While the pandemic went into its second year, more and more companies started understanding that the new work from home trend is here to stay, with approx. 50% of employees preferring not to go back to the office full time. While working from home provided employees with opportunities to cut back on traveling expenses and to take advantage of the time they no longer spend commuting, this represented an increasing challenge for the employers who had to make sure that communication and collaboration does not have to suffer.
As such, it has become increasingly important for all the persons of a company to have a unique, centralized source of truth to rely on in order to ensure consistency and organizational alignment. And this means companies started to increase analytics investments, although the overall budgets were not increasing. Companies have performed budget rebalances in favor of data analytics, performance management and business intelligence software mainly because in times of crisis, having updated data on hand represented a must for hard-and-fast decision making.
The Top Analytics Trend is the Increasing Rate of Adoption
The disruptions which have been seen in the services industries (airlines, hotels, restaurants) and more generally in the global supply chains meant that powerful algorithms had to be employed to rapidly recalculate and reload schedules, consolidate orders, optimize shipments, monitor decreasing inventory or rebalance employee shifts to prevent burnout or ensure an equitable shift planning.
Because of the skills shortage that has been felt in all the modern economies, AI has become instrumental in compensating for these shortages. For example, with foot traffic being banned, many companies had to start their online shops and operations virtually overnight and had to carefully monitor the customer experience in order to ensure the success of their digital transition.
Cloud adoption at its highest, online e-commerce booms
While Business Intelligence is currently taking off, 2021 has seen the maturing of a trend which has been around over the last decade. A recent survey shows that roughly 90% of the responding companies indicated that they are using the cloud. While 55% of the companies say they are still using traditionally managed on-premises infrastructure, almost half of all the companies said they plan to migrate more that 50% of their applications to the cloud in the upcoming year.
As the Covid 19 crisis has forced companies to move online, ecommerce solutions such as Shopify, enjoyed exponential growth. By adopting cloud based ecommerce platforms, companies could easily scale up or down as demand fluctuated, thus having been able to turn the physical store location which has historically been a fixed cost into a variable one that also enables them to enjoy increased visibility and online traffic.
Data Engineering Trends
The need for large scale, rapid data consumption has created a high demand for Data Engineers in recent years. While companies started to understand the benefits of investing in Business Intelligence tools, they have also realized that the productivity of Business Intelligence and Machine Learning is still limited if they don’t have ready at hand data.
Subsequently, the last 2 years have taught us that adopting the cloud is the future of managing data and analytics. Since companies still rely on a mix of on-premises and cloud platforms to store and manage their data, there is a continuous need to seamlessly integrate them.
Moreover, the advent of headless API solutions have moved the challenge of creating end to end web-apps and graphical interfaces from the supplier to the customer which although gives the customer more freedom in customizing their integrations and their reporting, at the same time it adds the overhead of contracting or hiring data engineering talent.
As Data engineers have been in very high demand, with some researches ranking them as the fastest-growing job since 2019, this means companies will generally have challenges finding the right talent that can take care of their needed integrations. As such, this means they will most likely have to rely on data analytics agencies that can deliver these integrations as a service.
One notable mention is that the No-SQL databases have continued to quietly deliver efficiency and productivity for the companies that adopted them As shown here, the popularity and adoption of document databases is steadily increasing and we believe that the two responsible factors are the continued development of new web-apps and companies that need to have a unique view of their operations and customers.
While No SQL databases have traditionally been used for web apps that needed high concurrency, with a large number of users using a web apps concomitantly, they have also started being increasingly used to power the advent of omnichannel marketing as they are able to support the consolidation of diverse and different data that does not adhere to a rigid structure. This way, companies that need flexibility and being able to integrate additional data sources, marketing software and new channels are able to do that as No-SQL databases do not require having a final blueprint of the desired solution upfront.
Business Intelligence Adoption
According to this study, the global business intelligence market is predicted to expand from $23.1 billion in 2020 to reach $33.3 billion by 2025, with a 7.6% CAGR. Due to the disruptions and uncertainties brought by the COVID 19 pandemic, business leaders are faced with having to take decisions while relying on incomplete data. As such, as leaders need to keep a close eye on their sales and costs, they need to carefully assess what is working for their business and what is not and to rebalance the budgets to invest only in the most profitable advertising channels.
Moreover, as lockdown and work from home has continued well into 2021, online businesses have needed real time data to assess the efficiency of their marketing and distribution channels. Generally, keeping a close eye on revenue and costs and making frequent adjustments has become the norm so leaders now need the capability to quickly understand who their most important customers are, what is the most efficient advertising channel and who their most profitable partners are.
According to this research and confirmed by our own experience, the business functions which are more likely to adopt and frequently use BI dashboards are Executive Management, Operations, Finance and Sales. As highlighted above, the leaders of an organization need to be up to date with the financial health of their organizations and as such, the C-level executives are the most likely persons to embrace the adoption of BI tools. After the high level metrics and dashboards have already been put in place, the integration and usage of BI tools is cascaded down to include lower level metrics that show the sanity of the marketing, sales and operations processes.
As we enter 2022, we are confident that the adoption of BI tools is going to continue and that BI will finally be adopted at scale in business functions such as logistics and supply chain which surprisingly have a lot of data at their disposal but have somehow fallen short during the last year of fully taking advantage of analytics.
Furthermore, although the self-service data analytics trend is anticipated to persist, companies are expected to improve their role and responsibilities after gaining insights from initial pilot projects and experiments. Our strong belief is that the Hub and Spoke Model discussed here is the optimal approach for implementing advanced analytics within an organization. This allows business users to create their own dashboards without depending on specialized IT assistance. However, they still require pre-existing data architectures that have been thoughtfully designed and maintained by specialized professionals, such as data engineers, architects, data scientists, and BI specialists.