Chapter 1
Information metabolism
Optimizing operational speed and information for success in a digital world
Organizations are like organisms. They have a metabolism, a tempo at which they operate. To remain healthy, the whole organization must operate at the same speed, but in practice, organizations tend to be multi-speed.
Since customer-facing processes (such as sales) typically operate faster than back-office processes (such as fulfilment), a natural tension exists, and organizations can become dysfunctional if they are not responsive to the market. There is an imperative to simultaneously digitize the front and back office to remain healthy and effective.
This level of organizational ambidexterity is easier to explain than deliver, naturally.
Intelligent automation (IA) technologies allow organizations to accelerate functional areas without making substantial changes to systems or processes. IA also enhances an organization’s flexibility, as digital workers can be instantly redeployed as needed.
IA enables organizations to begin embracing digital transformation without having to reengineer these functional areas wholesale. This change is coming, but with IA this change will be less painful and more achievable.
There are compelling examples and leading practices of how IA impacts each of these domain areas. When embracing IA, organizations must balance the opportunities from two perspectives:
- Doing things differently – being digitally enabled
- Doing different things – being digitally transformed
Clients on their IA journey determine the best approaches for how to scale and optimize for the future. This promotes success and drives toward achieving the desired state, capitalizing on this untapped opportunity that exists within their own walls — allowing them to set and achieve a new bar of success.
Chapter 2
Doing things differently
Transformation of existing processes for digital business enablement
The first phase of transformation is becoming digitally enabled. Here, IA technologies such as RPA or machine learning (ML) are used to generate the same results from the same process, only faster, cheaper and more reliably. Most business processes have undergone decades of optimization around cost, hence achieving further cost savings is a challenge.
Few of these same processes have been optimized around speed, which means there is far more room for improvement in this dimension. Robots can be programmed to perform the same steps as humans, only 300%-400% faster, with greater accuracy and consistency.
Machine learning is a form of AI, and can be applied to widen the scope of automation by learning and managing through variability, where rules-based automation is insufficient. This layer of cognitive automation brings flexibility and resilience to the model, and when done at scale, the complete IA solution provides a meaningful basis for improving business performance with direct cost savings.
Reality of B2B response times:³
- The average first response time of B2B companies to their leads was 42 hours.
- Only 37% of companies responded to their leads within an hour.
- 16% of companies responded within one to 24 hours.
- 24% of companies took more than 24 hours.
- 23% of the companies never responded at all.
In back-office processes, it is not unusual to achieve 10%-25% cost reductions with IA. But it is also common to see 70%-90% reductions in process time in these same automations, without re-engineering the underlying processes.
Digitally enabling your business allows the same business results to be generated faster, cheaper and more consistently without substantial cost or disruption. This is an enormous step toward improving and harmonizing an organization’s information metabolism. It also prepares the organization for the next step, which is transformation.
Chapter 3
Doing different things
Creating new and unexpected outcomes
A hallmark of digital transformation is that it generates new and sometimes unexpected outcomes and value. Frequently, this value is not predictable until after it is experienced.
When Amazon launched its same-day delivery service as part of its Prime offering, many predicted it would fail. Years later, Prime has completely changed the competitive landscape for online retail.
Similarly, Domino’s new Dinner Bell service may appear to be no more than a pizza-tracking app, but the outcome of knowing exactly when your pizza will arrive may prove to be transformational.
Digital transformation means doing different things, and here IA also plays a role. Chatbots are more than a tool to automate human conversation; they may be engineered to collect time- and context-centered information from a customer so that their needs can be answered perfectly, the first time.
Artificial intelligence can be applied as a recommendation engine, sorting through enormous data sets in search of the single best answer for a specific customer need. Transformation also means that back-office functions can become more than barriers; they can be enablers of growth and innovation.
Customer satisfaction ratings for live chat are often higher than all other support channels, likely because of the speed and conversational nature.
Almost two-thirds of buyers expect a response within 10 minutes to any marketing, sales or customer service inquiry.⁵
Success with digital transformation requires a holistic approach. Customer-centered, front-office solutions often receive the most attention.
However, back-office processes must similarly be transformed to deliver the promise of front-end solutions. Maintaining a balance between front- and back-end investment in digital improves the likelihood of success.
Similarly, moving to completely reengineered, redesigned and transformed processes may prove more difficult, and riskier, than it appears. This is particularly true for customer-facing solutions. If you promise to give your customers a transformational experience and value proposition, it’s critical that your back office can deliver on that promise.
By first targeting digital enablement, organizations can identify early wins and obvious vulnerabilities in their operations, which can then be leveraged or mitigated to build upon digital success. A balanced, intentional and holistic approach yields the most reliable and resilient results, while providing speed, flexibility and adaptability along the way.
Summary
Intelligent automation (IA) draws from a spectrum of technologies, such as robotic process automation (RPA), chatbots and artificial intelligence (AI). They can equip organizations to embrace digital transformation and minimize the cost, effort and angst experienced in the journey.
A comprehensive, holistic business transformation leverages these technologies to include both customer-facing, front-office applications and customer-supporting, back-office applications. The result is a digital enterprise that can stay ahead of customer expectations for an increasingly digital and automated experience.