3 items tagged "forrester"

  • BI trends: What to expect for retail in 2019?

    BI trends: What to expect in retail in 2019?

    To help retailers and brands plan for 2019, Researcher Claudia Tajima and Fiona Swerdlow are interviewing experts within Forrester for their series, ´Applying 2019 Predictions To Retail´. This week, Claudia interviewed Jennifer Belissent, Ph.D. and principal analyst on Forrester’s consumer insights team, on their 2019 BI predictions report. Here’s what Jennifer thinks retailers and brands can expect and should focus on regarding BI for the rest of 2019.

    Claudia:Your first BI prediction for 2019 states that companies cannot be successful simply selling raw data and that self-service data marketplaces will struggle. BI tools need to start delivering data insights and services. How does this shift affect retailers?

    Jennifer: For retailers today, there is a vast amount of data that you could use to improve business and better understand your customers. Many retailers already use their data to understand their customers and forecast trends. But today is a rapidly evolving landscape of new, alternative data sources. Opportunities to enrich data with new sources are appealing. However, retailers must evaluate those opportunities carefully. Why? The time to value is longer when buying raw data instead of buying data insights. For example, buying a customer’s credit score would be faster time to value than buying the raw customer data to ultimately find their credit score. My recommendation is that retailers should not rush to buy data or expect to be able to buy data from a marketplace and get all the answers they’re searching for. In some cases, retailers need insights service providers to interpret this data.

    Claudia:How will the demand for data storytelling skills impact retailers’ talent acquisition strategies?

    Jennifer: This demand exists because there is a gap between technology users and data scientists. They don’t always speak the same language, but a storyteller can bridge the gap. Organizations need a storyteller who can talk to the business team, data team, and the technology team and help them reach a common understanding. This balance is critical for BI teams to be able to both organize data and deliver the data in a compelling way. Forrester’s research suggests that more mature companies, those that are more ´insights-driven´, have these skills.

    Claudia:Organizations are predicted to abandon unactionable BI reporting and dashboards. How should retailers respond to growing derelict dashboard graveyards?

    Jennifer: Retailers are seeking answers to questions such as: How does one store compare to others? How does it compare to regional sales? However, retailer leaders’ interest in specific reports or dashboards eventually goes down over time. Creating a data center of excellence increases more data awareness, but it also brings about a frenzy of requests for new dashboards and reports. Ultimately, many of these requests end up as orphaned dashboards. It is important for retailers to be careful of how they embrace data democratization. Take time to step back and rationalize, prioritize, and determine which data from reports and dashboards you need and don’t need.

    Claudia:Why should retailers consider adopting data fabrics in place of data lakes?

    Jennifer: In the past, many organizations chose to put their data into massive data lakes. However, these organizations did not fully think through how their data lakes should be organized and used. Today, organizations are starting to realize that there is no major benefit to putting all of their data into one centralized data lake. The new trend is to create a data fabric of woven data from across different parts of the organization that sits somewhere central. Data fabric stores maintain their own individual data, but there is a central data point where it can all be accessed.

    Claudia:What recommendations would you give to retail leaders looking into investing in BI tools in the coming 12 to 18 months?

    Jennifer: Data catalogues, which serve as a knowledge repository, are becoming very popular. Organizations typically have one centralized data catalogue. Interesting data catalogue outputs include: use cases, algorithms, as well as which reports the data has been used for and where has it been tested in sales. In terms of ambient data governance tools, retailers should look for BI tools that have data governance built directly into them.

    Author: Fiona Swerdlow

    Source: Forrester

  • Dare to disrupt with technology-driven innovation

    Dare to disrupt with technology-driven innovation

    Clients never tell their business wants to be an also-ran. Everyone wants to dominate their market and is searching for the competitive advantage that helps them do it. The drive for leadership is why growth, year after year, is the top business priority. It’s a surrogate for leadership or at least the path to it.

    The question is, “how do you create market-dominating growth over the long term?” The answer, come to find out, is straightforward: Develop new value delivery models, exploit emerging technology to create these, and deliver highly differentiated products, services, or solutions. In other words, to lead and grow, you have to do things differently.

