Steve Prentice, vice president and Gartner fellow, explores the opportunities and challenges brought by an algorithm-defined enterprise.
The term ‘algorithmic business’ is relatively new, but the practical use of algorithms is already well-established in many industries. Gartner has said that enterprise architects (EAs) and IT leaders must begin designing their algorithmic business models, both to capitalise on their potential for business differentiation, and to mitigate the possible risks involved.
The significant development and growth of smart machines is a major factor in the way algorithms have emerged from the shadows, and become more easily accessible to every organisation. Their impact can already be seen in today’s world. But there is much work ahead to harness the opportunities and manage the challenges of algorithmic business.
Outlined below are the current realities that EA and IT leaders need to prepare for as the disruption from algorithmic business accelerates.
Algorithms today
Enterprise architects and IT leaders should examine how algorithms and smart machines are already used by competitors, and even other industries, to determine if there is relevance to their own needs.
The retail sector has long been at the leading edge of using analytics and algorithms to improve business outcomes. Today, many retail analysts believe that the algorithms that automate pricing and merchandising could soon become the most valuable asset that a retailer can possess.
In human resources, algorithms are already transforming talent acquisition, as organisations are able to rapidly evaluate the suitability of candidates for specific roles, but the same technology could easily be applied within an organisation to allocate workloads to the right people.
In healthcare, the open availability of advanced clinical algorithms is transforming the efficiency of healthcare delivery organisations and their ability to deliver care.
The practice of sharing and co-developing algorithms between organisations with mutual interests could be relevant to most organisations. It is also likely to be a development model employed in many vertical industries.
New business opportunities
While digital business is already transforming organisations, algorithmic business will create even greater levels of disruption. Open algorithm marketplaces will rapidly create and incentivise an entire ecosystem of algorithm developers in the same way that app stores and mobile devices have changed software development.
Advances in technology will expand the scope of what talent recruitment involves, to create a virtual talent industry that will enable organisations to recruit smart machines and algorithms to provide the kind of expertise that is currently provided by people.
To cope with this fluidity and disruption, businesses should explore and deploy multiple business models concurrently. These business models will be created with the use of algorithms and are a necessary part of coping with the pace of change, and exploiting fleeting business opportunities, in a digital world.
These advancements will not be without problems, however, and the successful organisations of the future will examine the potential pitfalls with equal diligence.
The challenges of algorithmic business
The advances and benefits of algorithmic business will come hand in hand with obstacles to navigate. Whether the problems are anticipated or unexpected, as smart computing becomes more pervasive, the implications have the potential to make or break organisations.
For example, an extreme point of view is that any beneficial effects of algorithms on humanity may be nullified by algorithmically driven systems that are antithetical to human interests. Or, while an algorithmic business model may be deployed with good intentions, it could be manipulated by malicious humans to achieve undesirable outcomes. Undesirable, at least, from the point of the view of the person or organisation that owns or controls the algorithm.
Algorithms rely on the data they are fed, and their decisions are only as good as the data they are based on. Moreover, tricky ethical problems that do not necessarily have a ‘correct’ answer will be inevitable, as a greater complexity of decision making is left in the hands of automated systems.
The scale of change that is made possible by smart machines and algorithmic business warrants considerable planning and testing. Organisations that fail to prepare risk being left behind or facing unexpected outcomes with negative implications.
