A recent global study undertaken by IDC for Sisense found BI and analytics were top of the list of programs canceled due to COVID budgetary shrinkage, and while AI adaption is on the rise, many organizations are looking to either replace or extend their BI and analytics capabilities over the coming year.
The report found 65% of organizations either canceled or temporarily delayed BI and analytics projects, and more than 50% either reduced or froze their BI and analytics budgets last year.
This is particularly hard to swallow when you take into account the findings of a recent Gartner survey, which shows 50% of organizations lack sufficient AI and data literacy skills to achieve business value.
The fact is, there is more of a need for analytics to be at the center of a business to survive, innovate and thrive in a world where tech is changing fast, markets are changing or disrupted, competitors are evolving, and customer needs accelerate, so cutting back on BI and analytics is only going to inhibit growth even further.
Every company must become a data company; there’s no getting around it. Savvy organizations know they don’t need to fear data and analytics — they see better insights as the pathway to a brighter future by making smarter, more informed business decisions.
Staying on top of the complex data landscape
BI and analytics teams are struggling to keep up with the volume and complexity of data. Data must be gathered from multiple departments and be brought together cohesively before it can even be utilized. Many organizations cite the complexity and volume of this data generated from multiple sources as the main challenge that limits their ability to generate actionable insights in a timely manner. And timely decisions are key to business success – real-time decisions are really table stakes in the hyper-competitive landscape post-pandemic.
It seems most organizations are currently using less than 10 data sources, but plan to use more than 10 in the future, with software companies using the largest number of data sources. The most important advanced analytics capabilities for data executives are connecting to multiple data sources (considered either important or extremely important by 71% of respondents), data profiling for data quality (66%), embedded analytics capabilities (66%), and mobile capabilities (65%). Gartner reports cloud can provide the necessary flexibility to utilise data effectively, in fact it reports 80% of analytics innovation is happening to the cloud.
The Sisense survey, conducted in November 2020 with 200 companies, also found 23% of BI and analytics teams are planning to replace their solutions in the next year, due to a lack of cloud architecture and API-first platforms; while 17.5% of organizations are launching new BI and analytics projects, led by software companies (48.3%) and healthcare organizations (29.6%); and 20.5% of organizations have increased their BI and analytics projects over the last year.
Similarly, more than half (nearly 52.4%) of all surveyed organizations are planning to replace their BI and analytics solution within the next two years, and nearly 75% are planning to add another BI and analytics solution in the coming two years.
Why is this? Given the abundance of tech on offer to organizations now, many have found they made the wrong choice, or chose a platform unsuitable to their use case. Many vendors still lack cloud architectures and API first platforms, and are using dated tech which is not keeping up with AI and more advanced features necessary for the modern analytics-driven companies.
Other reasons for the replacement of existing solutions are ease of use, performance, and the ability to customize and extend functionalities as data analysis becomes more demanding.
Good news for AI….so far
As data gets more complex and harder to both collate and analyze, or serves up historical insights that go to the wrong person, AI adoption is on the rise, with 92% of organizations either using or planning to use AI as part of their BI and analytics solutions, mainly for anomaly detection and altering, automation of data preparation, and serving up the right insights in real time to the right person in order to make smarter, more informed business decisions, rapidly.
The adoption of AI as part of BI and analytics is particularly strong in finance (70.1%), software (69%) and retail (64.3%), and 52% of business consulting and transportation/logistics companies plan to use AI within the next two years.
Tackling data skills and talent shortages
As data needs extend, now, more than any other time in recent history, the data professional is under pressure to ‘deliver’ – deliver by finding insights in customer behavior, deliver by discovering new levers to pull and deliver to find cost savings.
The skills requirements of the data professional are even more important, and the market changes are moving so fast we can’t keep up. Couple this with the fact the data sets we might have previously relied on, particularly with regard to economic activity or customer behavior, now don’t have a lot of relevance to what we’re actually seeing in the real world anymore.
No business can beef up its data capabilities overnight. To get data smart takes a few things: Longer-term thinking, data democratization, c-suite buy in, and continual education.
The survey shows 51% of organizations employ more than 20 data workers, 64.5% of finance companies and 62.1% of software companies employ more than 20 data workers, and 24.3% of manufacturing companies employ 2-5 data workers.
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HR and marketing departments are leading the data way, with 69.3% of HR and 68.7% of marketing departments currently relying on data sources for decision making, followed by IT (59.3%). Engineering (25.3%) and product teams (26.7%) make the least use of data sources, but 39% and 40% of them, respectively, are planning to use data in the future.
Why are BI and data analytics important now more than ever?
As mentioned above, every company now needs to be a data company, not only to achieve growth, but to deliver business resilience, and to survive and thrive.
More than half of organizations surveyed look to improve efficiency by using BI and analytics. At the same time, 52% of software companies and 50% of finance companies use BI and analytics to identify new revenue streams. More than half of respondents in retail and manufacturing (56% each) look to cut costs through the use of BI and analytics.
Data and its proper analysis is increasingly making the difference to businesses looking to gain a competitive edge, while cutting costs and driving innovation. The question now is not whether an organization should be looking to BI and analytics, but how they will actually go about it.
Sisense is helping bridge that skill set gap, empowering organizations to unlock business potential faster with AI-powered Explanations, an enhanced live data experience, and a robust new reporting service to make smarter, more informed business decisions.
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[…] don’t have the AI and data skills needed. This stops them from using data to add value32. It shows how vital it is to teach staff about AI and provide them with training. Also, about 75% […]