Every entrepreneur today has tried swimming in the marketing waters. It is barely impossible to have a business and not have a marketing plan for your product to reach as many clients as possible. The very soul of that plan is the marketing automation – the software that will automate some marketing tasks previously done manually, like sending emails, posting on social media, SEO, blog posts, etc. It has proven to save the resources, namely money, and help your business grow. That’s only if used correctly. If not, it can do quite the opposite and smudge your reputation and brand in the process.

But don’t worry, because here we’ll show you how to avoid the most common marketing automation mistakes. …

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Your company isn’t a psychologist’s office. It’s not a life coaching facility. It’s not a social club. So why does it matter so much that you have satisfied (aka happy and engaged) employees? The answer is simple. It comes down to cold, hard finances. Research supports the idea that companies that have satisfied employees have a major advantage over companies that don’t. Satisfied employees:

• Are more productive
• Come to work more regularly
• Are less likely to leave for another job

How do you measure this engagement- or disengagement? How can you use these results, and measure their evolution over time? You can start by doing what most of other business departments in your company already do: tracking specific HR KPIs measuring employee satisfaction, and compiling and visualizing them through solid HR dashboards. Just like a lot of other business units, the human resources department is evolving into a data-driven function. This does not mean that the “human” aspect disappears, but on the contrary that it can better be assessed and the behavior, motivation, etc, can be followed and better taken into account. That will help your business make informed talent decisions, evaluate employees’ performance and operate better workforce planning.

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At the Big Data panel at the Strategic Competitive Intelligence Conference in Amsterdam, some years ago, one of the questions posed to the audience was a topic that every BI practitioner must address:  why do people focus more on the dataset rather than on the right business intelligence questions? In other words, when working with big data and business intelligence software, teams often find themselves focusing on the data, rather than the problems that the data can solve. One reason this can happen is because although organizing data is challenging, it may still be more straightforward than analyzing business problems. …

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Business intelligence software is quickly becoming a mainstay for organizations of all sizes. The resulting success stories are pouring in. Armed with BI, these companies are promoting cost efficiency, optimizing inventory levels, reducing waste, improving business processes and, in general, providing departments across their organization with the data they need to succeed via interactive dashboards. Many organizations have heard these success stories and are jumping onboard the BI train. However, recognizing the importance of data and analytics is one thing; meeting the needs of business decision-makers in the most efficient and appropriate way is a different matter. To do this you need the proper processes and tools in place and you need to follow best practices. We have already provided you with the top BI dashboard best practices. To ensure you get the desired value out of your BI investments and get you on the path to success we have come up with a top 5 of business intelligence best practices and a top 5 business intelligence worst practices you must know.

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Artificial intelligence (AI) is here and it is getting smarter all the time. For many, mention of AI immediately conjures up images of The Terminator. At the very least it makes many think of robots and machines disrupting the workforce and replacing jobs. While the latter may not be completely out of the realm of possibility, datapine is leaving that side of AI to Silicon Valley and John Connor. Instead we are excitedly monitoring and utilizing artificial intelligence in business intelligence.

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