number 2 – Digitization doesn’t signify transformation. Think of the changes that occurred in your office space where your office documents that were stored inside the employee’s computer have been shifted to cloud-based servers. For you to exchange these documents with your colleagues, we could export these or even write emails attaching exported documents with them. The broad idea is that digital transformation services don’t narrow down to mere substituting the old tools with the new ones that are digitalized. Instead, it simply implies a proper holistic change in relation to technology also the ways in which people think about using the technology today. Instead, it implies a complete change in relation to both the changes in technology also the way people think of using the technology. Hence, the most significant understanding of digitalization is not transformation.
The Agenda with Digital Transformation Services
According to businesses that work on your digital transformation, it is the holistic transformation approach that would consolidate the changes within the four prime business aspects:
- Transformation of core operations from the physical to digital – Choosing the road to digital transformation through either reshaping how the value gets delivered or rather what is getting delivered.
- Experience – Reconsidering the partner/customer plus employee experience as one complete experience feedback tool.
- Digital Infrastructure – Adopting various cloud-based devices to operate a software, build plus seamlessly integrate the newer applications, to store and/or retrieve data, also compute
- Information analytics and management – building a kind of data-driven business where the complete decision-making would depend on insights collected from the gathered data.
An extra layer of this shift is in the creation of accessible interfaces to rather efficiently operate the fresh digital tools on every level, both internal and customer-facing ones. Let us look deeper into the mentioned elements and explore the way they interact.
The Two Paths of Digital Transformation from Physical mode to Digital
There isn’t a single playbook for meeting the needs of the digital age for all businesses. Certain services that would be completely physical couldn’t survive the huge surge of disruptive digitalization. For instance, the complete video plus rental industry in the United States was removed from the market when Hulu and Netflix burst on the fore.
While there are certain brick-and-mortar organizations that experience the digital impact in a rather mild manner. Amazon, for instance, hasn’t killed the retail unit but has rather pushed it to work with newer digital instruments. The different degrees of service and products digitalization across the industries influences our path of transformation. In case an industry gets driven by sustaining innovation, the transformation must consider what could be eventually delivered plus redefine its value of it.
Path #1 – This path would signify the change within an operating model to better the workflow that is currently existing without defining the basic proposition. It would usually tie-up with the industries where the product is almost physical, where customers do not expect huge change regarding value proposition, and the revenue gets generated beyond the digital modes.
Path #2 – Transformation of what the business delivers – This path of transformation is rather helpful and preferred when there is no longer match of physical revenue streams with the expectations in digital transformations of the customers. This leads to the replacement of the physical proposition with the digital mode.
Value Proposition Transformation Path
- Better the existing proposition with digital experience – This would help both to enhance the current customer experience and thus building a brand-new digital community.
- Introducing a new stream of revenue – Add a fresh revenue stream which remains solely based on ye digital community also does not interact with the physical entity. The basic phenomenon is stretching of the brand.
- Transforming the proposition – Based on the type of industry, transformation would imply either complete replacing of the physical entity with the digital or building one integrated physical plus digital value.
Choosing one path shouldn’t get based merely on the level of digital disruption. Whereas mobility plus digital expectations of the customers are rather critical, the organizations need to consider the completely strategic decisions on several other players also the availability to shift the legacy along with the physical processes to the digital ones.
The traditional IT infrastructures along with the private cloud servers can not anymore sustain the exponentially growing endpoints along with the subsequent development of interfaces and applications to enable communications with these endpoints. We are way beyond the mass enterprise model of mobility adoption. Today there is a surge of the Internet of Things, where companies are able to track with higher efficiency and operate their corporate assets, machineries, and vehicles can gather data also analyze it from all endpoint chips. This kind of infrastructural complexity makes:
- The computing workloads rather unpredictable
- Cross-application connection difficult while considering from engineering standpoint
Analytics and Information Management
Every time we talk about analytics, the prime point of consideration is how you would shift from the assumptions, on the basis of experience plus intuition, to the direction of decision-making that is data-driven. The gradual goals in analytics are optimizing the current processes so that cost is reduced, the customer experience is personalized – we have discussed earlier that earlier process that was automated processes would use gathered data plus best practices. However, achieving these goals using analytics is inseparable from the newer methods of data and information management. These don’t just make sure proper usage of software tools but rather ground changes in the methods the organizations would operate. To understand these two aspects, let us check-in details:
Analytics at Maturity Levels
The maximum recognized approach towards gathering an understanding of the levels of developing analytics is its maturity model. It talks about how the analytics would evolve as a business moves from the assumption-based model to the decision-making model to an organization that is data-driven.
Descriptive analytics – It is the basic level of analytics that will answer the question – “what happened”? A person can receive the answer by looking at the dashboards plus reports. In maximum cases, the initiative with analytics just stops here while decisions are still based on the assumptions that would derive from the data that is partly unanalyzed.