    Most firms, however, incrementally trudge up the digital innovation curve of yesterday’s business models and technologies. The result is that customer experiences are not differentiated. Everyone uses the same approaches, the same technologies, and gets the same results. The best, we find, are practicing the disciplines of technology-driven innovation.

    Forrester has given the release date for a new report the topic of technology-driven innovation: May 13th. We can already give you a sneak peek of the key takeaways of that report.

    Key takeaways from the report

    • Technology-driven innovation creates market-dominating differentiation and growth:Technology-driven innovation flips the innovation equation on its head. It puts rapid technology experimentation at the forefront of your efforts, not last, after the current customer and business needs are understood. It lets your firm ride waves of technology-fueled disruption to change the game and create a lasting competitive advantage, which translates to long-term growth.
    • Technology-driven innovators grow 4x faster than their peers: Our research indicates that technology-driven innovation leaders grow at 3 to 4 times a faster pace than their industry average. It is a massive opportunity for those that can get it right. The rest? They will try to follow you incrementally and ultimately lose that race.
    • Technology-driven innovation will turn business on its head: This is because, as firms catch on, change will accelerate, and only firms that proactively adapt will be able to excel. CIOs at leading firms will become second in line to CEOs, but they may be titled something different and have very different, shape-shifting organizations working for them. What’s more, we think CMOs and chief sales officers will be replaced by chief growth officers as firms transform and disrupt expensive and inefficient processes that generate revenue.

    Conclusion

    Technology-driven innovation makes your organization smarter, both in general and in comparison to your competition. Daring to disrupt through technology-driven innovation can lead to radical improvements and create competitive advantages. 

    Don't be afraid to fail when it comes to technology-driven innovation, be motivated to become smarter!

    Author: Brian Hopkins

    Source: Forrester

     

  • Forrester: The developments around enterprise BI platforms for 2019

    Forrester: The developments around enterprise BI platforms for 2019

    Information technology keeps moving forward at an ever-increasing pace. Business intelligence (BI) technology isn’t falling behind and keeps constantly evolving. BI vendors can no longer be categorized as:

    • IT-focused and enterprise-scalable vs. business-user-focused BI platforms mostly going after departmental and line of business use cases. All formerly IT-focused BI vendors have moved squarely into the business-user-focused territory. And most BI vendors that originally architected their platforms for ease of use, often sacrificing scalability, have introduced large-enterprise scalability features, technology, and architecture.
    • On-premises vs. cloud BI platforms. All formerly on-premises-only BI vendors now have cloud deployment options. 
    • Data visualization platforms. Forrester no longer considers data visualization a separate, distinct market segment. It can rather be seen as a table-stakescapability of all BI and analytics platforms.

    Going forward (but no guarantees as the market will surely grow, mature, and morph again next year), Forrester will segment enterprise BI platforms into the following three categories:

    • Client-managed enterprise BI platforms. In this segment, clients are fully responsible for deploying their private instance of the BI software. They may choose to install it on-premises, in a public cloud, or hosted by a vendor. The client is ultimately responsible for the timing of upgrades and other software platform management decisions. Organizations that want to retain control over software upgrades and fixes should consider vendors in this category.
    • Vendor-managed enterprise BI platforms. In this segment, clients do not deploy but subscribe to software. A vendor maintains a single software instance and partitions it for logical private instances for each client. All clients are on the same software version, and all get the same continuous upgrades. Clients have no control over upgrades or other decisions. Organizations that are ready to completely shift software management responsibilities to the vendor should consider this category. Organizations must also be willing to use software deployed in a public cloud, as software in this category does not run on-premises.
    • In-data-lake enterprise BI platforms. These BI platforms (app server, metadata server, etc.) run entirely inside data lake clusters and do not move data (including result sets) out of clusters. Organizations that are mostly looking for a BI platform to analyze terabytes of data stored in data lakes, especially for detail-level (versus aggregate) analysis, should consider vendors in this category.

    Author: Boris Evelson

    Source: Forrester

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