“Enabling clients reimagine their decision making & accentuate the business performance with AI strategy in a transformation, innovation and disruption driven world”

In today’s fast paced & volatile VUCA world, leaders face unprecedented challenges. They need to navigate through volatility while staying focused on strategy, business performance and culture.  Artificial Intelligence is fast becoming a game changing catalyst and a strategic differentiator and almost a panacea to solve large, complex and unresolved problems.  To be an AI powered organization, leaders not only need to have a broad understanding of AI strategy, they need to know how and where to use it.  AIQRATE advisory services and consulting offerings are designed to enable leaders and decision makers from Enterprises, GCCs, Cloud Providers, Technology players, Startups, SMBs, VC/PE firms, Public Institutions and Academic Institutions to become AI ready and reduce the risk associated with curating, deploying AI strategy and ensuing interventions and increase the predictability of a durable leader’s success.

In the age of the bionic enterprises, AI continues to dominate the technology & business landscape.  Under the aegis of transformation, disruption and innovation, AI has several applications and impact areas which usher a new change in how we make decisions in the enterprise and personal spheres.  Traditionally, human decisions are to a large extent based on intuition, gut and historical data.  In the age of AI, several of our decisions will be taken by algorithms.  Leveraging AI, the ability to mimic the human brain and the ensuing ability to sense, comprehend and act will significantly go up and will result in emergence of augmented intelligence in decision making. Enterprises, GCCs, SMBs, Startups and Government Institutions are attempting to harness the power of AI to change the way they do business.  All these industry segments are looking at AI becoming the secret sauce behind making them gain a competitive advantage.  If you have not started yet, you are already behind the competition, however large or pedigreed you might be.

So, where are you placed on your AI journey?  At AIQRATE, we can guide you on your journey of understanding what AI can do for you, embedding it within your business strategy, functional areas and augmenting the decision-making process.

At AIQRATE, we are here to help you with the art of the possible with AI.  Through our bespoke AI strategy frameworks, methodologies, toolkits, playbooks and assessments, we will bring seamless Transformation, Innovation and Disruption to your businesses.  Leveraging our proven repository of consulting templates and artifacts, we will curate your AI strategic approach roadmap. Our advisory offerings and consulting engagements are designed in alignment with your strategic growth, vision and competitive scenarios.

We are at an inflection point where AI will revolutionize the way we do business. The paradigms of customer, products, offerings, services and competition will change dramatically; and being AI-ready will become a true differentiator.  AIQRATE will be your strategic partner to help you to prepare for what’s next in order to stay relevant.

Enclosing here our journey walk through of 2020.

For the past few years, Artificial Intelligence has initiated unlocking value gains through the automation and augmentation of routinized operational activity. But are we underestimating the potential of machine intelligence? Does it make sense to relegate a powerful technology to perform tactical tasks? Or can AI move further upstream and help corporate boards make more accurate, strategic decisions?

The possibility of AI to enable better decision-making has been heavily discounted thus far. However, with Artificial Intelligence capably enabling more informed decisions in the realm of healthcare and investment banking – two of the most complex arenas where AI has been deployed – the possibility of having machine cognition in the boardroom no longer sounds too far-fetched. At the end of the day, corporate boards make complex decisions, that have huge ramifications for the future of their organizations. It is important that these decisions are based in fact, rather than judgement. AI can help corporate boards make faster, more accurate and unbiased decisions. AI can help inform strategy by giving executives a better understanding of their internal and external environments. Let us look at some key areas where senior executives in organizations can look at making better decisions using Artificial Intelligence.

AI for Executive Decision-Making

Corporate boards and top executives are charged with maintaining the health and competitiveness of an organization. They are responsible for the long-term sustainability and success of their organizations. This, in turn, requires them to stay ahead of the curve and understand their business landscape and intelligently deploy capital across inorganic and organic growth channels. Executives also own the key metrics for their organizations – and ensure that the overall return for the shareholder capital employed continuously beats industry expectations. Let us look at how AI can help transform the activity of executives in these areas.

Executive leaders often rely on numerous reports around key organizational metrics to make decisions that can have massive implications for their businesses. Is a particular segment of the business growing rapidly? Are some cost centers underperforming on their efficiency metrics? Are there laggards in the product portfolio of the enterprise that are dragging performance down? All these numbers have to figuratively be at the tip of an executive’s tongue – so that in key meetings decisions that affect the future of the business can be made more accurately and quickly.

AI-powered smart assistants would be extremely critical to help push the needle on making executive decisions with accuracy and speed. With intelligent bots, executives can be provided updates on the most critical metrics that they care for at the right time when they need them. With AI, it is possible to personalize the insights that are sent to executives – so that they are able to drill down and understand the basis for each metric.

Unbiased Capital Allocation on R&D and M&A Activities

Corporate boards and executives also need to take the long term view of how their companies evolve to thrive in the future. This requires intelligent bets to be taken on budgetary spending – for both organic and inorganic activities. How much money needs to be realistically spent on Research and Development activity and how it can it help corporations maintain larger moats against their competition? Can corporations look at inorganic acquisitions to accelerate the growth of synergistic capabilities that can form much more compelling value propositions?

AI will soon be able to provide comprehensive answers to such questions. By leveraging data from multiple sources combined with intelligent algorithms, AI will be able to weigh these multiple options and identify which one is best suited for each unique situations. In this way again, AI can help executives forecast which decisions can have maximum impact on financial metrics and model the long-term health of the organization.

