Digital Darwinism calls for new enterprise architectures: The 7 layers to the Cognitive Enterprise

In my article "The next evolution of a successful company: The Cognitive Enterprise" I talked about how the outside-in digitization of the last 10 years has developed into an inside-out digitization.

To enable companies to make full use of their internal and external data, to make effective use of exponential technologies such as Artificial Intelligence (AI) or Blockchain, and to remain competitive in the long term, it is necessary to move towards a so-called "Cognitive Enterprise".

The Cognitive Enterpriese consists of a multitude of business platforms, so-called capability layers. We are talking specifically about 7 layers:

IBM has defined seven key measures that are at the heart of successful digital and cognitive transformations. In this article, I will give a brief overview of each one.

1. Create platforms to unleash Digital Darwinism

Today, business platforms dominate the markets in every region. Some already have the winner-take-most status. We as end consumers have been able to observe the development of mass platforms such as Amazon, Alibaba or Ebay in recent years. All these platforms are examples of extreme scaling, speed and scale of their products. In the corporate context, those who build business platforms will have a major competitive advantage in the future. The application of the right strategic criteria to the core business platform is crucial.

To date, only 28% of executives invest in a business platform model. And in fact, most companies are still dealing with fundamental questions. What parts of their business should they run as a platform? Should they join the platforms run by others? How do they respond to competing platforms? Platforms must leverage deep expertise, open workflows, and data synergies to unlock expansion potential within an ecosystem. Methodologies such as design thinking, co-creation and afile approaches should also be used for successful and rapid development.

2. Leverage the incumbent advantage in data

Exponential data growth is well known and continues to evolve. According to Gartner, corporate data will also grow by 800% by 2020.

But for many companies, enterprise-wide data integration is still more ambitious than reality. Less than 4 out of 10 companies have integrated their data across the enterprise, and the gap between those who use their data with great impact and those who don't is widening. This makes it difficult to link data together and the discovery process lengthy and costly. 

The amount and diversity of data is critical, because when combined they have the potential to create the deep accounts and insights necessary to operate successful business models. But it's not just the mass that counts, it's the value that can be created ("Not just the mass, but the class"). For example, proprietary and heterogeneous data and analysis can be integrated and curated to improve the performance of the business platform.

A topic that is currently also much discussed is bias in data in order not to falsify the results. Other aspects to consider are human error, manipulation or data drift, which can lead to data becoming inaccurate or incomplete over time. Meanwhile, companies, including IBM, are defining the importance of transparency - the need to know very well the data that is used for training machines.

3. Architect your business for change

In most companies, the corporate structure and architecture has evolved and grown historically. In reality, legacy systems today bind already outdated processes and workflows. About 30 percent of enterprise applications have been migrated to the cloud, leaving more than 70 percent of computer workloads to be migrated. Silos dominate that make it difficult to extract data, let alone use it for intelligent and immediate action.

Companies can no longer afford to take a wait-and-see approach to determining what works for others in their industry or which technology or service will "win". Enterprise architecture - like the business strategy - must anticipate the future, but also leave its options open.

To become a cognitive enterprise, companies develop new business platforms that can form a foundation for enterprise architecture. There are a few points that need to be considered:

• The intention of the business platform will determine the architectural form and advance the desired operating model of the Cognitive Enterprise.
• Enabling agility and flexibility requires some basic architectural choices to create a practical framework for progress.
• These decisions relate to workflows, data, artificial intelligence (AI) and computers.
• Intelligent orchestration of open and hybrid architectures across networks and ecosystems is required.

4. Redesign company workflows around AI

The new technologies and enterprise architectures improve both customer and employee experience. They convey a kind of creativity, are often interactive and entertaining. All this raises the bar for expectations of personal touch, human interaction, and empathy. These are all qualities that enable companies to stand out. For example, does the company know whether an inquiry was for the customer or on behalf of his mother? As a result, customer-oriented workflows have to be humanized and automated from start to finish. With AI we can also work with a sentiment analysis or tone analyzer to read e.g. in e-mails or tweets whether an author is angry, early-started or enthusiastic. Mood analysis can improve the predictive accuracy of consumer preferences in addition to traditional demographic data.

Strategic workflows should be rethought. On a business platform, workflows are not only automated, optimized and efficient. They are also agile and intelligent. They can be easily scaled so that both human and machine learn continuously. This means that adaptive business processes and workflows can no longer be viewed statically, but should be constantly developed and improved.

5. Get agile, change fast and build things

Companies should become agile, be able to change quickly and build new things. It's not just an agile methodology on how to approach projects or develop software, it's a company-wide culture that needs to be established. Agility should also eliminate bottlenecks in workflows in operational activities. A company must be able to change quickly and realign itself. Today's processes and procedures often stand in the way of this.

To date, only 16% of companies have a high level of competence with agile practices in their company. The majority is still maturing.

In the end, it is up to the managers to establish an agile organization according to the motto "closely aligned and loosely coupled. This means that managers should convey a strong sense of purpose, a kind of Nordstern, which their teams follow. If this vision is clearly communicated, employees can be enabled to independently find their way to this goal. This procedure also includes the promotion of experiments and rapid failure. And to give employees the strength to take action against established standards.

One of the most difficult changes for managers is the increasing willingness to learn. Many companies sit on a lot of data, but only use it for basic decisions. After all, agility is more than just execution; it is a means to discover and develop new strategies. And that's where managers need the courage to explore new strategies and try them out.

6. Reinvent your workforce to ignite talent

The shortage of skilled workers, which was mentioned decades ago, shows no signs of easing. Instead, there is a growing need for new skills and continuous retraining.

When companies strive to be successful on business platforms, to respond to new opportunities with innovation and speed, one thing has become clear: Everyone competes with everyone for talent.

I recently read a study in which a survey on the talent situation was conducted at C-Level. Almost half of the companies said they didn't have the talent they need to execute their business strategies. And one thing's for sure: The use of AI also requires the necessary skills and further training of employees.

Learning should be both continuous and deeply personalized. The fact is that 100% of jobs will change and that exponential learning will be a prerequisite for survival in the future. There is a very fitting quote that says: "We are not what we know, but what we are willing to learn". Instead of hiring on the basis of specific technical or professional skills, companies learn to hire on the basis of curiosity, aptitude and the ability.

As with customer experiences, AI can help companies personalize employee experiences.On the one hand, AI can help with the learning process by automatically suggesting the right learning to the employee, but on the other hand it also supports employees where exponential learning does not follow and where knowledge is made available.

7. Win with trust and security

Privacy concerns and access to authorized information are becoming increasingly important, not only in Germany. The confidence of customers that a company is protecting their data has become a compelling expectation.

Too little caution is very costly and not only in financial terms. Companies have to find a balance not to be restricted by excessive caution (because this affects customer experience and innovation) but also to ensure the necessary security.

Security must be guaranteed in both human and machine processes and appropriate governance must be put in place.

Further information on the Cognitive Enterprise can be found in the IBM IBV study "The Cognitive Enterprise: Reinventing your company with AI":