Diagnostic analytics – Here the question is “Why did that happen”? With a constant stream of data, the descriptive analytics is not merely enough to capture that pattern that is acquired in the record, to divide the data items into segments based on similarities, or even conduct any sentiment analysis.
Predictive analytics – Here the question is what would happen? Once we have captured the data patterns along with the insights received, we would forecast the future happening based on historic data. Predictive analytics model is generally realized by the means of machine learning.
Prescriptive analytics – Here the question is “what is that we should do”? Based on all the best practices of resolving the issues, prescriptive analytics would automate the decision-making, when quite a several specific conditions are confirmed. For instance, many international banks gather various data regarding the transactions on a credit card,s and comes with a high degree of confidence, one can understand whether certain transactions are fraud. Hence, when deciding to block any suspicious card is made in a completely automatic pattern, and once identified the specific circumstances would trigger an algorithm.
The path from prescriptive to descriptive analytics can only be accomplished if any organization would make certain operational changes.
Building of the Data-driven business
Analytics would thrive within a fertile environment. However, there are several external and internal barriers to the same, from people who make decisions on the basis of their experience to the simple lacking in analytics talent. Businesses need to come up with certain strategic approaches to build organizations that are data-driven. Let us check the circumstances:
Democratize all the access to data
It is quite likely that your business is already collecting a huge amount of useful data. However, the usual scenario would be different departments are all hoarding their data also impending a complete understanding of processes for other units in business. Defeating this behavior on the C-level would enable for one jumpstart in analytics.
Collect maximum possible amount of data
Embarking on the prescriptive and predictive analytics initiative using some of the latest technological developments entails you collect as much data as is feasible. Besides the common figures, try capturing those decisions that surrounded the data use and the level of confidence those decisions had. Businesses can employ this information towards building more comprehensive algorithms that are based on machine learning.
Hiring the right talent
Analytics talent is rather scarce and really expensive when considering retention and compensation. However, an even higher magnitude of the problem is finding a business translator, a person with both data science and technical background, those who could act in a management position, and comes with in-depth domain expertise. This person needs to bridge the technical aspects within analytics with concrete interests in business and at times act as one visionary so as to foster the use of the latest techniques in data science.
If required anonymize data
In certain industries like banking or insurance, there is no way you could fully democratize your access to data and provide sensitive customer information to any consultant, analyst, or even a data scientist. In this case, we generally recommend that the data is anonymized beforehand through the simple method of substituting revealing records with certain numbers.
Setting up the strategy of digital transformation
At every business, we would recommend that you follow the mentioned steps to set up the strategy of digital transformation:
The foremost step is considering how your digitization is driven within a given industry. Begin with an assessment of the strategic moves by the industry competitors. Consider what your customer and stakeholder expectations are. Is there an impact by disruptive innovation or sustaining? Define parameters like networking and mobile levels of adoption among customers also partners.
Define the transformation path
Based on received insights, we need to consider the strategic path in digital transformation. Is there are need to reshape the operational model so that the delivery of physical service or product is supported? Is there a need to reshape the service or product to meet the partner and customer digital expectations?
Based on the path chosen, which aspect of the approach needs to be approached foremost? Access the internal operations also prioritize what must be reconsidered first. Is it about the evolution of partner/employee/customer experience? How holistic is the cloud shift and on which level of analytics maturity is your organization?
Break down all your agenda to concrete tactical positioning, What kind of acquisitors would you need to consider? Also, consider the resources with a timeline that is required to pursue this strategy.
Reconciling the domain expertise with all tech enablers
You need to connect the technical expertise with domain knowledge to consider the available solutions also foresee how these technologies could be employed in the industry in newer ways.
Studying your supplier
Study the suppliers including cloud servers. How much do the application and digital development environment of any given supplier match the choice of technology enablers contacted? How much of the investment is required to fill the technological gaps that this supplier comes with?
Building a hybrid ecosystem
The transition process from the old IT to the newer digitized ecosystem that is cloud-based sets a unique challenge of operating within a hybrid surrounding. All organizations must gradually move forward to the future platform and infrastructure while maintaining the current ones. This mandates additional budgeting for data migration and personnel training.
Expanding your business vision
As you think of any kind of transformation, you cannot overlook the dynamics of cultural change. There are studies that reveal that only 4 percent of the Fortune 500 companies worldwide are digital-ready. So that you could support change, the vision must be aligned through the entire generation, where the first-ever link in this alignment is of course the board.
To Sum Up
Digital transformation services are a broad spectrum of terms that would embrace a huge array of elements which when combined would define how any organization addresses interactions with the customers plus clients, how it would operate internal devices and manage the employee interactions, and gradually how this kind of digital framework gets supported on a technical plane. However, the main nagging challenge for any company undergoing digital transformation isn’t financed. In case of done right, digital transformation consulting services can reduce cost.