As corporate boardrooms take serious cognizance of having robotic counterparts augmenting the decision-making process, it is important to consider certain caveats. For AI to work to its full potential, it is important to ensure that it is provided high quality data and continuously refined algorithms. We have seen the fallouts of algorithms going awry before. Biased algorithms working off bad data sets create issues that could potentially disrupt the fabric of the organization. It is therefore important that organizations ensure the implementation of explainable AI that can provide the rationale and take accountability of the decisions that it powers. Finally, it is important that executive leaders also create the right culture within their organizations for AI to thrive. A combination of human intelligence and artificial intelligence is the future and hence it is critical that companies relook at their culture to ensure that both can amicably survive together and put the organization on the right path.

According to research by McKinsey, it is estimated that 16 percent of board of directors did not fully understand how the dynamics of their industries were changing and how new technologies could impact their businesses. This gives AI a huge window of opportunity to permeate through global boardrooms and power better decisions. Decisions that can keep their organizations financially healthy, focused on the long-term and competitively differentiated against their competitors.

A considerable amount of current conversation in the area of data science and analytics focuses on the virtues of solving all the challenges that organizations face when using this new paradigm in the business world. There is also a lot of discussion around the technology-related issues that impact achieving data science and analytics goals.

What hasn’t gotten the attention that it merits, however, is the role of business leadership and how thought leaders need to raise the stakes to become not only well versed in analytics, but to build data science and analytics literacy throughout their organizations. They need a heightened awareness of analytics if they are going to effectively drive analytics strategies and outcomes for their organizations and become true leaders in this area by all relevant measures.

The following three significant findings from align with this point of view:

• Create a culture for making fact-based decisions.
• Establish a common data science and analytics vision—and strategy—to focus everyone on the outcomes.
• Instill analytics expertise across the entire organization, from the top down.

Senior executives and business managers should aspire to create the core competencies and to develop analytical insights that enable them to become data science and analytics leaders within their industries. Education, mentorship, and consultation with outside advisors should be implemented to gain the knowledge necessary to attain a leadership role. When selecting a consultancy, business leaders should choose one that can advise, mentor, and support based on specific needs and levels of maturity, as opposed to those that may take a force-fit approach that essentially attempts to force a round peg methodology into a square pegenvironment. And a good grasp of numbers in respect to numerical literacy is also important in this age of fact-based decision making based on insights derived from large volumes of data.

Numerical literacy means acceptable levels of working knowledge and experience in decision science in which analytical techniques such as statistical and descriptive analysis, forecasting, and performance management can be applied. In addition, moving from a gut-based decision model to a fact-based one requires both cultural change as well as the tools and know-how required to create and manage the facts themselves. Finance teams can typically be the source of such competencies, and they can be used as a center for fostering and developing these competencies across the enterprise. It is ultimately at the mercy of top level management on how they are going to leverage their business acumen to instil a cultural change to foster data thinking.

Bringing In Data Mentors At The Very Top

Today’s executives and managers are trained primarily in operations, finance, marketing, and sales, along with a bit of strategy thrown in for good measure. While a significant number of senior executives in the US have advanced degrees in their field of expertise, few have been formally trained in information management, analytics, or decision science. Yet, virtually none have been schooled in decision science, information theory, analytics, or risk management. Lack of training in these areas creates a dilemma for those organizations that want to focus on data science and analytics but do not have experienced leaders who can lead from a position of domain expertise. But that wouldn’t mean stacking up data workers at the TLM (top level management). Leadership drive , domain insight and People Skills will still be the most coveted virtues at the very top. But the lack of ground level data-sifting skills need not be only plugged at the lower levels. To achieve these competencies without formal education or hands-on experience requires consultation with outside data mentors and advisors who can work hand in hand with the entire senior executive team. These advisors help ground the team in both the science and the pragmatics required to achieve successful data science and analytics outcomes that can be applied pervasively across the organization. This approach—some call it the “charm school” approach—can be characterized by a close collaboration among all parties involved. It can rapidly accelerate the process of nondisruptively developing the senior executive team’s data science and analytics expertise and competency to maximize strategic outcomes.

Data science and analytics success should be driven by the business, and more importantly from the ranks of its senior executives and managers—not from the bottom up or from the IT function. The inherent accountability for all strategic initiatives is at the very top of the organization and cascades down and across to business managers at various levels who then have responsibilities for its execution within their area of control. Organizations today remain hierarchical in both structure and cultural behavior. To change either of these structures requires engaged and competent senior executive teams that are committed to the outcome and can influence and align behaviors to support it.

Strategic Thinking in Data Monetization

A number of organizations have come to this realization already. They’re now engaging with management consultancies and analytics boutiques to address their shortcomings and accelerate results from their data science and analytics strategies and successfully monetize them. Alongside these mentoring activities, organizational leadership is strongly advised to consider organizational structures and change readiness as complementary endeavors. They can help illuminate the revisions to structure and Organizational Change Management (OCM) activities required to bring the entire organization to a level that they could start assessing the monetizing estimates of data thinking. These accompanying measures can also bring cohesion to the entire data science and analytics strategy and the pursuit of its outcomes.

Firms that are looking to monetize Data and their Data Science strategies, must look beyond the data and into the economic questions that the data can answer. Often the data can help answer questions about the value, use, risk, or future value or risk of a specific asset. Or the data can say something about an overall market and how asset classes perform and how customers behave generally. Such insights are understood to have great economic value to asset owners and market participants. However, not all data will offer these features or value. The temperature readings from inside our refrigerators are unlikely to alter markets. However, the temperature readings of our furnaces and air conditioners could, in aggregate, drive new energy conservation and policy decisions.

Transforming data into economic insights will be the focus of top level executives who will monetize data. This transformation will require the creation of data products. It may be that such data products can be sold or traded to clients. It can also be that giving away data products  will drive other related monetization strategies. Hence creating the data product will not only require technical expertise with manipulating data but a clear vision on how data can be leveraged to answer economical questions and how the future market of the various domains will pan out.