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Enterprise Analytics: How to Implement it and Generate Real ROI

Companies have been investing in enterprise analytics applications for decades, but until recently, the companies who implemented business intelligence solutions weren’t certain they were getting the return they expected. In fact, according to the Analytics Comes of Age study of McKinsey, 50% of businesses say that analytics and Big Data have altered their business practices for the better. 

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For many companies, analytics projects aren’t driven by IT. The Gartner study said that about sixty-four percent of big data projects were driven by departmental managers outside of IT, and by the CIO. Line of business managers are seeking ways to generate more value from the vast amounts of structured and unstructured data stored:

  • On private and public clouds
  • On their on-premises servers and storage systems
  • In hybrid environments

Large and medium businesses with multiple departments have elevated their expectations to acquire and implement business intelligence systems which:

  • Process and create visualizations of data from many different departments
  • Connect to a variety of business applications by way of an open API
  • Present business performance insights in formats which non-IT users can understand and customize
  • Processes large volumes of data, and presents descriptive and predictive insights fast

Emerging Repositories of Data

The digital age has produced a number of new data sources for BI engines to drill into. For example: web content, social media channels, mobile applications, and cloud based applications for a variety of customer, project management and other business functions.

There have been BI tools in the market for many years which could pull information from multiple sources, although historically, they required a great deal of technical know-how to connect, configure and customize to departmental systems. Further, even if divisional applications aren’t integrated, big data systems are expected to identify the relationships between circumstances like:

  • Poor Net Promoter scores and declining contract renewal rates
  • Parts inventory shortages and difficulties collecting payments for delayed order deliveries
  • In retail, relationships between products which customers frequently buy, and the marketing campaigns they respond to
  • Distribution delivery routes and complaints about late shipments

Accurately identifying trends and patterns across customers, prospects, employees and other people in your business ecosystem is the “Holy Grail” of analytics applications. Not just people, but products, locations, finances, and other elements of your business.

Reasoning through Lifecycles, Not Phases

Businesses with multiple departments benefit from being able to identify relationships between different departments such as sales, marketing and customer service. The ability to track data over an extended period of time is critical.

Tracking relationships with customers from the lead stage through to purchase and beyond can generate valuable intelligence for companies, such as:

  • How to market to other customers/prospects with similar persona profiles more effectively
  • The ability to act decisively on reliable data, and to share it with colleagues and other stakeholders. Leading enterprise analytics applications provide real-time performance data, or close to it. Instead of guessing how to resolve business challenges, data can identify concerning trends and suggest best course of action plans
  • Reliable data from multiple areas of your business can be sourced and shared across your business to privileged executives. Instead of acting in isolation, divisional management can co-operatively plan to address elements of business challenges/objectives that are within their control

The ability to track business performance over long periods of time, and the relationships between departments during that time will surface some important trends. Of course you need to be able to pull that information into your analytics system from their systems.

You could collect the information manually, process it, and massage it into a way which can convey the results simply. But the time, effort and potential for human error could skew the data, and the value of your efforts. Data visualization apps with powerful API’s take the guesswork, and potentially the manipulation out of manually generated reports.

After the Harvest, Invite Everyone to Feast

Implementing an enterprise-wide analytics system is great, but making the results available to only a select few diminishes the potential value of your investment. Once you have a system to regularly collect, process and present data, circle your company’s wagons. Sharing real-time results, and discussing them in real-time will:

  • Enable departmental managers to make decisions on reliable data faster
  • Help employees appreciate the impact of their team’s results across the company, as opposed to as an isolated entity
  • Encourage further collaboration between departments when they see the benefit of sharing results, both good and bad
  • Build opportunities to create revenue from your data, instead of it being a cost center and a burden.

Consider the ramification of anonymizing your data, and then sharing some of the statistics with your customers, partners and investors. If your products are performing better, and lasting longer than they were a few years ago, this is data you should be sharing. Customers are looking for evidence of your expertise, reliability and how you are different from your competitors. Investors are interested in your company’s performance and future direction. Some powerful ways to use your data include:

  • Infographics
  • Benchmarking data
  • Analyst reports
  • Whitepapers and other gated content
  • Sales and investor/potential investor pitch presentations
  • Recruiting new employees, channel partners and suppliers

Creating accurate, timely presentations of your corporate data for external stakeholders builds trust and credibility. If your company is all “on the same page” as to the latest results, and what is being done to improve or sustain them, a consistent voice is a good thing.

Implementing Analytics to Tell Better Stories

If the marketing gurus are right, and success in business comes from the ability to tell good stories, then inter-departmental business intelligence is a great way to prove you are sharing authentic stories, not myths. Let’s say your company released a new product to market, which led to a boost in sales. Or you acquired another company, which opened up a new market segment. If you keep that story a secret,

Just like when we were kids, stories benefit from a hero, a quest, some drama, comedy and some learnings along the way.  If you identify positive trends in your business and follow the data to the people behind the trends, you’re sure to find some heroes to celebrate. You can ask them how they were successful, and share their tales with employees, customers and partners.

Does your company have a variety of departments, all using individual business applications and analytics tools? Consider consolidating on a single, enterprise reporting system. Connect the dots between peaks and valleys in your business trends, and learn how to grow your business with a macro view of your operations. If you can’t see the forest because you are too busy looking at the trees, take a bird’s eye view instead.

Chris Miller

By Chris Miller

Chris Miller is a senior customer service analyst at FinancesOnline. For more than 5 years now, he has witnessed and written about the tremendous impact of digital technologies that have deeply disrupted the customer service industry. The onset of chatbots and other AI/ML tech, omnichannel platforms, highly personalized service, the emerging blockchain methodologies specially created a deep impact, all of which are reflected in his writing. His reviews of customer service applications serve as invaluable resources for businesses of any size and scale.

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