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Published By: PwC     Published Date: Oct 03, 2019
We’re in one of the longest-running positive M&A cycles in recent history. Even as global economic headwinds develop, corporate and private equity investors continue to experience unparalleled access to capital for potential deals. This suggests that the current wave of US industry consolidations and aggressive private equity investing will continue into the foreseeable future, even as deal volume has slowed from recent peaks. At the same time, with increasing valuations for companies, expectations on sellers are more rigorous, even punishing on surprises. Proactive preparation has become mandatory; processes are more accelerated and data-driven, quality of earnings analysis and sell-side due diligence have become table stakes. Sellers have to respond appropriately and with confidence as experienced buyers move toward a close. Selling your company takes robust planning and discipline. Whether you are divesting the business completely or bringing in a private equity investor to fuel additional growth, the process you develop and follow will play a critical role in creating value for your shareholders and family. Everyone has a lot more data than even five years ago to value your business, including benchmarks and operational data sources. The one piece of information the market doesn’t have is your story: what you’ve done and what the business can do next, setting up a clear and credible case for terms you can justify. The glue that holds it together is that you are clear about buyers’ expectations, understand your company’s value and can evaluate and explain the prospects for your business. Above all, you need to have worked through what you want to accomplish for yourself and your stakeholders with a prospective transaction. To a large extent, this will determine the right exit strategy for you. Many entrepreneurs today are motivated by more outcomes than retirement or a simple wealth event. You may want to consider taking a “second bite at the apple.” This typically involves structuring an exit that divests a controlling stake but creates a continued role to grow the return on the remaining stake. Whatever path you may be considering, we hope this guide serves as a useful starting point for the conversations you will have with your stakeholders, trusted employees and family, as well as your advisers as you realize the value you’ve worked hard to create.
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PwC
Published By: SafetyCulture     Published Date: Aug 14, 2018
Consistency and customer experience are key to quality and profitability in retail. Manual reporting processes can be unwieldy and time-consuming, but bringing together all compliance procedures under one digital platform means fast, consistent and easy-to-access performance data. Using real-time insights into best practice improves the reporting of quality control, stock loss prevention, inspection processes, logistics and more – saving time, increasing efficiency and boosting customer satisfaction. Benefits include better branding through monitoring rollouts with uploaded photos and videos, protection against shrinkage through improved inspection processes and audits, and clearer visibility of issues which means a speedier response.
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SafetyCulture
Published By: Progress     Published Date: Oct 09, 2017
"The customer experience is incredibly important to business success and is often tied to customer engagement, retention rates, revenue, purchase frequency and overall loyalty. Today, the customer journey is incredibly complex, with everything from geographic location to data quality influencing the customer experience. As a result, brands may not be making the most of their customer experiences. However, with a mix of new technology combined with best practices, companies can regain control of the customer journey and create memorable experiences for their customers. "
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Progress
Published By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance
    
IBM
Published By: STARLIMS     Published Date: Apr 16, 2014
Learn how a Laboratory Information Management System can improve trace evidence management in the crime lab, but will also help analysts with data entry, documentation, and quality control.
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starlims, lims, trace evidence management, crime lab, quality control
    
STARLIMS
Published By: Melissa Data     Published Date: Nov 18, 2008
Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software, data quality tools, data quality management, data quality objects, data quality api, address quality, data cleanse, data hygiene, data quality, data quality analysis, data quality api, data quality assurance, data quality control
    
Melissa Data
Published By: Melissa Data     Published Date: Nov 18, 2008
Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software, data quality tools, data quality management, data quality objects, data quality api, address quality, data cleanse, data hygiene, data quality, data quality analysis, data quality api, data quality assurance, data quality control
    
Melissa Data
Published By: Optum     Published Date: Nov 20, 2017
Unlocking value and achieving growth in health care depends on population health management supported by a foundation of accurate, comprehensive and actionable data. This toolkit is designed to help you take immediate action to assess, refine and expand your organization’s ability to deliver improved care quality while controlling costs.
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health care, action, insight, analytics, population health management, provider, delivery, quality, growth, phm, value, optum, partner, leader, executive, toolkit, resource, implement
    
Optum
Published By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, ibm, big data outcomes, information governance, big data analytics
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : 
ibm, idc, big data, data, analytics, information governance
    
IBM
Published By: IBM     Published Date: Apr 06, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : 
big data, analytics, unstructured content, enterprise information, ibm
    
IBM
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