by Mike Pearl

Why CEOs believe problem solving through data is the future of business

Apr 14, 2017
AnalyticsBig DataCloud Computing

The collective CEO future vision is one where technology and data enabled capabilities will be the future of business decision making, but many IT decision-makers still experience challenges regarding 'problem solving through data.'

bigdata problem thinkstock
Credit: Thinkstock

A recent statistic caught my eye: according to a study by IDG Enterprise, 53 percent of IT decision-makers report that their company is planning to implement a data-driven project, and specifically – a project with the goal of generating greater value from existing company data within the next year. [1] Within the same survey, 78% of respondents report feeling strongly that the analysis of big data could potentially fundamentally change the way their company does business, and 71 percent feel strongly that data will create new revenue streams and lines of business within three years. [1]

Now what makes this interesting to me is that at the same time, 90 percent of these same IT decision-makers surveyed report having directly experienced challenges in the use of such data – the same data that they predict will revolutionize the way their company looks at everything from business performance and revenue streams, to supply chain and HR. The major pain points are cited as data access and analysis (38 percent)), followed by data transformation (17 percent), data creation/collection (13 percent)), and migration issues (13 percent)). [1] At the same time as advocating data project spend, they have almost across the board experienced challenges in making their projects a successful reality.

Despite these seemingly contradictory findings, the overwhelming belief in the positive impact that technology and data will have on business remains strong. According to PwC’s 20th CEO Survey, a major trend on the minds of global CEOs is that business growth will increasingly come from prioritized investment in innovation, and digital capabilities (23 percent) and 15 percent) respectively), and growth and corporate profitability will no longer be supported through traditional levers or business models alone. The study cites that 61 percent) of CEOs surveyed rank “problem solving” as the number one important and desirable skill in future hiring – making it clear that the collective CEO future vision is one where technology and data enabled capabilities will be the future of business decision making. Clearly, the age of problem solving through trust and reliance on data is upon us. To make this point even more clear, consider that the same CEO Survey noted that one of the fastest growing skills needed in the enterprise are data engineering and data analysis. [2]

ceo survey PwC

IT’s flexibility and change paradox

When considered together, all of these figures might paint a picture of mixed messages for the future. There is no shortage of talk and predictions of the many innovations that the internet of things (IoT), artificial intelligence (AI), big data and cloud computing are expected to deliver. On the other hand, it is clear that the individuals tasked with implementing the future of business, technology leaders and IT decision-makers, have some real challenges when it comes to turning these predictions into reality. What is missing in recent conversations about the enterprise data and analytics innovation journey is what the path towards the CEO vision of ‘problem solving through data’ might look like. If the statistics put out by IDG Enterprise are any indication, there is great uncertainty on the road ahead to carry out the bold visions of the future of technology in enterprise by those who have been given the task.

Steer your enterprise in the right direction

There are several objectives that companies should consider in order to set themselves up for future success. To take advantage of the latest trends in driving insight through analytics, organizations should not underestimate the challenges with first harnessing the massive volumes of data that currently exist and will only grow larger. At the highest level, successful business outcomes can only be achieved when companies have a strong roadmap in preparing their existing data sources to work in concert with one another. Adopting a flexible as-a-Service model to reduce unnecessary infrastructure costs and remove growth constraints will be important, as will be enabling non-technical end users for success. Analytics automation and the on-demand “do it yourself” reporting make consuming analytics and making data-driven decisions more accessible to even the least “tech savvy” users.

Companies need to realize the most common obstacles to data access, collection and preparation and how to solve them.

No matter the size, businesses already have most of the data they need to succeed. The reason many fail to benefit from analytic investments is the incompatibility of data types, formats, aging, etc., which naturally happens when data is sourced from disparate and incompatible systems. The old mentality teaches us that all data must be in the same system or on the same platform to be beneficial, but with new data ingestion, transformation and integration technologies this is no longer the case. When looking to invest, organizations should focus on architecting a platform that is scalable and flexible with the sophistication to seamlessly ingest multiple sources and types of data (i.e. events, batch, streaming, structured, unstructured, etc.) and integrate, transform, and prepare it to be consumed by visualization and analysis tools.

Companies should choose flexible platforms and on-demand services to leverage investments most effectively.

The as-a-Service trend is here to stay, and it certainly applies when considering the ultimate platform to host and hold your enterprise data. Inflexible or incompatible solutions are outdated now that new technologies are available that allow complete elasticity in how data is stored, managed and retrieved. With a focus on modern integration solutions, organizations can gain access to a multitude of the latest third party tools and services, allowing for significant flexibility in getting your data to work with any new tool that comes on the market. The added benefit with this level of flexibility is the ability to pilot solutions within your enterprise to see what work best for your specific needs and circumstances. It is no longer necessary to become locked into a certain set of technologies or tools when you open yourself up to the app-like flexibility of the current Analytics-as-a-Service technologies.

Automate analytics with on-demand business reporting and visualizations like “do it yourself” and “do it for me” insights to make the right decisions possible for the basic end-user.

Big data and analytics technologies organized in the ways outlined above can provide great business decision making insights, but this can only go as far as the business’ ability to understand and have access to it in real time, and on demand. One of the more significant challenges that enterprises can face when implementing analytic services is the human challenge of getting users to consume and understand the outputs. Luckily, advancements are being made to visualization and reporting methods that cater to all user types – from novice non-technical users who prefer business analysts to curate and analyze data in a “do it for me” model delivering insights directly to their inbox, to more advanced users who prefer a “do it yourself” model leveraging self-service analysis and custom reporting capabilities with real time information coming directly from source systems. Gone are the days of IT requests for cumbersome datasets and static reports, with uncertainty around data completeness, or in some cases a complete lack of transparency into certain systems all together. Access to usable, accurate and dynamic reporting is a critical factor towards getting any analytic or data investment to become trusted and institutionalized, delivering the benefits an organization expects.

About the author

In my role as Global and US Cloud Computing leader at PwC, I help large and small companies think through these challenges on a daily basis. Because of our regular interaction with company data challenges and deep expertise with solutions, PwC has developed a portfolio of data and analytic solutions to help even the most challenged companies quickly begin taking advantage of their enterprise and business data. Our Real-Time Insights solution was developed through years of experience with the most difficult challenges our clients face when putting data and analytics to work. Our full set of strategic alliances and partnerships speed time-to-market and make it possible to deliver data-driven decision making into the hands of the business – faster and easier than you might think.

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